program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3510.2.1"}, {"coremlc-version", "3500.32.1"}})] { func main(tensor length, tensor mel) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, dict, tensor>>>>((("DefaultShapes", {{"mel", [1, 128, 100]}}), ("EnumeratedShapes", {{"length_1_1_1_1_1_mel_1_1_1_128_1000_", {{"length", [1]}, {"mel", [1, 128, 1000]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_100_", {{"length", [1]}, {"mel", [1, 128, 100]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_1500_", {{"length", [1]}, {"mel", [1, 128, 1500]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_2000_", {{"length", [1]}, {"mel", [1, 128, 2000]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_200_", {{"length", [1]}, {"mel", [1, 128, 200]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_3000_", {{"length", [1]}, {"mel", [1, 128, 3000]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_300_", {{"length", [1]}, {"mel", [1, 128, 300]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_400_", {{"length", [1]}, {"mel", [1, 128, 400]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_500_", {{"length", [1]}, {"mel", [1, 128, 500]}}}, {"length_1_1_1_1_1_mel_1_1_1_128_750_", {{"length", [1]}, {"mel", [1, 128, 750]}}}})))] { tensor var_6 = const()[name = tensor("op_6"), val = tensor(1024)]; tensor var_11 = const()[name = tensor("op_11"), val = tensor(128)]; tensor var_12 = const()[name = tensor("op_12"), val = tensor(8)]; tensor var_21 = const()[name = tensor("op_21"), val = tensor(-1)]; tensor var_22 = const()[name = tensor("op_22"), val = tensor(0)]; tensor var_26 = const()[name = tensor("op_26"), val = tensor(1)]; tensor x_3_perm_0 = const()[name = tensor("x_3_perm_0"), val = tensor([0, 2, 1])]; tensor mel_to_fp16_dtype_0 = const()[name = tensor("mel_to_fp16_dtype_0"), val = tensor("fp16")]; tensor tensor_2_axes_0 = const()[name = tensor("tensor_2_axes_0"), val = tensor([1])]; tensor mel_to_fp16 = cast(dtype = mel_to_fp16_dtype_0, x = mel)[name = tensor("cast_284")]; tensor x_3_cast_fp16 = transpose(perm = x_3_perm_0, x = mel_to_fp16)[name = tensor("transpose_482")]; tensor tensor_2_cast_fp16 = expand_dims(axes = tensor_2_axes_0, x = x_3_cast_fp16)[name = tensor("tensor_2_cast_fp16")]; tensor var_92_shape_cast_fp16 = shape(x = tensor_2_cast_fp16)[name = tensor("op_92_shape_cast_fp16")]; tensor gather_0 = const()[name = tensor("gather_0"), val = tensor(1)]; tensor gather_1_axis_0 = const()[name = tensor("gather_1_axis_0"), val = tensor(0)]; tensor gather_1_batch_dims_0 = const()[name = tensor("gather_1_batch_dims_0"), val = tensor(0)]; tensor gather_1_validate_indices_0 = const()[name = tensor("gather_1_validate_indices_0"), val = tensor(false)]; tensor var_92_shape_cast_fp16_to_int16_dtype_0 = const()[name = tensor("op_92_shape_cast_fp16_to_int16_dtype_0"), val = tensor("int16")]; tensor select_1_to_uint16 = const()[name = tensor("select_1_to_uint16"), val = tensor(2)]; tensor var_92_shape_cast_fp16_to_int16 = cast(dtype = var_92_shape_cast_fp16_to_int16_dtype_0, x = var_92_shape_cast_fp16)[name = tensor("cast_283")]; tensor gather_1_cast_uint16 = gather(axis = gather_1_axis_0, batch_dims = gather_1_batch_dims_0, indices = select_1_to_uint16, validate_indices = gather_1_validate_indices_0, x = var_92_shape_cast_fp16_to_int16)[name = tensor("gather_1_cast_uint16")]; tensor gather_1_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_1_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_2 = const()[name = tensor("gather_2"), val = tensor(128)]; tensor const_0 = const()[name = tensor("const_0"), val = tensor(0)]; tensor const_1 = const()[name = tensor("const_1"), val = tensor(1)]; tensor gather_1_cast_uint16_to_int32 = cast(dtype = gather_1_cast_uint16_to_int32_dtype_0, x = gather_1_cast_uint16)[name = tensor("cast_282")]; tensor var_95 = range_1d(end = gather_1_cast_uint16_to_int32, start = const_0, step = const_1)[name = tensor("op_95")]; tensor expand_dims_0_axes_0 = const()[name = tensor("expand_dims_0_axes_0"), val = tensor([0])]; tensor expand_dims_0 = expand_dims(axes = expand_dims_0_axes_0, x = var_95)[name = tensor("expand_dims_0")]; tensor shape_3 = shape(x = expand_dims_0)[name = tensor("shape_3")]; tensor concat_0_axis_0 = const()[name = tensor("concat_0_axis_0"), val = tensor(0)]; tensor concat_0_interleave_0 = const()[name = tensor("concat_0_interleave_0"), val = tensor(false)]; tensor concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (gather_0, gather_1_cast_uint16_to_int32))[name = tensor("concat_0")]; tensor real_div_0 = real_div(x = concat_0, y = shape_3)[name = tensor("real_div_0")]; tensor var_97 = tile(reps = real_div_0, x = expand_dims_0)[name = tensor("op_97")]; tensor var_98_axes_0 = const()[name = tensor("op_98_axes_0"), val = tensor([1])]; tensor var_98 = expand_dims(axes = var_98_axes_0, x = length)[name = tensor("op_98")]; tensor time_mask_1 = less(x = var_97, y = var_98)[name = tensor("time_mask_1")]; tensor var_100_axes_0 = const()[name = tensor("op_100_axes_0"), val = tensor([-1])]; tensor var_100 = expand_dims(axes = var_100_axes_0, x = time_mask_1)[name = tensor("op_100")]; tensor shape_4 = shape(x = var_100)[name = tensor("shape_4")]; tensor concat_1_axis_0 = const()[name = tensor("concat_1_axis_0"), val = tensor(0)]; tensor concat_1_interleave_0 = const()[name = tensor("concat_1_interleave_0"), val = tensor(false)]; tensor concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (gather_0, gather_1_cast_uint16_to_int32, gather_2))[name = tensor("concat_1")]; tensor real_div_1 = real_div(x = concat_1, y = shape_4)[name = tensor("real_div_1")]; tensor var_102 = tile(reps = real_div_1, x = var_100)[name = tensor("op_102")]; tensor gather_3 = const()[name = tensor("gather_3"), val = tensor(1)]; tensor gather_4 = const()[name = tensor("gather_4"), val = tensor(1)]; tensor gather_6 = const()[name = tensor("gather_6"), val = tensor(128)]; tensor var_108_axes_0 = const()[name = tensor("op_108_axes_0"), val = tensor([1])]; tensor cast_4_to_fp16_dtype_0 = const()[name = tensor("cast_4_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_102_to_fp16 = cast(dtype = cast_4_to_fp16_dtype_0, x = var_102)[name = tensor("cast_281")]; tensor var_108_cast_fp16 = expand_dims(axes = var_108_axes_0, x = var_102_to_fp16)[name = tensor("op_108_cast_fp16")]; tensor shape_9_cast_fp16 = shape(x = var_108_cast_fp16)[name = tensor("shape_9_cast_fp16")]; tensor concat_2_axis_0 = const()[name = tensor("concat_2_axis_0"), val = tensor(0)]; tensor concat_2_interleave_0 = const()[name = tensor("concat_2_interleave_0"), val = tensor(false)]; tensor concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (gather_3, gather_4, gather_1_cast_uint16_to_int32, gather_6))[name = tensor("concat_2")]; tensor real_div_2 = real_div(x = concat_2, y = shape_9_cast_fp16)[name = tensor("real_div_2")]; tensor expanded_mask_1_cast_fp16 = tile(reps = real_div_2, x = var_108_cast_fp16)[name = tensor("expanded_mask_1_cast_fp16")]; tensor input_3_cast_fp16 = mul(x = tensor_2_cast_fp16, y = expanded_mask_1_cast_fp16)[name = tensor("input_3_cast_fp16")]; tensor tensor_4_pad_type_0 = const()[name = tensor("tensor_4_pad_type_0"), val = tensor("custom")]; tensor tensor_4_pad_0 = const()[name = tensor("tensor_4_pad_0"), val = tensor([1, 1, 1, 1])]; tensor tensor_4_strides_0 = const()[name = tensor("tensor_4_strides_0"), val = tensor([2, 2])]; tensor tensor_4_dilations_0 = const()[name = tensor("tensor_4_dilations_0"), val = tensor([1, 1])]; tensor tensor_4_groups_0 = const()[name = tensor("tensor_4_groups_0"), val = tensor(1)]; tensor encoder_pre_encode_conv_0_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1280))), name = tensor("encoder_pre_encode_conv_0_weight_to_fp16_palettized"), shape = tensor([256, 1, 3, 3])]; tensor encoder_pre_encode_conv_0_bias_to_fp16 = const()[name = tensor("encoder_pre_encode_conv_0_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1408)))]; tensor tensor_4_cast_fp16 = conv(bias = encoder_pre_encode_conv_0_bias_to_fp16, dilations = tensor_4_dilations_0, groups = tensor_4_groups_0, pad = tensor_4_pad_0, pad_type = tensor_4_pad_type_0, strides = tensor_4_strides_0, weight = encoder_pre_encode_conv_0_weight_to_fp16_palettized, x = input_3_cast_fp16)[name = tensor("tensor_4_cast_fp16")]; tensor cast_0_to_fp16_dtype_0 = const()[name = tensor("cast_0_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_119_promoted_to_fp16 = const()[name = tensor("op_119_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor length_to_fp16 = cast(dtype = cast_0_to_fp16_dtype_0, x = length)[name = tensor("cast_280")]; tensor var_120_cast_fp16 = add(x = length_to_fp16, y = var_119_promoted_to_fp16)[name = tensor("op_120_cast_fp16")]; tensor var_121_promoted_to_fp16 = const()[name = tensor("op_121_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_122_cast_fp16 = add(x = var_120_cast_fp16, y = var_121_promoted_to_fp16)[name = tensor("op_122_cast_fp16")]; tensor var_123_promoted_to_fp16 = const()[name = tensor("op_123_promoted_to_fp16"), val = tensor(0x1.8p+1)]; tensor var_124_cast_fp16 = sub(x = var_122_cast_fp16, y = var_123_promoted_to_fp16)[name = tensor("op_124_cast_fp16")]; tensor var_19_promoted_to_fp16 = const()[name = tensor("op_19_promoted_to_fp16"), val = tensor(0x1p+1)]; tensor floor_div_0_cast_fp16 = floor_div(x = var_124_cast_fp16, y = var_19_promoted_to_fp16)[name = tensor("floor_div_0_cast_fp16")]; tensor var_126_promoted_to_fp16 = const()[name = tensor("op_126_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor current_lengths0_1_cast_fp16 = add(x = floor_div_0_cast_fp16, y = var_126_promoted_to_fp16)[name = tensor("current_lengths0_1_cast_fp16")]; tensor cast_6_dtype_0 = const()[name = tensor("cast_6_dtype_0"), val = tensor("int32")]; tensor var_129_shape_cast_fp16 = shape(x = tensor_4_cast_fp16)[name = tensor("op_129_shape_cast_fp16")]; tensor gather_7_axis_0 = const()[name = tensor("gather_7_axis_0"), val = tensor(0)]; tensor gather_7_batch_dims_0 = const()[name = tensor("gather_7_batch_dims_0"), val = tensor(0)]; tensor gather_7_validate_indices_0 = const()[name = tensor("gather_7_validate_indices_0"), val = tensor(false)]; tensor var_129_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_129_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_7_to_uint16 = const()[name = tensor("select_7_to_uint16"), val = tensor(0)]; tensor var_129_shape_cast_fp16_to_uint16 = cast(dtype = var_129_shape_cast_fp16_to_uint16_dtype_0, x = var_129_shape_cast_fp16)[name = tensor("cast_279")]; tensor gather_7_cast_uint16 = gather(axis = gather_7_axis_0, batch_dims = gather_7_batch_dims_0, indices = select_7_to_uint16, validate_indices = gather_7_validate_indices_0, x = var_129_shape_cast_fp16_to_uint16)[name = tensor("gather_7_cast_uint16")]; tensor gather_7_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_7_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_8_axis_0 = const()[name = tensor("gather_8_axis_0"), val = tensor(0)]; tensor gather_8_batch_dims_0 = const()[name = tensor("gather_8_batch_dims_0"), val = tensor(0)]; tensor gather_8_validate_indices_0 = const()[name = tensor("gather_8_validate_indices_0"), val = tensor(false)]; tensor select_8_to_uint16 = const()[name = tensor("select_8_to_uint16"), val = tensor(2)]; tensor gather_8_cast_uint16 = gather(axis = gather_8_axis_0, batch_dims = gather_8_batch_dims_0, indices = select_8_to_uint16, validate_indices = gather_8_validate_indices_0, x = var_129_shape_cast_fp16_to_uint16)[name = tensor("gather_8_cast_uint16")]; tensor gather_8_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_8_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_9 = const()[name = tensor("gather_9"), val = tensor(64)]; tensor const_2 = const()[name = tensor("const_2"), val = tensor(0)]; tensor const_3 = const()[name = tensor("const_3"), val = tensor(1)]; tensor gather_8_cast_uint16_to_int32 = cast(dtype = gather_8_cast_uint16_to_int32_dtype_0, x = gather_8_cast_uint16)[name = tensor("cast_278")]; tensor var_132 = range_1d(end = gather_8_cast_uint16_to_int32, start = const_2, step = const_3)[name = tensor("op_132")]; tensor expand_dims_1_axes_0 = const()[name = tensor("expand_dims_1_axes_0"), val = tensor([0])]; tensor expand_dims_1 = expand_dims(axes = expand_dims_1_axes_0, x = var_132)[name = tensor("expand_dims_1")]; tensor shape_13 = shape(x = expand_dims_1)[name = tensor("shape_13")]; tensor concat_3_axis_0 = const()[name = tensor("concat_3_axis_0"), val = tensor(0)]; tensor concat_3_interleave_0 = const()[name = tensor("concat_3_interleave_0"), val = tensor(false)]; tensor gather_7_cast_uint16_to_int32 = cast(dtype = gather_7_cast_uint16_to_int32_dtype_0, x = gather_7_cast_uint16)[name = tensor("cast_277")]; tensor concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (gather_7_cast_uint16_to_int32, gather_8_cast_uint16_to_int32))[name = tensor("concat_3")]; tensor real_div_3 = real_div(x = concat_3, y = shape_13)[name = tensor("real_div_3")]; tensor var_134 = tile(reps = real_div_3, x = expand_dims_1)[name = tensor("op_134")]; tensor var_135_axes_0 = const()[name = tensor("op_135_axes_0"), val = tensor([1])]; tensor current_lengths0_1_cast_fp16_to_int32 = cast(dtype = cast_6_dtype_0, x = current_lengths0_1_cast_fp16)[name = tensor("cast_276")]; tensor var_135 = expand_dims(axes = var_135_axes_0, x = current_lengths0_1_cast_fp16_to_int32)[name = tensor("op_135")]; tensor time_mask0_1 = less(x = var_134, y = var_135)[name = tensor("time_mask0_1")]; tensor var_137_axes_0 = const()[name = tensor("op_137_axes_0"), val = tensor([-1])]; tensor var_137 = expand_dims(axes = var_137_axes_0, x = time_mask0_1)[name = tensor("op_137")]; tensor shape_14 = shape(x = var_137)[name = tensor("shape_14")]; tensor concat_4_axis_0 = const()[name = tensor("concat_4_axis_0"), val = tensor(0)]; tensor concat_4_interleave_0 = const()[name = tensor("concat_4_interleave_0"), val = tensor(false)]; tensor concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (gather_7_cast_uint16_to_int32, gather_8_cast_uint16_to_int32, gather_9))[name = tensor("concat_4")]; tensor real_div_4 = real_div(x = concat_4, y = shape_14)[name = tensor("real_div_4")]; tensor var_139 = tile(reps = real_div_4, x = var_137)[name = tensor("op_139")]; tensor gather_11 = const()[name = tensor("gather_11"), val = tensor(256)]; tensor gather_13 = const()[name = tensor("gather_13"), val = tensor(64)]; tensor var_145_axes_0 = const()[name = tensor("op_145_axes_0"), val = tensor([1])]; tensor cast_9_to_fp16_dtype_0 = const()[name = tensor("cast_9_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_139_to_fp16 = cast(dtype = cast_9_to_fp16_dtype_0, x = var_139)[name = tensor("cast_275")]; tensor var_145_cast_fp16 = expand_dims(axes = var_145_axes_0, x = var_139_to_fp16)[name = tensor("op_145_cast_fp16")]; tensor shape_19_cast_fp16 = shape(x = var_145_cast_fp16)[name = tensor("shape_19_cast_fp16")]; tensor concat_5_axis_0 = const()[name = tensor("concat_5_axis_0"), val = tensor(0)]; tensor concat_5_interleave_0 = const()[name = tensor("concat_5_interleave_0"), val = tensor(false)]; tensor concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (gather_7_cast_uint16_to_int32, gather_11, gather_8_cast_uint16_to_int32, gather_13))[name = tensor("concat_5")]; tensor real_div_5 = real_div(x = concat_5, y = shape_19_cast_fp16)[name = tensor("real_div_5")]; tensor expanded_mask0_1_cast_fp16 = tile(reps = real_div_5, x = var_145_cast_fp16)[name = tensor("expanded_mask0_1_cast_fp16")]; tensor input0_3_cast_fp16 = mul(x = tensor_4_cast_fp16, y = expanded_mask0_1_cast_fp16)[name = tensor("input0_3_cast_fp16")]; tensor var_149_cast_fp16 = relu(x = input0_3_cast_fp16)[name = tensor("op_149_cast_fp16")]; tensor var_150_shape_cast_fp16 = shape(x = var_149_cast_fp16)[name = tensor("op_150_shape_cast_fp16")]; tensor gather_14_axis_0 = const()[name = tensor("gather_14_axis_0"), val = tensor(0)]; tensor gather_14_batch_dims_0 = const()[name = tensor("gather_14_batch_dims_0"), val = tensor(0)]; tensor gather_14_validate_indices_0 = const()[name = tensor("gather_14_validate_indices_0"), val = tensor(false)]; tensor var_150_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_150_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_14_to_uint16 = const()[name = tensor("select_14_to_uint16"), val = tensor(0)]; tensor var_150_shape_cast_fp16_to_uint16 = cast(dtype = var_150_shape_cast_fp16_to_uint16_dtype_0, x = var_150_shape_cast_fp16)[name = tensor("cast_274")]; tensor gather_14_cast_uint16 = gather(axis = gather_14_axis_0, batch_dims = gather_14_batch_dims_0, indices = select_14_to_uint16, validate_indices = gather_14_validate_indices_0, x = var_150_shape_cast_fp16_to_uint16)[name = tensor("gather_14_cast_uint16")]; tensor gather_14_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_14_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_15 = const()[name = tensor("gather_15"), val = tensor(256)]; tensor gather_16_axis_0 = const()[name = tensor("gather_16_axis_0"), val = tensor(0)]; tensor gather_16_batch_dims_0 = const()[name = tensor("gather_16_batch_dims_0"), val = tensor(0)]; tensor gather_16_validate_indices_0 = const()[name = tensor("gather_16_validate_indices_0"), val = tensor(false)]; tensor select_16_to_uint16 = const()[name = tensor("select_16_to_uint16"), val = tensor(2)]; tensor gather_16_cast_uint16 = gather(axis = gather_16_axis_0, batch_dims = gather_16_batch_dims_0, indices = select_16_to_uint16, validate_indices = gather_16_validate_indices_0, x = var_150_shape_cast_fp16_to_uint16)[name = tensor("gather_16_cast_uint16")]; tensor gather_16_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_16_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_17 = const()[name = tensor("gather_17"), val = tensor(64)]; tensor concat_6_axis_0 = const()[name = tensor("concat_6_axis_0"), val = tensor(0)]; tensor concat_6_interleave_0 = const()[name = tensor("concat_6_interleave_0"), val = tensor(false)]; tensor gather_14_cast_uint16_to_int32 = cast(dtype = gather_14_cast_uint16_to_int32_dtype_0, x = gather_14_cast_uint16)[name = tensor("cast_272")]; tensor gather_16_cast_uint16_to_int32 = cast(dtype = gather_16_cast_uint16_to_int32_dtype_0, x = gather_16_cast_uint16)[name = tensor("cast_273")]; tensor concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (gather_14_cast_uint16_to_int32, gather_15, gather_16_cast_uint16_to_int32, gather_17))[name = tensor("concat_6")]; tensor real_div_6 = real_div(x = concat_6, y = shape_19_cast_fp16)[name = tensor("real_div_6")]; tensor expanded_mask1_1_cast_fp16 = tile(reps = real_div_6, x = var_145_cast_fp16)[name = tensor("expanded_mask1_1_cast_fp16")]; tensor input1_4_cast_fp16 = mul(x = var_149_cast_fp16, y = expanded_mask1_1_cast_fp16)[name = tensor("input1_4_cast_fp16")]; tensor tensor_6_pad_type_0 = const()[name = tensor("tensor_6_pad_type_0"), val = tensor("custom")]; tensor tensor_6_pad_0 = const()[name = tensor("tensor_6_pad_0"), val = tensor([1, 1, 1, 1])]; tensor tensor_6_strides_0 = const()[name = tensor("tensor_6_strides_0"), val = tensor([2, 2])]; tensor tensor_6_groups_0 = const()[name = tensor("tensor_6_groups_0"), val = tensor(256)]; tensor tensor_6_dilations_0 = const()[name = tensor("tensor_6_dilations_0"), val = tensor([1, 1])]; tensor encoder_pre_encode_conv_2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3200))), name = tensor("encoder_pre_encode_conv_2_weight_to_fp16_palettized"), shape = tensor([256, 1, 3, 3])]; tensor encoder_pre_encode_conv_2_bias_to_fp16 = const()[name = tensor("encoder_pre_encode_conv_2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3328)))]; tensor tensor_6_cast_fp16 = conv(bias = encoder_pre_encode_conv_2_bias_to_fp16, dilations = tensor_6_dilations_0, groups = tensor_6_groups_0, pad = tensor_6_pad_0, pad_type = tensor_6_pad_type_0, strides = tensor_6_strides_0, weight = encoder_pre_encode_conv_2_weight_to_fp16_palettized, x = input1_4_cast_fp16)[name = tensor("tensor_6_cast_fp16")]; tensor var_165_promoted_to_fp16 = const()[name = tensor("op_165_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_166_cast_fp16 = add(x = current_lengths0_1_cast_fp16, y = var_165_promoted_to_fp16)[name = tensor("op_166_cast_fp16")]; tensor var_167_promoted_to_fp16 = const()[name = tensor("op_167_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_168_cast_fp16 = add(x = var_166_cast_fp16, y = var_167_promoted_to_fp16)[name = tensor("op_168_cast_fp16")]; tensor var_169_promoted_to_fp16 = const()[name = tensor("op_169_promoted_to_fp16"), val = tensor(0x1.8p+1)]; tensor var_170_cast_fp16 = sub(x = var_168_cast_fp16, y = var_169_promoted_to_fp16)[name = tensor("op_170_cast_fp16")]; tensor var_19_promoted_1_to_fp16 = const()[name = tensor("op_19_promoted_1_to_fp16"), val = tensor(0x1p+1)]; tensor floor_div_1_cast_fp16 = floor_div(x = var_170_cast_fp16, y = var_19_promoted_1_to_fp16)[name = tensor("floor_div_1_cast_fp16")]; tensor var_172_promoted_to_fp16 = const()[name = tensor("op_172_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor current_lengths1_1_cast_fp16 = add(x = floor_div_1_cast_fp16, y = var_172_promoted_to_fp16)[name = tensor("current_lengths1_1_cast_fp16")]; tensor cast_12_dtype_0 = const()[name = tensor("cast_12_dtype_0"), val = tensor("int32")]; tensor var_175_shape_cast_fp16 = shape(x = tensor_6_cast_fp16)[name = tensor("op_175_shape_cast_fp16")]; tensor gather_18_axis_0 = const()[name = tensor("gather_18_axis_0"), val = tensor(0)]; tensor gather_18_batch_dims_0 = const()[name = tensor("gather_18_batch_dims_0"), val = tensor(0)]; tensor gather_18_validate_indices_0 = const()[name = tensor("gather_18_validate_indices_0"), val = tensor(false)]; tensor var_175_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_175_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_18_to_uint16 = const()[name = tensor("select_18_to_uint16"), val = tensor(0)]; tensor var_175_shape_cast_fp16_to_uint16 = cast(dtype = var_175_shape_cast_fp16_to_uint16_dtype_0, x = var_175_shape_cast_fp16)[name = tensor("cast_271")]; tensor gather_18_cast_uint16 = gather(axis = gather_18_axis_0, batch_dims = gather_18_batch_dims_0, indices = select_18_to_uint16, validate_indices = gather_18_validate_indices_0, x = var_175_shape_cast_fp16_to_uint16)[name = tensor("gather_18_cast_uint16")]; tensor gather_18_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_18_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_19_axis_0 = const()[name = tensor("gather_19_axis_0"), val = tensor(0)]; tensor gather_19_batch_dims_0 = const()[name = tensor("gather_19_batch_dims_0"), val = tensor(0)]; tensor gather_19_validate_indices_0 = const()[name = tensor("gather_19_validate_indices_0"), val = tensor(false)]; tensor select_19_to_uint16 = const()[name = tensor("select_19_to_uint16"), val = tensor(2)]; tensor gather_19_cast_uint16 = gather(axis = gather_19_axis_0, batch_dims = gather_19_batch_dims_0, indices = select_19_to_uint16, validate_indices = gather_19_validate_indices_0, x = var_175_shape_cast_fp16_to_uint16)[name = tensor("gather_19_cast_uint16")]; tensor gather_19_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_19_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_20 = const()[name = tensor("gather_20"), val = tensor(32)]; tensor const_4 = const()[name = tensor("const_4"), val = tensor(0)]; tensor const_5 = const()[name = tensor("const_5"), val = tensor(1)]; tensor gather_19_cast_uint16_to_int32 = cast(dtype = gather_19_cast_uint16_to_int32_dtype_0, x = gather_19_cast_uint16)[name = tensor("cast_270")]; tensor var_178 = range_1d(end = gather_19_cast_uint16_to_int32, start = const_4, step = const_5)[name = tensor("op_178")]; tensor expand_dims_2_axes_0 = const()[name = tensor("expand_dims_2_axes_0"), val = tensor([0])]; tensor expand_dims_2 = expand_dims(axes = expand_dims_2_axes_0, x = var_178)[name = tensor("expand_dims_2")]; tensor shape_28 = shape(x = expand_dims_2)[name = tensor("shape_28")]; tensor concat_7_axis_0 = const()[name = tensor("concat_7_axis_0"), val = tensor(0)]; tensor concat_7_interleave_0 = const()[name = tensor("concat_7_interleave_0"), val = tensor(false)]; tensor gather_18_cast_uint16_to_int32 = cast(dtype = gather_18_cast_uint16_to_int32_dtype_0, x = gather_18_cast_uint16)[name = tensor("cast_269")]; tensor concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (gather_18_cast_uint16_to_int32, gather_19_cast_uint16_to_int32))[name = tensor("concat_7")]; tensor real_div_7 = real_div(x = concat_7, y = shape_28)[name = tensor("real_div_7")]; tensor var_180 = tile(reps = real_div_7, x = expand_dims_2)[name = tensor("op_180")]; tensor var_181_axes_0 = const()[name = tensor("op_181_axes_0"), val = tensor([1])]; tensor current_lengths1_1_cast_fp16_to_int32 = cast(dtype = cast_12_dtype_0, x = current_lengths1_1_cast_fp16)[name = tensor("cast_268")]; tensor var_181 = expand_dims(axes = var_181_axes_0, x = current_lengths1_1_cast_fp16_to_int32)[name = tensor("op_181")]; tensor time_mask1_1 = less(x = var_180, y = var_181)[name = tensor("time_mask1_1")]; tensor var_183_axes_0 = const()[name = tensor("op_183_axes_0"), val = tensor([-1])]; tensor var_183 = expand_dims(axes = var_183_axes_0, x = time_mask1_1)[name = tensor("op_183")]; tensor shape_29 = shape(x = var_183)[name = tensor("shape_29")]; tensor concat_8_axis_0 = const()[name = tensor("concat_8_axis_0"), val = tensor(0)]; tensor concat_8_interleave_0 = const()[name = tensor("concat_8_interleave_0"), val = tensor(false)]; tensor concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (gather_18_cast_uint16_to_int32, gather_19_cast_uint16_to_int32, gather_20))[name = tensor("concat_8")]; tensor real_div_8 = real_div(x = concat_8, y = shape_29)[name = tensor("real_div_8")]; tensor var_185 = tile(reps = real_div_8, x = var_183)[name = tensor("op_185")]; tensor gather_22 = const()[name = tensor("gather_22"), val = tensor(256)]; tensor gather_24 = const()[name = tensor("gather_24"), val = tensor(32)]; tensor var_191_axes_0 = const()[name = tensor("op_191_axes_0"), val = tensor([1])]; tensor cast_15_to_fp16_dtype_0 = const()[name = tensor("cast_15_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_185_to_fp16 = cast(dtype = cast_15_to_fp16_dtype_0, x = var_185)[name = tensor("cast_267")]; tensor var_191_cast_fp16 = expand_dims(axes = var_191_axes_0, x = var_185_to_fp16)[name = tensor("op_191_cast_fp16")]; tensor shape_34_cast_fp16 = shape(x = var_191_cast_fp16)[name = tensor("shape_34_cast_fp16")]; tensor concat_9_axis_0 = const()[name = tensor("concat_9_axis_0"), val = tensor(0)]; tensor concat_9_interleave_0 = const()[name = tensor("concat_9_interleave_0"), val = tensor(false)]; tensor concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (gather_18_cast_uint16_to_int32, gather_22, gather_19_cast_uint16_to_int32, gather_24))[name = tensor("concat_9")]; tensor real_div_9 = real_div(x = concat_9, y = shape_34_cast_fp16)[name = tensor("real_div_9")]; tensor expanded_mask2_1_cast_fp16 = tile(reps = real_div_9, x = var_191_cast_fp16)[name = tensor("expanded_mask2_1_cast_fp16")]; tensor input2_2_cast_fp16 = mul(x = tensor_6_cast_fp16, y = expanded_mask2_1_cast_fp16)[name = tensor("input2_2_cast_fp16")]; tensor tensor_8_pad_type_0 = const()[name = tensor("tensor_8_pad_type_0"), val = tensor("valid")]; tensor tensor_8_strides_0 = const()[name = tensor("tensor_8_strides_0"), val = tensor([1, 1])]; tensor tensor_8_pad_0 = const()[name = tensor("tensor_8_pad_0"), val = tensor([0, 0, 0, 0])]; tensor tensor_8_dilations_0 = const()[name = tensor("tensor_8_dilations_0"), val = tensor([1, 1])]; tensor tensor_8_groups_0 = const()[name = tensor("tensor_8_groups_0"), val = tensor(1)]; tensor encoder_pre_encode_conv_3_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36736))), name = tensor("encoder_pre_encode_conv_3_weight_to_fp16_palettized"), shape = tensor([256, 256, 1, 1])]; tensor encoder_pre_encode_conv_3_bias_to_fp16 = const()[name = tensor("encoder_pre_encode_conv_3_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36864)))]; tensor tensor_8_cast_fp16 = conv(bias = encoder_pre_encode_conv_3_bias_to_fp16, dilations = tensor_8_dilations_0, groups = tensor_8_groups_0, pad = tensor_8_pad_0, pad_type = tensor_8_pad_type_0, strides = tensor_8_strides_0, weight = encoder_pre_encode_conv_3_weight_to_fp16_palettized, x = input2_2_cast_fp16)[name = tensor("tensor_8_cast_fp16")]; tensor var_202_shape_cast_fp16 = shape(x = tensor_8_cast_fp16)[name = tensor("op_202_shape_cast_fp16")]; tensor gather_25_axis_0 = const()[name = tensor("gather_25_axis_0"), val = tensor(0)]; tensor gather_25_batch_dims_0 = const()[name = tensor("gather_25_batch_dims_0"), val = tensor(0)]; tensor gather_25_validate_indices_0 = const()[name = tensor("gather_25_validate_indices_0"), val = tensor(false)]; tensor var_202_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_202_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_25_to_uint16 = const()[name = tensor("select_25_to_uint16"), val = tensor(0)]; tensor var_202_shape_cast_fp16_to_uint16 = cast(dtype = var_202_shape_cast_fp16_to_uint16_dtype_0, x = var_202_shape_cast_fp16)[name = tensor("cast_266")]; tensor gather_25_cast_uint16 = gather(axis = gather_25_axis_0, batch_dims = gather_25_batch_dims_0, indices = select_25_to_uint16, validate_indices = gather_25_validate_indices_0, x = var_202_shape_cast_fp16_to_uint16)[name = tensor("gather_25_cast_uint16")]; tensor gather_25_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_25_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_26 = const()[name = tensor("gather_26"), val = tensor(256)]; tensor gather_27_axis_0 = const()[name = tensor("gather_27_axis_0"), val = tensor(0)]; tensor gather_27_batch_dims_0 = const()[name = tensor("gather_27_batch_dims_0"), val = tensor(0)]; tensor gather_27_validate_indices_0 = const()[name = tensor("gather_27_validate_indices_0"), val = tensor(false)]; tensor select_27_to_uint16 = const()[name = tensor("select_27_to_uint16"), val = tensor(2)]; tensor gather_27_cast_uint16 = gather(axis = gather_27_axis_0, batch_dims = gather_27_batch_dims_0, indices = select_27_to_uint16, validate_indices = gather_27_validate_indices_0, x = var_202_shape_cast_fp16_to_uint16)[name = tensor("gather_27_cast_uint16")]; tensor gather_27_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_27_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_28 = const()[name = tensor("gather_28"), val = tensor(32)]; tensor concat_10_axis_0 = const()[name = tensor("concat_10_axis_0"), val = tensor(0)]; tensor concat_10_interleave_0 = const()[name = tensor("concat_10_interleave_0"), val = tensor(false)]; tensor gather_25_cast_uint16_to_int32 = cast(dtype = gather_25_cast_uint16_to_int32_dtype_0, x = gather_25_cast_uint16)[name = tensor("cast_264")]; tensor gather_27_cast_uint16_to_int32 = cast(dtype = gather_27_cast_uint16_to_int32_dtype_0, x = gather_27_cast_uint16)[name = tensor("cast_265")]; tensor concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (gather_25_cast_uint16_to_int32, gather_26, gather_27_cast_uint16_to_int32, gather_28))[name = tensor("concat_10")]; tensor real_div_10 = real_div(x = concat_10, y = shape_34_cast_fp16)[name = tensor("real_div_10")]; tensor expanded_mask3_1_cast_fp16 = tile(reps = real_div_10, x = var_191_cast_fp16)[name = tensor("expanded_mask3_1_cast_fp16")]; tensor input3_2_cast_fp16 = mul(x = tensor_8_cast_fp16, y = expanded_mask3_1_cast_fp16)[name = tensor("input3_2_cast_fp16")]; tensor var_210_cast_fp16 = relu(x = input3_2_cast_fp16)[name = tensor("op_210_cast_fp16")]; tensor var_211_shape_cast_fp16 = shape(x = var_210_cast_fp16)[name = tensor("op_211_shape_cast_fp16")]; tensor gather_29_axis_0 = const()[name = tensor("gather_29_axis_0"), val = tensor(0)]; tensor gather_29_batch_dims_0 = const()[name = tensor("gather_29_batch_dims_0"), val = tensor(0)]; tensor gather_29_validate_indices_0 = const()[name = tensor("gather_29_validate_indices_0"), val = tensor(false)]; tensor var_211_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_211_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_29_to_uint16 = const()[name = tensor("select_29_to_uint16"), val = tensor(0)]; tensor var_211_shape_cast_fp16_to_uint16 = cast(dtype = var_211_shape_cast_fp16_to_uint16_dtype_0, x = var_211_shape_cast_fp16)[name = tensor("cast_263")]; tensor gather_29_cast_uint16 = gather(axis = gather_29_axis_0, batch_dims = gather_29_batch_dims_0, indices = select_29_to_uint16, validate_indices = gather_29_validate_indices_0, x = var_211_shape_cast_fp16_to_uint16)[name = tensor("gather_29_cast_uint16")]; tensor gather_29_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_29_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_30 = const()[name = tensor("gather_30"), val = tensor(256)]; tensor gather_31_axis_0 = const()[name = tensor("gather_31_axis_0"), val = tensor(0)]; tensor gather_31_batch_dims_0 = const()[name = tensor("gather_31_batch_dims_0"), val = tensor(0)]; tensor gather_31_validate_indices_0 = const()[name = tensor("gather_31_validate_indices_0"), val = tensor(false)]; tensor select_31_to_uint16 = const()[name = tensor("select_31_to_uint16"), val = tensor(2)]; tensor gather_31_cast_uint16 = gather(axis = gather_31_axis_0, batch_dims = gather_31_batch_dims_0, indices = select_31_to_uint16, validate_indices = gather_31_validate_indices_0, x = var_211_shape_cast_fp16_to_uint16)[name = tensor("gather_31_cast_uint16")]; tensor gather_31_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_31_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_32 = const()[name = tensor("gather_32"), val = tensor(32)]; tensor concat_11_axis_0 = const()[name = tensor("concat_11_axis_0"), val = tensor(0)]; tensor concat_11_interleave_0 = const()[name = tensor("concat_11_interleave_0"), val = tensor(false)]; tensor gather_29_cast_uint16_to_int32 = cast(dtype = gather_29_cast_uint16_to_int32_dtype_0, x = gather_29_cast_uint16)[name = tensor("cast_261")]; tensor gather_31_cast_uint16_to_int32 = cast(dtype = gather_31_cast_uint16_to_int32_dtype_0, x = gather_31_cast_uint16)[name = tensor("cast_262")]; tensor concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (gather_29_cast_uint16_to_int32, gather_30, gather_31_cast_uint16_to_int32, gather_32))[name = tensor("concat_11")]; tensor real_div_11 = real_div(x = concat_11, y = shape_34_cast_fp16)[name = tensor("real_div_11")]; tensor expanded_mask4_1_cast_fp16 = tile(reps = real_div_11, x = var_191_cast_fp16)[name = tensor("expanded_mask4_1_cast_fp16")]; tensor input4_1_cast_fp16 = mul(x = var_210_cast_fp16, y = expanded_mask4_1_cast_fp16)[name = tensor("input4_1_cast_fp16")]; tensor tensor_10_pad_type_0 = const()[name = tensor("tensor_10_pad_type_0"), val = tensor("custom")]; tensor tensor_10_pad_0 = const()[name = tensor("tensor_10_pad_0"), val = tensor([1, 1, 1, 1])]; tensor tensor_10_strides_0 = const()[name = tensor("tensor_10_strides_0"), val = tensor([2, 2])]; tensor tensor_10_groups_0 = const()[name = tensor("tensor_10_groups_0"), val = tensor(256)]; tensor tensor_10_dilations_0 = const()[name = tensor("tensor_10_dilations_0"), val = tensor([1, 1])]; tensor encoder_pre_encode_conv_5_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38656))), name = tensor("encoder_pre_encode_conv_5_weight_to_fp16_palettized"), shape = tensor([256, 1, 3, 3])]; tensor encoder_pre_encode_conv_5_bias_to_fp16 = const()[name = tensor("encoder_pre_encode_conv_5_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38784)))]; tensor tensor_10_cast_fp16 = conv(bias = encoder_pre_encode_conv_5_bias_to_fp16, dilations = tensor_10_dilations_0, groups = tensor_10_groups_0, pad = tensor_10_pad_0, pad_type = tensor_10_pad_type_0, strides = tensor_10_strides_0, weight = encoder_pre_encode_conv_5_weight_to_fp16_palettized, x = input4_1_cast_fp16)[name = tensor("tensor_10_cast_fp16")]; tensor var_226_promoted_to_fp16 = const()[name = tensor("op_226_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_227_cast_fp16 = add(x = current_lengths1_1_cast_fp16, y = var_226_promoted_to_fp16)[name = tensor("op_227_cast_fp16")]; tensor var_228_promoted_to_fp16 = const()[name = tensor("op_228_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_229_cast_fp16 = add(x = var_227_cast_fp16, y = var_228_promoted_to_fp16)[name = tensor("op_229_cast_fp16")]; tensor var_230_promoted_to_fp16 = const()[name = tensor("op_230_promoted_to_fp16"), val = tensor(0x1.8p+1)]; tensor var_231_cast_fp16 = sub(x = var_229_cast_fp16, y = var_230_promoted_to_fp16)[name = tensor("op_231_cast_fp16")]; tensor var_19_promoted_2_to_fp16 = const()[name = tensor("op_19_promoted_2_to_fp16"), val = tensor(0x1p+1)]; tensor floor_div_2_cast_fp16 = floor_div(x = var_231_cast_fp16, y = var_19_promoted_2_to_fp16)[name = tensor("floor_div_2_cast_fp16")]; tensor var_233_promoted_to_fp16 = const()[name = tensor("op_233_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor current_lengths2_1_cast_fp16 = add(x = floor_div_2_cast_fp16, y = var_233_promoted_to_fp16)[name = tensor("current_lengths2_1_cast_fp16")]; tensor cast_19_dtype_0 = const()[name = tensor("cast_19_dtype_0"), val = tensor("int32")]; tensor var_236_shape_cast_fp16 = shape(x = tensor_10_cast_fp16)[name = tensor("op_236_shape_cast_fp16")]; tensor gather_33_axis_0 = const()[name = tensor("gather_33_axis_0"), val = tensor(0)]; tensor gather_33_batch_dims_0 = const()[name = tensor("gather_33_batch_dims_0"), val = tensor(0)]; tensor gather_33_validate_indices_0 = const()[name = tensor("gather_33_validate_indices_0"), val = tensor(false)]; tensor var_236_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_236_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_33_to_uint16 = const()[name = tensor("select_33_to_uint16"), val = tensor(0)]; tensor var_236_shape_cast_fp16_to_uint16 = cast(dtype = var_236_shape_cast_fp16_to_uint16_dtype_0, x = var_236_shape_cast_fp16)[name = tensor("cast_260")]; tensor gather_33_cast_uint16 = gather(axis = gather_33_axis_0, batch_dims = gather_33_batch_dims_0, indices = select_33_to_uint16, validate_indices = gather_33_validate_indices_0, x = var_236_shape_cast_fp16_to_uint16)[name = tensor("gather_33_cast_uint16")]; tensor gather_33_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_33_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_34_axis_0 = const()[name = tensor("gather_34_axis_0"), val = tensor(0)]; tensor gather_34_batch_dims_0 = const()[name = tensor("gather_34_batch_dims_0"), val = tensor(0)]; tensor gather_34_validate_indices_0 = const()[name = tensor("gather_34_validate_indices_0"), val = tensor(false)]; tensor select_34_to_uint16 = const()[name = tensor("select_34_to_uint16"), val = tensor(2)]; tensor gather_34_cast_uint16 = gather(axis = gather_34_axis_0, batch_dims = gather_34_batch_dims_0, indices = select_34_to_uint16, validate_indices = gather_34_validate_indices_0, x = var_236_shape_cast_fp16_to_uint16)[name = tensor("gather_34_cast_uint16")]; tensor gather_34_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_34_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_35 = const()[name = tensor("gather_35"), val = tensor(16)]; tensor const_6 = const()[name = tensor("const_6"), val = tensor(0)]; tensor const_7 = const()[name = tensor("const_7"), val = tensor(1)]; tensor gather_34_cast_uint16_to_int32 = cast(dtype = gather_34_cast_uint16_to_int32_dtype_0, x = gather_34_cast_uint16)[name = tensor("cast_259")]; tensor var_239 = range_1d(end = gather_34_cast_uint16_to_int32, start = const_6, step = const_7)[name = tensor("op_239")]; tensor expand_dims_3_axes_0 = const()[name = tensor("expand_dims_3_axes_0"), val = tensor([0])]; tensor expand_dims_3 = expand_dims(axes = expand_dims_3_axes_0, x = var_239)[name = tensor("expand_dims_3")]; tensor shape_48 = shape(x = expand_dims_3)[name = tensor("shape_48")]; tensor concat_12_axis_0 = const()[name = tensor("concat_12_axis_0"), val = tensor(0)]; tensor concat_12_interleave_0 = const()[name = tensor("concat_12_interleave_0"), val = tensor(false)]; tensor gather_33_cast_uint16_to_int32 = cast(dtype = gather_33_cast_uint16_to_int32_dtype_0, x = gather_33_cast_uint16)[name = tensor("cast_258")]; tensor concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (gather_33_cast_uint16_to_int32, gather_34_cast_uint16_to_int32))[name = tensor("concat_12")]; tensor real_div_12 = real_div(x = concat_12, y = shape_48)[name = tensor("real_div_12")]; tensor var_241 = tile(reps = real_div_12, x = expand_dims_3)[name = tensor("op_241")]; tensor var_242_axes_0 = const()[name = tensor("op_242_axes_0"), val = tensor([1])]; tensor current_lengths2_1_cast_fp16_to_int32 = cast(dtype = cast_19_dtype_0, x = current_lengths2_1_cast_fp16)[name = tensor("cast_257")]; tensor var_242 = expand_dims(axes = var_242_axes_0, x = current_lengths2_1_cast_fp16_to_int32)[name = tensor("op_242")]; tensor time_mask2_1 = less(x = var_241, y = var_242)[name = tensor("time_mask2_1")]; tensor var_244_axes_0 = const()[name = tensor("op_244_axes_0"), val = tensor([-1])]; tensor var_244 = expand_dims(axes = var_244_axes_0, x = time_mask2_1)[name = tensor("op_244")]; tensor shape_49 = shape(x = var_244)[name = tensor("shape_49")]; tensor concat_13_axis_0 = const()[name = tensor("concat_13_axis_0"), val = tensor(0)]; tensor concat_13_interleave_0 = const()[name = tensor("concat_13_interleave_0"), val = tensor(false)]; tensor concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (gather_33_cast_uint16_to_int32, gather_34_cast_uint16_to_int32, gather_35))[name = tensor("concat_13")]; tensor real_div_13 = real_div(x = concat_13, y = shape_49)[name = tensor("real_div_13")]; tensor var_246 = tile(reps = real_div_13, x = var_244)[name = tensor("op_246")]; tensor gather_37 = const()[name = tensor("gather_37"), val = tensor(256)]; tensor gather_39 = const()[name = tensor("gather_39"), val = tensor(16)]; tensor var_252_axes_0 = const()[name = tensor("op_252_axes_0"), val = tensor([1])]; tensor cast_22_to_fp16_dtype_0 = const()[name = tensor("cast_22_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_246_to_fp16 = cast(dtype = cast_22_to_fp16_dtype_0, x = var_246)[name = tensor("cast_256")]; tensor var_252_cast_fp16 = expand_dims(axes = var_252_axes_0, x = var_246_to_fp16)[name = tensor("op_252_cast_fp16")]; tensor shape_54_cast_fp16 = shape(x = var_252_cast_fp16)[name = tensor("shape_54_cast_fp16")]; tensor concat_14_axis_0 = const()[name = tensor("concat_14_axis_0"), val = tensor(0)]; tensor concat_14_interleave_0 = const()[name = tensor("concat_14_interleave_0"), val = tensor(false)]; tensor concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (gather_33_cast_uint16_to_int32, gather_37, gather_34_cast_uint16_to_int32, gather_39))[name = tensor("concat_14")]; tensor real_div_14 = real_div(x = concat_14, y = shape_54_cast_fp16)[name = tensor("real_div_14")]; tensor expanded_mask5_1_cast_fp16 = tile(reps = real_div_14, x = var_252_cast_fp16)[name = tensor("expanded_mask5_1_cast_fp16")]; tensor input5_1_cast_fp16 = mul(x = tensor_10_cast_fp16, y = expanded_mask5_1_cast_fp16)[name = tensor("input5_1_cast_fp16")]; tensor tensor_1_pad_type_0 = const()[name = tensor("tensor_1_pad_type_0"), val = tensor("valid")]; tensor tensor_1_strides_0 = const()[name = tensor("tensor_1_strides_0"), val = tensor([1, 1])]; tensor tensor_1_pad_0 = const()[name = tensor("tensor_1_pad_0"), val = tensor([0, 0, 0, 0])]; tensor tensor_1_dilations_0 = const()[name = tensor("tensor_1_dilations_0"), val = tensor([1, 1])]; tensor tensor_1_groups_0 = const()[name = tensor("tensor_1_groups_0"), val = tensor(1)]; tensor encoder_pre_encode_conv_6_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72192))), name = tensor("encoder_pre_encode_conv_6_weight_to_fp16_palettized"), shape = tensor([256, 256, 1, 1])]; tensor encoder_pre_encode_conv_6_bias_to_fp16 = const()[name = tensor("encoder_pre_encode_conv_6_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72320)))]; tensor tensor_1_cast_fp16 = conv(bias = encoder_pre_encode_conv_6_bias_to_fp16, dilations = tensor_1_dilations_0, groups = tensor_1_groups_0, pad = tensor_1_pad_0, pad_type = tensor_1_pad_type_0, strides = tensor_1_strides_0, weight = encoder_pre_encode_conv_6_weight_to_fp16_palettized, x = input5_1_cast_fp16)[name = tensor("tensor_1_cast_fp16")]; tensor var_263_shape_cast_fp16 = shape(x = tensor_1_cast_fp16)[name = tensor("op_263_shape_cast_fp16")]; tensor gather_40_axis_0 = const()[name = tensor("gather_40_axis_0"), val = tensor(0)]; tensor gather_40_batch_dims_0 = const()[name = tensor("gather_40_batch_dims_0"), val = tensor(0)]; tensor gather_40_validate_indices_0 = const()[name = tensor("gather_40_validate_indices_0"), val = tensor(false)]; tensor var_263_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_263_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_40_to_uint16 = const()[name = tensor("select_40_to_uint16"), val = tensor(0)]; tensor var_263_shape_cast_fp16_to_uint16 = cast(dtype = var_263_shape_cast_fp16_to_uint16_dtype_0, x = var_263_shape_cast_fp16)[name = tensor("cast_255")]; tensor gather_40_cast_uint16 = gather(axis = gather_40_axis_0, batch_dims = gather_40_batch_dims_0, indices = select_40_to_uint16, validate_indices = gather_40_validate_indices_0, x = var_263_shape_cast_fp16_to_uint16)[name = tensor("gather_40_cast_uint16")]; tensor gather_40_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_40_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_41 = const()[name = tensor("gather_41"), val = tensor(256)]; tensor gather_42_axis_0 = const()[name = tensor("gather_42_axis_0"), val = tensor(0)]; tensor gather_42_batch_dims_0 = const()[name = tensor("gather_42_batch_dims_0"), val = tensor(0)]; tensor gather_42_validate_indices_0 = const()[name = tensor("gather_42_validate_indices_0"), val = tensor(false)]; tensor select_42_to_uint16 = const()[name = tensor("select_42_to_uint16"), val = tensor(2)]; tensor gather_42_cast_uint16 = gather(axis = gather_42_axis_0, batch_dims = gather_42_batch_dims_0, indices = select_42_to_uint16, validate_indices = gather_42_validate_indices_0, x = var_263_shape_cast_fp16_to_uint16)[name = tensor("gather_42_cast_uint16")]; tensor gather_42_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_42_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_43 = const()[name = tensor("gather_43"), val = tensor(16)]; tensor concat_15_axis_0 = const()[name = tensor("concat_15_axis_0"), val = tensor(0)]; tensor concat_15_interleave_0 = const()[name = tensor("concat_15_interleave_0"), val = tensor(false)]; tensor gather_40_cast_uint16_to_int32 = cast(dtype = gather_40_cast_uint16_to_int32_dtype_0, x = gather_40_cast_uint16)[name = tensor("cast_253")]; tensor gather_42_cast_uint16_to_int32 = cast(dtype = gather_42_cast_uint16_to_int32_dtype_0, x = gather_42_cast_uint16)[name = tensor("cast_254")]; tensor concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (gather_40_cast_uint16_to_int32, gather_41, gather_42_cast_uint16_to_int32, gather_43))[name = tensor("concat_15")]; tensor real_div_15 = real_div(x = concat_15, y = shape_54_cast_fp16)[name = tensor("real_div_15")]; tensor expanded_mask6_1_cast_fp16 = tile(reps = real_div_15, x = var_252_cast_fp16)[name = tensor("expanded_mask6_1_cast_fp16")]; tensor input6_1_cast_fp16 = mul(x = tensor_1_cast_fp16, y = expanded_mask6_1_cast_fp16)[name = tensor("input6_1_cast_fp16")]; tensor var_271_cast_fp16 = relu(x = input6_1_cast_fp16)[name = tensor("op_271_cast_fp16")]; tensor var_272_shape_cast_fp16 = shape(x = var_271_cast_fp16)[name = tensor("op_272_shape_cast_fp16")]; tensor gather_44_axis_0 = const()[name = tensor("gather_44_axis_0"), val = tensor(0)]; tensor gather_44_batch_dims_0 = const()[name = tensor("gather_44_batch_dims_0"), val = tensor(0)]; tensor gather_44_validate_indices_0 = const()[name = tensor("gather_44_validate_indices_0"), val = tensor(false)]; tensor var_272_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_272_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_44_to_uint16 = const()[name = tensor("select_44_to_uint16"), val = tensor(0)]; tensor var_272_shape_cast_fp16_to_uint16 = cast(dtype = var_272_shape_cast_fp16_to_uint16_dtype_0, x = var_272_shape_cast_fp16)[name = tensor("cast_252")]; tensor gather_44_cast_uint16 = gather(axis = gather_44_axis_0, batch_dims = gather_44_batch_dims_0, indices = select_44_to_uint16, validate_indices = gather_44_validate_indices_0, x = var_272_shape_cast_fp16_to_uint16)[name = tensor("gather_44_cast_uint16")]; tensor gather_44_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_44_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_45 = const()[name = tensor("gather_45"), val = tensor(256)]; tensor gather_46_axis_0 = const()[name = tensor("gather_46_axis_0"), val = tensor(0)]; tensor gather_46_batch_dims_0 = const()[name = tensor("gather_46_batch_dims_0"), val = tensor(0)]; tensor gather_46_validate_indices_0 = const()[name = tensor("gather_46_validate_indices_0"), val = tensor(false)]; tensor select_46_to_uint16 = const()[name = tensor("select_46_to_uint16"), val = tensor(2)]; tensor gather_46_cast_uint16 = gather(axis = gather_46_axis_0, batch_dims = gather_46_batch_dims_0, indices = select_46_to_uint16, validate_indices = gather_46_validate_indices_0, x = var_272_shape_cast_fp16_to_uint16)[name = tensor("gather_46_cast_uint16")]; tensor gather_46_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_46_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_47 = const()[name = tensor("gather_47"), val = tensor(16)]; tensor concat_16_axis_0 = const()[name = tensor("concat_16_axis_0"), val = tensor(0)]; tensor concat_16_interleave_0 = const()[name = tensor("concat_16_interleave_0"), val = tensor(false)]; tensor gather_44_cast_uint16_to_int32 = cast(dtype = gather_44_cast_uint16_to_int32_dtype_0, x = gather_44_cast_uint16)[name = tensor("cast_250")]; tensor gather_46_cast_uint16_to_int32 = cast(dtype = gather_46_cast_uint16_to_int32_dtype_0, x = gather_46_cast_uint16)[name = tensor("cast_251")]; tensor concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (gather_44_cast_uint16_to_int32, gather_45, gather_46_cast_uint16_to_int32, gather_47))[name = tensor("concat_16")]; tensor real_div_16 = real_div(x = concat_16, y = shape_54_cast_fp16)[name = tensor("real_div_16")]; tensor expanded_mask7_1_cast_fp16 = tile(reps = real_div_16, x = var_252_cast_fp16)[name = tensor("expanded_mask7_1_cast_fp16")]; tensor x0_2_cast_fp16 = mul(x = var_271_cast_fp16, y = expanded_mask7_1_cast_fp16)[name = tensor("x0_2_cast_fp16")]; tensor var_284_shape_cast_fp16 = shape(x = x0_2_cast_fp16)[name = tensor("op_284_shape_cast_fp16")]; tensor gather_48_axis_0 = const()[name = tensor("gather_48_axis_0"), val = tensor(0)]; tensor gather_48_batch_dims_0 = const()[name = tensor("gather_48_batch_dims_0"), val = tensor(0)]; tensor gather_48_validate_indices_0 = const()[name = tensor("gather_48_validate_indices_0"), val = tensor(false)]; tensor var_284_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_284_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_48_to_uint16 = const()[name = tensor("select_48_to_uint16"), val = tensor(0)]; tensor var_284_shape_cast_fp16_to_uint16 = cast(dtype = var_284_shape_cast_fp16_to_uint16_dtype_0, x = var_284_shape_cast_fp16)[name = tensor("cast_249")]; tensor gather_48_cast_uint16 = gather(axis = gather_48_axis_0, batch_dims = gather_48_batch_dims_0, indices = select_48_to_uint16, validate_indices = gather_48_validate_indices_0, x = var_284_shape_cast_fp16_to_uint16)[name = tensor("gather_48_cast_uint16")]; tensor gather_48_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_48_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_49_axis_0 = const()[name = tensor("gather_49_axis_0"), val = tensor(0)]; tensor gather_49_batch_dims_0 = const()[name = tensor("gather_49_batch_dims_0"), val = tensor(0)]; tensor gather_49_validate_indices_0 = const()[name = tensor("gather_49_validate_indices_0"), val = tensor(false)]; tensor select_49_to_uint16 = const()[name = tensor("select_49_to_uint16"), val = tensor(2)]; tensor gather_49_cast_uint16 = gather(axis = gather_49_axis_0, batch_dims = gather_49_batch_dims_0, indices = select_49_to_uint16, validate_indices = gather_49_validate_indices_0, x = var_284_shape_cast_fp16_to_uint16)[name = tensor("gather_49_cast_uint16")]; tensor gather_49_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_49_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor var_286_perm_0 = const()[name = tensor("op_286_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_17_axis_0 = const()[name = tensor("concat_17_axis_0"), val = tensor(0)]; tensor concat_17_interleave_0 = const()[name = tensor("concat_17_interleave_0"), val = tensor(false)]; tensor gather_48_cast_uint16_to_int32 = cast(dtype = gather_48_cast_uint16_to_int32_dtype_0, x = gather_48_cast_uint16)[name = tensor("cast_247")]; tensor gather_49_cast_uint16_to_int32 = cast(dtype = gather_49_cast_uint16_to_int32_dtype_0, x = gather_49_cast_uint16)[name = tensor("cast_248")]; tensor concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (gather_48_cast_uint16_to_int32, gather_49_cast_uint16_to_int32, var_21))[name = tensor("concat_17")]; tensor var_286_cast_fp16 = transpose(perm = var_286_perm_0, x = x0_2_cast_fp16)[name = tensor("transpose_481")]; tensor input_5_cast_fp16 = reshape(shape = concat_17, x = var_286_cast_fp16)[name = tensor("input_5_cast_fp16")]; tensor encoder_pre_encode_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2170112))), name = tensor("encoder_pre_encode_out_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor encoder_pre_encode_out_bias_to_fp16 = const()[name = tensor("encoder_pre_encode_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2170240)))]; tensor linear_0_cast_fp16 = linear(bias = encoder_pre_encode_out_bias_to_fp16, weight = encoder_pre_encode_out_weight_to_fp16_palettized, x = input_5_cast_fp16)[name = tensor("linear_0_cast_fp16")]; tensor cast_28_dtype_0 = const()[name = tensor("cast_28_dtype_0"), val = tensor("int32")]; tensor var_296_shape_cast_fp16 = shape(x = linear_0_cast_fp16)[name = tensor("op_296_shape_cast_fp16")]; tensor gather_50_axis_0 = const()[name = tensor("gather_50_axis_0"), val = tensor(0)]; tensor gather_50_batch_dims_0 = const()[name = tensor("gather_50_batch_dims_0"), val = tensor(0)]; tensor gather_50_validate_indices_0 = const()[name = tensor("gather_50_validate_indices_0"), val = tensor(false)]; tensor var_296_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_296_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_50_to_uint16 = const()[name = tensor("select_50_to_uint16"), val = tensor(1)]; tensor var_296_shape_cast_fp16_to_uint16 = cast(dtype = var_296_shape_cast_fp16_to_uint16_dtype_0, x = var_296_shape_cast_fp16)[name = tensor("cast_246")]; tensor gather_50_cast_uint16 = gather(axis = gather_50_axis_0, batch_dims = gather_50_batch_dims_0, indices = select_50_to_uint16, validate_indices = gather_50_validate_indices_0, x = var_296_shape_cast_fp16_to_uint16)[name = tensor("gather_50_cast_uint16")]; tensor gather_50_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_50_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor center_pos_1_to_fp16 = const()[name = tensor("center_pos_1_to_fp16"), val = tensor([0x1.388p+12])]; tensor input_len_1_promoted_to_fp16_dtype_0 = const()[name = tensor("input_len_1_promoted_to_fp16_dtype_0"), val = tensor("fp16")]; tensor gather_50_cast_uint16_to_fp16 = cast(dtype = input_len_1_promoted_to_fp16_dtype_0, x = gather_50_cast_uint16)[name = tensor("cast_245")]; tensor start_pos_1_cast_fp16 = sub(x = center_pos_1_to_fp16, y = gather_50_cast_uint16_to_fp16)[name = tensor("start_pos_1_cast_fp16")]; tensor var_308_item_cast_fp16 = squeeze(x = start_pos_1_cast_fp16)[name = tensor("op_308_item_cast_fp16")]; tensor var_308_dtype_0 = const()[name = tensor("op_308_dtype_0"), val = tensor("int32")]; tensor var_309_cast_fp16 = add(x = center_pos_1_to_fp16, y = gather_50_cast_uint16_to_fp16)[name = tensor("op_309_cast_fp16")]; tensor var_310_promoted_to_fp16 = const()[name = tensor("op_310_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor end_pos_1_cast_fp16 = sub(x = var_309_cast_fp16, y = var_310_promoted_to_fp16)[name = tensor("end_pos_1_cast_fp16")]; tensor var_312_item_cast_fp16 = squeeze(x = end_pos_1_cast_fp16)[name = tensor("op_312_item_cast_fp16")]; tensor var_312_dtype_0 = const()[name = tensor("op_312_dtype_0"), val = tensor("int32")]; tensor concat_18_values0_0 = const()[name = tensor("concat_18_values0_0"), val = tensor(0)]; tensor concat_18_values2_0 = const()[name = tensor("concat_18_values2_0"), val = tensor(0)]; tensor concat_18_axis_0 = const()[name = tensor("concat_18_axis_0"), val = tensor(0)]; tensor concat_18_interleave_0 = const()[name = tensor("concat_18_interleave_0"), val = tensor(false)]; tensor var_308_item_cast_fp16_to_int32 = cast(dtype = var_308_dtype_0, x = var_308_item_cast_fp16)[name = tensor("cast_244")]; tensor concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (concat_18_values0_0, var_308_item_cast_fp16_to_int32, concat_18_values2_0))[name = tensor("concat_18")]; tensor concat_19_values0_0 = const()[name = tensor("concat_19_values0_0"), val = tensor(1)]; tensor concat_19_values2_0 = const()[name = tensor("concat_19_values2_0"), val = tensor(1024)]; tensor concat_19_axis_0 = const()[name = tensor("concat_19_axis_0"), val = tensor(0)]; tensor concat_19_interleave_0 = const()[name = tensor("concat_19_interleave_0"), val = tensor(false)]; tensor var_312_item_cast_fp16_to_int32 = cast(dtype = var_312_dtype_0, x = var_312_item_cast_fp16)[name = tensor("cast_243")]; tensor concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (concat_19_values0_0, var_312_item_cast_fp16_to_int32, concat_19_values2_0))[name = tensor("concat_19")]; tensor pos_emb_1_end_mask_0 = const()[name = tensor("pos_emb_1_end_mask_0"), val = tensor([true, false, true])]; tensor encoder_pos_enc_pe_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2172352))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7291904))), name = tensor("encoder_pos_enc_pe_to_fp16_palettized"), shape = tensor([1, 9999, 1024])]; tensor pos_emb_1_cast_fp16 = slice_by_index(begin = concat_18, end = concat_19, end_mask = pos_emb_1_end_mask_0, x = encoder_pos_enc_pe_to_fp16_palettized)[name = tensor("pos_emb_1_cast_fp16")]; tensor concat_20_axis_0 = const()[name = tensor("concat_20_axis_0"), val = tensor(0)]; tensor concat_20_interleave_0 = const()[name = tensor("concat_20_interleave_0"), val = tensor(false)]; tensor gather_50_cast_uint16_to_int32 = cast(dtype = gather_50_cast_uint16_to_int32_dtype_0, x = gather_50_cast_uint16)[name = tensor("cast_242")]; tensor concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (var_26, gather_50_cast_uint16_to_int32, gather_50_cast_uint16_to_int32))[name = tensor("concat_20")]; tensor fill_0_value_0_to_fp16 = const()[name = tensor("fill_0_value_0_to_fp16"), val = tensor(0x1p+0)]; tensor fill_0_cast_fp16 = fill(shape = concat_20, value = fill_0_value_0_to_fp16)[name = tensor("fill_0_cast_fp16")]; tensor cast_29_dtype_0 = const()[name = tensor("cast_29_dtype_0"), val = tensor("bool")]; tensor const_9 = const()[name = tensor("const_9"), val = tensor(1)]; tensor var_321 = range_1d(end = gather_50_cast_uint16_to_int32, start = var_22, step = const_9)[name = tensor("op_321")]; tensor expand_dims_4_axes_0 = const()[name = tensor("expand_dims_4_axes_0"), val = tensor([0])]; tensor expand_dims_4 = expand_dims(axes = expand_dims_4_axes_0, x = var_321)[name = tensor("expand_dims_4")]; tensor var_325_axes_0 = const()[name = tensor("op_325_axes_0"), val = tensor([-1])]; tensor encoded_length = cast(dtype = cast_28_dtype_0, x = current_lengths2_1_cast_fp16)[name = tensor("cast_241")]; tensor var_325 = expand_dims(axes = var_325_axes_0, x = encoded_length)[name = tensor("op_325")]; tensor pad_mask_1 = less(x = expand_dims_4, y = var_325)[name = tensor("pad_mask_1")]; tensor var_327_axes_0 = const()[name = tensor("op_327_axes_0"), val = tensor([1])]; tensor var_327 = expand_dims(axes = var_327_axes_0, x = pad_mask_1)[name = tensor("op_327")]; tensor concat_21_axis_0 = const()[name = tensor("concat_21_axis_0"), val = tensor(0)]; tensor concat_21_interleave_0 = const()[name = tensor("concat_21_interleave_0"), val = tensor(false)]; tensor concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (var_26, gather_50_cast_uint16_to_int32, var_26))[name = tensor("concat_21")]; tensor pad_mask_for_att_mask_1 = tile(reps = concat_21, x = var_327)[name = tensor("pad_mask_for_att_mask_1")]; tensor var_330_perm_0 = const()[name = tensor("op_330_perm_0"), val = tensor([0, 2, 1])]; tensor var_330 = transpose(perm = var_330_perm_0, x = pad_mask_for_att_mask_1)[name = tensor("transpose_480")]; tensor pad_mask_for_att_mask0_1 = logical_and(x = pad_mask_for_att_mask_1, y = var_330)[name = tensor("pad_mask_for_att_mask0_1")]; tensor concat_22_values0_0 = const()[name = tensor("concat_22_values0_0"), val = tensor(1)]; tensor concat_22_values2_0 = const()[name = tensor("concat_22_values2_0"), val = tensor(0)]; tensor concat_22_axis_0 = const()[name = tensor("concat_22_axis_0"), val = tensor(0)]; tensor concat_22_interleave_0 = const()[name = tensor("concat_22_interleave_0"), val = tensor(false)]; tensor concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (concat_22_values0_0, gather_50_cast_uint16_to_int32, concat_22_values2_0))[name = tensor("concat_22")]; tensor var_333_begin_0 = const()[name = tensor("op_333_begin_0"), val = tensor([0, 0, 0])]; tensor var_333_end_mask_0 = const()[name = tensor("op_333_end_mask_0"), val = tensor([true, false, true])]; tensor fill_0_cast_fp16_to_bool = cast(dtype = cast_29_dtype_0, x = fill_0_cast_fp16)[name = tensor("cast_240")]; tensor var_333 = slice_by_index(begin = var_333_begin_0, end = concat_22, end_mask = var_333_end_mask_0, x = fill_0_cast_fp16_to_bool)[name = tensor("op_333")]; tensor concat_23_values0_0 = const()[name = tensor("concat_23_values0_0"), val = tensor(1)]; tensor concat_23_values1_0 = const()[name = tensor("concat_23_values1_0"), val = tensor(0)]; tensor concat_23_axis_0 = const()[name = tensor("concat_23_axis_0"), val = tensor(0)]; tensor concat_23_interleave_0 = const()[name = tensor("concat_23_interleave_0"), val = tensor(false)]; tensor concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (concat_23_values0_0, concat_23_values1_0, gather_50_cast_uint16_to_int32))[name = tensor("concat_23")]; tensor att_mask0_1_begin_0 = const()[name = tensor("att_mask0_1_begin_0"), val = tensor([0, 0, 0])]; tensor att_mask0_1_end_mask_0 = const()[name = tensor("att_mask0_1_end_mask_0"), val = tensor([true, true, false])]; tensor att_mask0_1 = slice_by_index(begin = att_mask0_1_begin_0, end = concat_23, end_mask = att_mask0_1_end_mask_0, x = var_333)[name = tensor("att_mask0_1")]; tensor att_mask2_1 = logical_and(x = pad_mask_for_att_mask0_1, y = att_mask0_1)[name = tensor("att_mask2_1")]; tensor mask_2 = logical_not(x = att_mask2_1)[name = tensor("mask_2")]; tensor pad_mask0_1 = logical_not(x = pad_mask_1)[name = tensor("pad_mask0_1")]; tensor input_9_axes_0 = const()[name = tensor("input_9_axes_0"), val = tensor([-1])]; tensor encoder_layers_0_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_0_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7292032)))]; tensor encoder_layers_0_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_0_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7294144)))]; tensor var_7_to_fp16 = const()[name = tensor("op_7_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_9_cast_fp16 = layer_norm(axes = input_9_axes_0, beta = encoder_layers_0_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_0_norm_feed_forward1_weight_to_fp16, x = linear_0_cast_fp16)[name = tensor("input_9_cast_fp16")]; tensor encoder_layers_0_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7296256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9393472))), name = tensor("encoder_layers_0_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_1_bias_0_to_fp16 = const()[name = tensor("linear_1_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9393600)))]; tensor linear_1_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_0_feed_forward1_linear1_weight_to_fp16_palettized, x = input_9_cast_fp16)[name = tensor("linear_1_cast_fp16")]; tensor var_356_cast_fp16 = silu(x = linear_1_cast_fp16)[name = tensor("op_356_cast_fp16")]; tensor encoder_layers_0_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9401856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11499072))), name = tensor("encoder_layers_0_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_2_bias_0_to_fp16 = const()[name = tensor("linear_2_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11499200)))]; tensor linear_2_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_feed_forward1_linear2_weight_to_fp16_palettized, x = var_356_cast_fp16)[name = tensor("linear_2_cast_fp16")]; tensor var_361_to_fp16 = const()[name = tensor("op_361_to_fp16"), val = tensor(0x1p-1)]; tensor var_362_cast_fp16 = mul(x = linear_2_cast_fp16, y = var_361_to_fp16)[name = tensor("op_362_cast_fp16")]; tensor input_13_cast_fp16 = add(x = linear_0_cast_fp16, y = var_362_cast_fp16)[name = tensor("input_13_cast_fp16")]; tensor query_2_axes_0 = const()[name = tensor("query_2_axes_0"), val = tensor([-1])]; tensor encoder_layers_0_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_0_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11501312)))]; tensor encoder_layers_0_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_0_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11503424)))]; tensor query_2_cast_fp16 = layer_norm(axes = query_2_axes_0, beta = encoder_layers_0_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_0_norm_self_att_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("query_2_cast_fp16")]; tensor var_375_shape_cast_fp16 = shape(x = query_2_cast_fp16)[name = tensor("op_375_shape_cast_fp16")]; tensor gather_52_axis_0 = const()[name = tensor("gather_52_axis_0"), val = tensor(0)]; tensor gather_52_batch_dims_0 = const()[name = tensor("gather_52_batch_dims_0"), val = tensor(0)]; tensor gather_52_validate_indices_0 = const()[name = tensor("gather_52_validate_indices_0"), val = tensor(false)]; tensor var_375_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_375_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_52_to_uint16 = const()[name = tensor("select_52_to_uint16"), val = tensor(0)]; tensor var_375_shape_cast_fp16_to_uint16 = cast(dtype = var_375_shape_cast_fp16_to_uint16_dtype_0, x = var_375_shape_cast_fp16)[name = tensor("cast_239")]; tensor gather_52_cast_uint16 = gather(axis = gather_52_axis_0, batch_dims = gather_52_batch_dims_0, indices = select_52_to_uint16, validate_indices = gather_52_validate_indices_0, x = var_375_shape_cast_fp16_to_uint16)[name = tensor("gather_52_cast_uint16")]; tensor gather_52_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_52_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_0_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11505536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12029888))), name = tensor("encoder_layers_0_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_3_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_self_attn_linear_q_weight_to_fp16_palettized, x = query_2_cast_fp16)[name = tensor("linear_3_cast_fp16")]; tensor concat_24_axis_0 = const()[name = tensor("concat_24_axis_0"), val = tensor(0)]; tensor concat_24_interleave_0 = const()[name = tensor("concat_24_interleave_0"), val = tensor(false)]; tensor gather_52_cast_uint16_to_int32 = cast(dtype = gather_52_cast_uint16_to_int32_dtype_0, x = gather_52_cast_uint16)[name = tensor("cast_238")]; tensor concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (gather_52_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_24")]; tensor q_2_cast_fp16 = reshape(shape = concat_24, x = linear_3_cast_fp16)[name = tensor("q_2_cast_fp16")]; tensor encoder_layers_0_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12030016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12554368))), name = tensor("encoder_layers_0_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_4_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_self_attn_linear_k_weight_to_fp16_palettized, x = query_2_cast_fp16)[name = tensor("linear_4_cast_fp16")]; tensor k_2_cast_fp16 = reshape(shape = concat_24, x = linear_4_cast_fp16)[name = tensor("k_2_cast_fp16")]; tensor encoder_layers_0_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12554496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13078848))), name = tensor("encoder_layers_0_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_5_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_self_attn_linear_v_weight_to_fp16_palettized, x = query_2_cast_fp16)[name = tensor("linear_5_cast_fp16")]; tensor v_2_cast_fp16 = reshape(shape = concat_24, x = linear_5_cast_fp16)[name = tensor("v_2_cast_fp16")]; tensor value_2_perm_0 = const()[name = tensor("value_2_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_0_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13078976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13603328))), name = tensor("encoder_layers_0_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_6_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_6_cast_fp16")]; tensor var_395 = const()[name = tensor("op_395"), val = tensor([1, -1, 8, 128])]; tensor p_2_cast_fp16 = reshape(shape = var_395, x = linear_6_cast_fp16)[name = tensor("p_2_cast_fp16")]; tensor encoder_layers_0_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_0_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13603456)))]; tensor var_398_cast_fp16 = add(x = q_2_cast_fp16, y = encoder_layers_0_self_attn_pos_bias_u_to_fp16)[name = tensor("op_398_cast_fp16")]; tensor encoder_layers_0_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_0_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13605568)))]; tensor var_400_cast_fp16 = add(x = q_2_cast_fp16, y = encoder_layers_0_self_attn_pos_bias_v_to_fp16)[name = tensor("op_400_cast_fp16")]; tensor x_11_transpose_x_0 = const()[name = tensor("x_11_transpose_x_0"), val = tensor(false)]; tensor x_11_transpose_y_0 = const()[name = tensor("x_11_transpose_y_0"), val = tensor(false)]; tensor transpose_192_perm_0 = const()[name = tensor("transpose_192_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_193_perm_0 = const()[name = tensor("transpose_193_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_193 = transpose(perm = transpose_193_perm_0, x = p_2_cast_fp16)[name = tensor("transpose_478")]; tensor transpose_192 = transpose(perm = transpose_192_perm_0, x = var_400_cast_fp16)[name = tensor("transpose_479")]; tensor x_11_cast_fp16 = matmul(transpose_x = x_11_transpose_x_0, transpose_y = x_11_transpose_y_0, x = transpose_192, y = transpose_193)[name = tensor("x_11_cast_fp16")]; tensor var_404_shape_cast_fp16 = shape(x = x_11_cast_fp16)[name = tensor("op_404_shape_cast_fp16")]; tensor gather_54_axis_0 = const()[name = tensor("gather_54_axis_0"), val = tensor(0)]; tensor gather_54_batch_dims_0 = const()[name = tensor("gather_54_batch_dims_0"), val = tensor(0)]; tensor gather_54_validate_indices_0 = const()[name = tensor("gather_54_validate_indices_0"), val = tensor(false)]; tensor var_404_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_404_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_54_to_uint16 = const()[name = tensor("select_54_to_uint16"), val = tensor(0)]; tensor var_404_shape_cast_fp16_to_uint16 = cast(dtype = var_404_shape_cast_fp16_to_uint16_dtype_0, x = var_404_shape_cast_fp16)[name = tensor("cast_237")]; tensor gather_54_cast_uint16 = gather(axis = gather_54_axis_0, batch_dims = gather_54_batch_dims_0, indices = select_54_to_uint16, validate_indices = gather_54_validate_indices_0, x = var_404_shape_cast_fp16_to_uint16)[name = tensor("gather_54_cast_uint16")]; tensor gather_54_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_54_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_55 = const()[name = tensor("gather_55"), val = tensor(8)]; tensor gather_56_axis_0 = const()[name = tensor("gather_56_axis_0"), val = tensor(0)]; tensor gather_56_batch_dims_0 = const()[name = tensor("gather_56_batch_dims_0"), val = tensor(0)]; tensor gather_56_validate_indices_0 = const()[name = tensor("gather_56_validate_indices_0"), val = tensor(false)]; tensor select_56_to_uint16 = const()[name = tensor("select_56_to_uint16"), val = tensor(2)]; tensor gather_56_cast_uint16 = gather(axis = gather_56_axis_0, batch_dims = gather_56_batch_dims_0, indices = select_56_to_uint16, validate_indices = gather_56_validate_indices_0, x = var_404_shape_cast_fp16_to_uint16)[name = tensor("gather_56_cast_uint16")]; tensor gather_56_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_56_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_57_axis_0 = const()[name = tensor("gather_57_axis_0"), val = tensor(0)]; tensor gather_57_batch_dims_0 = const()[name = tensor("gather_57_batch_dims_0"), val = tensor(0)]; tensor gather_57_validate_indices_0 = const()[name = tensor("gather_57_validate_indices_0"), val = tensor(false)]; tensor select_57_to_uint16 = const()[name = tensor("select_57_to_uint16"), val = tensor(3)]; tensor gather_57_cast_uint16 = gather(axis = gather_57_axis_0, batch_dims = gather_57_batch_dims_0, indices = select_57_to_uint16, validate_indices = gather_57_validate_indices_0, x = var_404_shape_cast_fp16_to_uint16)[name = tensor("gather_57_cast_uint16")]; tensor gather_57_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_57_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_4_pad_0 = const()[name = tensor("x0_4_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_4_mode_0 = const()[name = tensor("x0_4_mode_0"), val = tensor("constant")]; tensor const_11_to_fp16 = const()[name = tensor("const_11_to_fp16"), val = tensor(0x0p+0)]; tensor x0_4_cast_fp16 = pad(constant_val = const_11_to_fp16, mode = x0_4_mode_0, pad = x0_4_pad_0, x = x_11_cast_fp16)[name = tensor("x0_4_cast_fp16")]; tensor concat_27_axis_0 = const()[name = tensor("concat_27_axis_0"), val = tensor(0)]; tensor concat_27_interleave_0 = const()[name = tensor("concat_27_interleave_0"), val = tensor(false)]; tensor gather_54_cast_uint16_to_int32 = cast(dtype = gather_54_cast_uint16_to_int32_dtype_0, x = gather_54_cast_uint16)[name = tensor("cast_235")]; tensor gather_56_cast_uint16_to_int32 = cast(dtype = gather_56_cast_uint16_to_int32_dtype_0, x = gather_56_cast_uint16)[name = tensor("cast_236")]; tensor concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (gather_54_cast_uint16_to_int32, gather_55, var_21, gather_56_cast_uint16_to_int32))[name = tensor("concat_27")]; tensor x1_2_cast_fp16 = reshape(shape = concat_27, x = x0_4_cast_fp16)[name = tensor("x1_2_cast_fp16")]; tensor var_414_begin_0 = const()[name = tensor("op_414_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_414_end_0 = const()[name = tensor("op_414_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_414_end_mask_0 = const()[name = tensor("op_414_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_414_cast_fp16 = slice_by_index(begin = var_414_begin_0, end = var_414_end_0, end_mask = var_414_end_mask_0, x = x1_2_cast_fp16)[name = tensor("op_414_cast_fp16")]; tensor concat_28_axis_0 = const()[name = tensor("concat_28_axis_0"), val = tensor(0)]; tensor concat_28_interleave_0 = const()[name = tensor("concat_28_interleave_0"), val = tensor(false)]; tensor gather_57_cast_uint16_to_int32 = cast(dtype = gather_57_cast_uint16_to_int32_dtype_0, x = gather_57_cast_uint16)[name = tensor("cast_234")]; tensor concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (gather_54_cast_uint16_to_int32, gather_55, gather_56_cast_uint16_to_int32, gather_57_cast_uint16_to_int32))[name = tensor("concat_28")]; tensor matrix_bd_2_cast_fp16 = reshape(shape = concat_28, x = var_414_cast_fp16)[name = tensor("matrix_bd_2_cast_fp16")]; tensor matrix_ac_2_transpose_x_0 = const()[name = tensor("matrix_ac_2_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_2_transpose_y_0 = const()[name = tensor("matrix_ac_2_transpose_y_0"), val = tensor(false)]; tensor transpose_194_perm_0 = const()[name = tensor("transpose_194_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_195_perm_0 = const()[name = tensor("transpose_195_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_195 = transpose(perm = transpose_195_perm_0, x = k_2_cast_fp16)[name = tensor("transpose_476")]; tensor transpose_194 = transpose(perm = transpose_194_perm_0, x = var_398_cast_fp16)[name = tensor("transpose_477")]; tensor matrix_ac_2_cast_fp16 = matmul(transpose_x = matrix_ac_2_transpose_x_0, transpose_y = matrix_ac_2_transpose_y_0, x = transpose_194, y = transpose_195)[name = tensor("matrix_ac_2_cast_fp16")]; tensor var_419_shape_cast_fp16 = shape(x = matrix_ac_2_cast_fp16)[name = tensor("op_419_shape_cast_fp16")]; tensor gather_58_axis_0 = const()[name = tensor("gather_58_axis_0"), val = tensor(0)]; tensor gather_58_batch_dims_0 = const()[name = tensor("gather_58_batch_dims_0"), val = tensor(0)]; tensor gather_58_validate_indices_0 = const()[name = tensor("gather_58_validate_indices_0"), val = tensor(false)]; tensor var_419_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_419_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_58_to_uint16 = const()[name = tensor("select_58_to_uint16"), val = tensor(3)]; tensor var_419_shape_cast_fp16_to_uint16 = cast(dtype = var_419_shape_cast_fp16_to_uint16_dtype_0, x = var_419_shape_cast_fp16)[name = tensor("cast_233")]; tensor gather_58_cast_uint16 = gather(axis = gather_58_axis_0, batch_dims = gather_58_batch_dims_0, indices = select_58_to_uint16, validate_indices = gather_58_validate_indices_0, x = var_419_shape_cast_fp16_to_uint16)[name = tensor("gather_58_cast_uint16")]; tensor gather_58_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_58_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_29_values0_0 = const()[name = tensor("concat_29_values0_0"), val = tensor(0)]; tensor concat_29_values1_0 = const()[name = tensor("concat_29_values1_0"), val = tensor(8)]; tensor concat_29_values2_0 = const()[name = tensor("concat_29_values2_0"), val = tensor(0)]; tensor concat_29_axis_0 = const()[name = tensor("concat_29_axis_0"), val = tensor(0)]; tensor concat_29_interleave_0 = const()[name = tensor("concat_29_interleave_0"), val = tensor(false)]; tensor gather_58_cast_uint16_to_int32 = cast(dtype = gather_58_cast_uint16_to_int32_dtype_0, x = gather_58_cast_uint16)[name = tensor("cast_232")]; tensor concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (concat_29_values0_0, concat_29_values1_0, concat_29_values2_0, gather_58_cast_uint16_to_int32))[name = tensor("concat_29")]; tensor matrix_bd0_2_begin_0 = const()[name = tensor("matrix_bd0_2_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_2_end_mask_0 = const()[name = tensor("matrix_bd0_2_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_2_cast_fp16 = slice_by_index(begin = matrix_bd0_2_begin_0, end = concat_29, end_mask = matrix_bd0_2_end_mask_0, x = matrix_bd_2_cast_fp16)[name = tensor("matrix_bd0_2_cast_fp16")]; tensor var_424_cast_fp16 = add(x = matrix_ac_2_cast_fp16, y = matrix_bd0_2_cast_fp16)[name = tensor("op_424_cast_fp16")]; tensor _inversed_scores_2_y_0_to_fp16 = const()[name = tensor("_inversed_scores_2_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_2_cast_fp16 = mul(x = var_424_cast_fp16, y = _inversed_scores_2_y_0_to_fp16)[name = tensor("_inversed_scores_2_cast_fp16")]; tensor value_2_cast_fp16 = transpose(perm = value_2_perm_0, x = v_2_cast_fp16)[name = tensor("transpose_475")]; tensor var_427_shape_cast_fp16 = shape(x = value_2_cast_fp16)[name = tensor("op_427_shape_cast_fp16")]; tensor gather_59_axis_0 = const()[name = tensor("gather_59_axis_0"), val = tensor(0)]; tensor gather_59_batch_dims_0 = const()[name = tensor("gather_59_batch_dims_0"), val = tensor(0)]; tensor gather_59_validate_indices_0 = const()[name = tensor("gather_59_validate_indices_0"), val = tensor(false)]; tensor var_427_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_427_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_59_to_uint16 = const()[name = tensor("select_59_to_uint16"), val = tensor(0)]; tensor var_427_shape_cast_fp16_to_uint16 = cast(dtype = var_427_shape_cast_fp16_to_uint16_dtype_0, x = var_427_shape_cast_fp16)[name = tensor("cast_231")]; tensor gather_59_cast_uint16 = gather(axis = gather_59_axis_0, batch_dims = gather_59_batch_dims_0, indices = select_59_to_uint16, validate_indices = gather_59_validate_indices_0, x = var_427_shape_cast_fp16_to_uint16)[name = tensor("gather_59_cast_uint16")]; tensor gather_59_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_59_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor mask0_4_axes_0 = const()[name = tensor("mask0_4_axes_0"), val = tensor([1])]; tensor mask0_4 = expand_dims(axes = mask0_4_axes_0, x = mask_2)[name = tensor("mask0_4")]; tensor var_9_to_fp16 = const()[name = tensor("op_9_to_fp16"), val = tensor(-0x1.388p+13)]; tensor scores0_2_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_2_cast_fp16, cond = mask0_4)[name = tensor("scores0_2_cast_fp16")]; tensor var_430_cast_fp16 = softmax(axis = var_21, x = scores0_2_cast_fp16)[name = tensor("op_430_cast_fp16")]; tensor var_8_to_fp16 = const()[name = tensor("op_8_to_fp16"), val = tensor(0x0p+0)]; tensor input_15_cast_fp16 = select(a = var_8_to_fp16, b = var_430_cast_fp16, cond = mask0_4)[name = tensor("input_15_cast_fp16")]; tensor x2_2_transpose_x_0 = const()[name = tensor("x2_2_transpose_x_0"), val = tensor(false)]; tensor x2_2_transpose_y_0 = const()[name = tensor("x2_2_transpose_y_0"), val = tensor(false)]; tensor x2_2_cast_fp16 = matmul(transpose_x = x2_2_transpose_x_0, transpose_y = x2_2_transpose_y_0, x = input_15_cast_fp16, y = value_2_cast_fp16)[name = tensor("x2_2_cast_fp16")]; tensor var_434_perm_0 = const()[name = tensor("op_434_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_30_axis_0 = const()[name = tensor("concat_30_axis_0"), val = tensor(0)]; tensor concat_30_interleave_0 = const()[name = tensor("concat_30_interleave_0"), val = tensor(false)]; tensor gather_59_cast_uint16_to_int32 = cast(dtype = gather_59_cast_uint16_to_int32_dtype_0, x = gather_59_cast_uint16)[name = tensor("cast_230")]; tensor concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (gather_59_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_30")]; tensor var_434_cast_fp16 = transpose(perm = var_434_perm_0, x = x2_2_cast_fp16)[name = tensor("transpose_474")]; tensor input0_6_cast_fp16 = reshape(shape = concat_30, x = var_434_cast_fp16)[name = tensor("input0_6_cast_fp16")]; tensor encoder_layers_0_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13607680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14132032))), name = tensor("encoder_layers_0_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_7_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_self_attn_linear_out_weight_to_fp16_palettized, x = input0_6_cast_fp16)[name = tensor("linear_7_cast_fp16")]; tensor input0_13_cast_fp16 = add(x = input_13_cast_fp16, y = linear_7_cast_fp16)[name = tensor("input0_13_cast_fp16")]; tensor x_15_axes_0 = const()[name = tensor("x_15_axes_0"), val = tensor([-1])]; tensor encoder_layers_0_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_0_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14132160)))]; tensor encoder_layers_0_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_0_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14134272)))]; tensor x_15_cast_fp16 = layer_norm(axes = x_15_axes_0, beta = encoder_layers_0_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_0_norm_conv_weight_to_fp16, x = input0_13_cast_fp16)[name = tensor("x_15_cast_fp16")]; tensor input_17_perm_0 = const()[name = tensor("input_17_perm_0"), val = tensor([0, 2, 1])]; tensor input0_15_pad_type_0 = const()[name = tensor("input0_15_pad_type_0"), val = tensor("valid")]; tensor input0_15_strides_0 = const()[name = tensor("input0_15_strides_0"), val = tensor([1])]; tensor input0_15_pad_0 = const()[name = tensor("input0_15_pad_0"), val = tensor([0, 0])]; tensor input0_15_dilations_0 = const()[name = tensor("input0_15_dilations_0"), val = tensor([1])]; tensor input0_15_groups_0 = const()[name = tensor("input0_15_groups_0"), val = tensor(1)]; tensor encoder_layers_0_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14136384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15185024))), name = tensor("encoder_layers_0_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_17_cast_fp16 = transpose(perm = input_17_perm_0, x = x_15_cast_fp16)[name = tensor("transpose_473")]; tensor input0_15_cast_fp16 = conv(dilations = input0_15_dilations_0, groups = input0_15_groups_0, pad = input0_15_pad_0, pad_type = input0_15_pad_type_0, strides = input0_15_strides_0, weight = encoder_layers_0_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_17_cast_fp16)[name = tensor("input0_15_cast_fp16")]; tensor x_17_split_num_splits_0 = const()[name = tensor("x_17_split_num_splits_0"), val = tensor(2)]; tensor x_17_split_axis_0 = const()[name = tensor("x_17_split_axis_0"), val = tensor(1)]; tensor x_17_split_cast_fp16_0, tensor x_17_split_cast_fp16_1 = split(axis = x_17_split_axis_0, num_splits = x_17_split_num_splits_0, x = input0_15_cast_fp16)[name = tensor("x_17_split_cast_fp16")]; tensor x_17_split_1_sigmoid_cast_fp16 = sigmoid(x = x_17_split_cast_fp16_1)[name = tensor("x_17_split_1_sigmoid_cast_fp16")]; tensor x_17_cast_fp16 = mul(x = x_17_split_cast_fp16_0, y = x_17_split_1_sigmoid_cast_fp16)[name = tensor("x_17_cast_fp16")]; tensor var_457_axes_0 = const()[name = tensor("op_457_axes_0"), val = tensor([1])]; tensor var_457 = expand_dims(axes = var_457_axes_0, x = pad_mask0_1)[name = tensor("op_457")]; tensor input3_1_cast_fp16 = select(a = var_8_to_fp16, b = x_17_cast_fp16, cond = var_457)[name = tensor("input3_1_cast_fp16")]; tensor input0_8_pad_0 = const()[name = tensor("input0_8_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_8_mode_0 = const()[name = tensor("input0_8_mode_0"), val = tensor("constant")]; tensor const_12_to_fp16 = const()[name = tensor("const_12_to_fp16"), val = tensor(0x0p+0)]; tensor input0_8_cast_fp16 = pad(constant_val = const_12_to_fp16, mode = input0_8_mode_0, pad = input0_8_pad_0, x = input3_1_cast_fp16)[name = tensor("input0_8_cast_fp16")]; tensor input1_6_pad_type_0 = const()[name = tensor("input1_6_pad_type_0"), val = tensor("valid")]; tensor input1_6_groups_0 = const()[name = tensor("input1_6_groups_0"), val = tensor(1024)]; tensor input1_6_strides_0 = const()[name = tensor("input1_6_strides_0"), val = tensor([1])]; tensor input1_6_pad_0 = const()[name = tensor("input1_6_pad_0"), val = tensor([0, 0])]; tensor input1_6_dilations_0 = const()[name = tensor("input1_6_dilations_0"), val = tensor([1])]; tensor const_59_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15185152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15189824))), name = tensor("const_59_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_60_to_fp16 = const()[name = tensor("const_60_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15189952)))]; tensor input_19_cast_fp16 = conv(bias = const_60_to_fp16, dilations = input1_6_dilations_0, groups = input1_6_groups_0, pad = input1_6_pad_0, pad_type = input1_6_pad_type_0, strides = input1_6_strides_0, weight = const_59_to_fp16_palettized, x = input0_8_cast_fp16)[name = tensor("input_19_cast_fp16")]; tensor var_472_cast_fp16 = silu(x = input_19_cast_fp16)[name = tensor("op_472_cast_fp16")]; tensor x_19_pad_type_0 = const()[name = tensor("x_19_pad_type_0"), val = tensor("valid")]; tensor x_19_strides_0 = const()[name = tensor("x_19_strides_0"), val = tensor([1])]; tensor x_19_pad_0 = const()[name = tensor("x_19_pad_0"), val = tensor([0, 0])]; tensor x_19_dilations_0 = const()[name = tensor("x_19_dilations_0"), val = tensor([1])]; tensor x_19_groups_0 = const()[name = tensor("x_19_groups_0"), val = tensor(1)]; tensor encoder_layers_0_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15192064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15716416))), name = tensor("encoder_layers_0_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_19_cast_fp16 = conv(dilations = x_19_dilations_0, groups = x_19_groups_0, pad = x_19_pad_0, pad_type = x_19_pad_type_0, strides = x_19_strides_0, weight = encoder_layers_0_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_472_cast_fp16)[name = tensor("x_19_cast_fp16")]; tensor var_479_perm_0 = const()[name = tensor("op_479_perm_0"), val = tensor([0, 2, 1])]; tensor var_479_cast_fp16 = transpose(perm = var_479_perm_0, x = x_19_cast_fp16)[name = tensor("transpose_472")]; tensor input1_8_cast_fp16 = add(x = input0_13_cast_fp16, y = var_479_cast_fp16)[name = tensor("input1_8_cast_fp16")]; tensor input0_10_axes_0 = const()[name = tensor("input0_10_axes_0"), val = tensor([-1])]; tensor encoder_layers_0_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_0_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15716544)))]; tensor encoder_layers_0_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_0_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15718656)))]; tensor input0_10_cast_fp16 = layer_norm(axes = input0_10_axes_0, beta = encoder_layers_0_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_0_norm_feed_forward2_weight_to_fp16, x = input1_8_cast_fp16)[name = tensor("input0_10_cast_fp16")]; tensor encoder_layers_0_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15720768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17817984))), name = tensor("encoder_layers_0_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_8_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_0_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_10_cast_fp16)[name = tensor("linear_8_cast_fp16")]; tensor var_490_cast_fp16 = silu(x = linear_8_cast_fp16)[name = tensor("op_490_cast_fp16")]; tensor encoder_layers_0_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17818112))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19915328))), name = tensor("encoder_layers_0_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_9_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_0_feed_forward2_linear2_weight_to_fp16_palettized, x = var_490_cast_fp16)[name = tensor("linear_9_cast_fp16")]; tensor var_495_to_fp16 = const()[name = tensor("op_495_to_fp16"), val = tensor(0x1p-1)]; tensor var_496_cast_fp16 = mul(x = linear_9_cast_fp16, y = var_495_to_fp16)[name = tensor("op_496_cast_fp16")]; tensor input2_4_cast_fp16 = add(x = input1_8_cast_fp16, y = var_496_cast_fp16)[name = tensor("input2_4_cast_fp16")]; tensor input0_17_axes_0 = const()[name = tensor("input0_17_axes_0"), val = tensor([-1])]; tensor encoder_layers_0_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_0_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19915456)))]; tensor encoder_layers_0_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_0_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19917568)))]; tensor input0_17_cast_fp16 = layer_norm(axes = input0_17_axes_0, beta = encoder_layers_0_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_0_norm_out_weight_to_fp16, x = input2_4_cast_fp16)[name = tensor("input0_17_cast_fp16")]; tensor input_23_axes_0 = const()[name = tensor("input_23_axes_0"), val = tensor([-1])]; tensor encoder_layers_1_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_1_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19919680)))]; tensor encoder_layers_1_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_1_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19921792)))]; tensor input_23_cast_fp16 = layer_norm(axes = input_23_axes_0, beta = encoder_layers_1_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_1_norm_feed_forward1_weight_to_fp16, x = input0_17_cast_fp16)[name = tensor("input_23_cast_fp16")]; tensor encoder_layers_1_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19923904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22021120))), name = tensor("encoder_layers_1_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_10_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_1_feed_forward1_linear1_weight_to_fp16_palettized, x = input_23_cast_fp16)[name = tensor("linear_10_cast_fp16")]; tensor var_519_cast_fp16 = silu(x = linear_10_cast_fp16)[name = tensor("op_519_cast_fp16")]; tensor encoder_layers_1_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22021248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24118464))), name = tensor("encoder_layers_1_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_11_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_feed_forward1_linear2_weight_to_fp16_palettized, x = var_519_cast_fp16)[name = tensor("linear_11_cast_fp16")]; tensor var_524_to_fp16 = const()[name = tensor("op_524_to_fp16"), val = tensor(0x1p-1)]; tensor var_525_cast_fp16 = mul(x = linear_11_cast_fp16, y = var_524_to_fp16)[name = tensor("op_525_cast_fp16")]; tensor input_27_cast_fp16 = add(x = input0_17_cast_fp16, y = var_525_cast_fp16)[name = tensor("input_27_cast_fp16")]; tensor query_4_axes_0 = const()[name = tensor("query_4_axes_0"), val = tensor([-1])]; tensor encoder_layers_1_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_1_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24118592)))]; tensor encoder_layers_1_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_1_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24120704)))]; tensor query_4_cast_fp16 = layer_norm(axes = query_4_axes_0, beta = encoder_layers_1_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_1_norm_self_att_weight_to_fp16, x = input_27_cast_fp16)[name = tensor("query_4_cast_fp16")]; tensor var_538_shape_cast_fp16 = shape(x = query_4_cast_fp16)[name = tensor("op_538_shape_cast_fp16")]; tensor gather_60_axis_0 = const()[name = tensor("gather_60_axis_0"), val = tensor(0)]; tensor gather_60_batch_dims_0 = const()[name = tensor("gather_60_batch_dims_0"), val = tensor(0)]; tensor gather_60_validate_indices_0 = const()[name = tensor("gather_60_validate_indices_0"), val = tensor(false)]; tensor var_538_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_538_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_60_to_uint16 = const()[name = tensor("select_60_to_uint16"), val = tensor(0)]; tensor var_538_shape_cast_fp16_to_uint16 = cast(dtype = var_538_shape_cast_fp16_to_uint16_dtype_0, x = var_538_shape_cast_fp16)[name = tensor("cast_229")]; tensor gather_60_cast_uint16 = gather(axis = gather_60_axis_0, batch_dims = gather_60_batch_dims_0, indices = select_60_to_uint16, validate_indices = gather_60_validate_indices_0, x = var_538_shape_cast_fp16_to_uint16)[name = tensor("gather_60_cast_uint16")]; tensor gather_60_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_60_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_1_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24122816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24647168))), name = tensor("encoder_layers_1_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_12_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_self_attn_linear_q_weight_to_fp16_palettized, x = query_4_cast_fp16)[name = tensor("linear_12_cast_fp16")]; tensor concat_31_axis_0 = const()[name = tensor("concat_31_axis_0"), val = tensor(0)]; tensor concat_31_interleave_0 = const()[name = tensor("concat_31_interleave_0"), val = tensor(false)]; tensor gather_60_cast_uint16_to_int32 = cast(dtype = gather_60_cast_uint16_to_int32_dtype_0, x = gather_60_cast_uint16)[name = tensor("cast_228")]; tensor concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (gather_60_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_31")]; tensor q_4_cast_fp16 = reshape(shape = concat_31, x = linear_12_cast_fp16)[name = tensor("q_4_cast_fp16")]; tensor encoder_layers_1_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24647296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25171648))), name = tensor("encoder_layers_1_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_13_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_self_attn_linear_k_weight_to_fp16_palettized, x = query_4_cast_fp16)[name = tensor("linear_13_cast_fp16")]; tensor k_4_cast_fp16 = reshape(shape = concat_31, x = linear_13_cast_fp16)[name = tensor("k_4_cast_fp16")]; tensor encoder_layers_1_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25171776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25696128))), name = tensor("encoder_layers_1_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_14_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_self_attn_linear_v_weight_to_fp16_palettized, x = query_4_cast_fp16)[name = tensor("linear_14_cast_fp16")]; tensor v_4_cast_fp16 = reshape(shape = concat_31, x = linear_14_cast_fp16)[name = tensor("v_4_cast_fp16")]; tensor value_4_perm_0 = const()[name = tensor("value_4_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_1_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25696256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26220608))), name = tensor("encoder_layers_1_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_15_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_15_cast_fp16")]; tensor var_558 = const()[name = tensor("op_558"), val = tensor([1, -1, 8, 128])]; tensor p_4_cast_fp16 = reshape(shape = var_558, x = linear_15_cast_fp16)[name = tensor("p_4_cast_fp16")]; tensor encoder_layers_1_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_1_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26220736)))]; tensor var_561_cast_fp16 = add(x = q_4_cast_fp16, y = encoder_layers_1_self_attn_pos_bias_u_to_fp16)[name = tensor("op_561_cast_fp16")]; tensor encoder_layers_1_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_1_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26222848)))]; tensor var_563_cast_fp16 = add(x = q_4_cast_fp16, y = encoder_layers_1_self_attn_pos_bias_v_to_fp16)[name = tensor("op_563_cast_fp16")]; tensor x_27_transpose_x_0 = const()[name = tensor("x_27_transpose_x_0"), val = tensor(false)]; tensor x_27_transpose_y_0 = const()[name = tensor("x_27_transpose_y_0"), val = tensor(false)]; tensor transpose_196_perm_0 = const()[name = tensor("transpose_196_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_197_perm_0 = const()[name = tensor("transpose_197_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_197 = transpose(perm = transpose_197_perm_0, x = p_4_cast_fp16)[name = tensor("transpose_470")]; tensor transpose_196 = transpose(perm = transpose_196_perm_0, x = var_563_cast_fp16)[name = tensor("transpose_471")]; tensor x_27_cast_fp16 = matmul(transpose_x = x_27_transpose_x_0, transpose_y = x_27_transpose_y_0, x = transpose_196, y = transpose_197)[name = tensor("x_27_cast_fp16")]; tensor var_567_shape_cast_fp16 = shape(x = x_27_cast_fp16)[name = tensor("op_567_shape_cast_fp16")]; tensor gather_62_axis_0 = const()[name = tensor("gather_62_axis_0"), val = tensor(0)]; tensor gather_62_batch_dims_0 = const()[name = tensor("gather_62_batch_dims_0"), val = tensor(0)]; tensor gather_62_validate_indices_0 = const()[name = tensor("gather_62_validate_indices_0"), val = tensor(false)]; tensor var_567_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_567_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_62_to_uint16 = const()[name = tensor("select_62_to_uint16"), val = tensor(0)]; tensor var_567_shape_cast_fp16_to_uint16 = cast(dtype = var_567_shape_cast_fp16_to_uint16_dtype_0, x = var_567_shape_cast_fp16)[name = tensor("cast_227")]; tensor gather_62_cast_uint16 = gather(axis = gather_62_axis_0, batch_dims = gather_62_batch_dims_0, indices = select_62_to_uint16, validate_indices = gather_62_validate_indices_0, x = var_567_shape_cast_fp16_to_uint16)[name = tensor("gather_62_cast_uint16")]; tensor gather_62_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_62_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_63 = const()[name = tensor("gather_63"), val = tensor(8)]; tensor gather_64_axis_0 = const()[name = tensor("gather_64_axis_0"), val = tensor(0)]; tensor gather_64_batch_dims_0 = const()[name = tensor("gather_64_batch_dims_0"), val = tensor(0)]; tensor gather_64_validate_indices_0 = const()[name = tensor("gather_64_validate_indices_0"), val = tensor(false)]; tensor select_64_to_uint16 = const()[name = tensor("select_64_to_uint16"), val = tensor(2)]; tensor gather_64_cast_uint16 = gather(axis = gather_64_axis_0, batch_dims = gather_64_batch_dims_0, indices = select_64_to_uint16, validate_indices = gather_64_validate_indices_0, x = var_567_shape_cast_fp16_to_uint16)[name = tensor("gather_64_cast_uint16")]; tensor gather_64_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_64_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_65_axis_0 = const()[name = tensor("gather_65_axis_0"), val = tensor(0)]; tensor gather_65_batch_dims_0 = const()[name = tensor("gather_65_batch_dims_0"), val = tensor(0)]; tensor gather_65_validate_indices_0 = const()[name = tensor("gather_65_validate_indices_0"), val = tensor(false)]; tensor select_65_to_uint16 = const()[name = tensor("select_65_to_uint16"), val = tensor(3)]; tensor gather_65_cast_uint16 = gather(axis = gather_65_axis_0, batch_dims = gather_65_batch_dims_0, indices = select_65_to_uint16, validate_indices = gather_65_validate_indices_0, x = var_567_shape_cast_fp16_to_uint16)[name = tensor("gather_65_cast_uint16")]; tensor gather_65_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_65_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_6_pad_0 = const()[name = tensor("x0_6_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_6_mode_0 = const()[name = tensor("x0_6_mode_0"), val = tensor("constant")]; tensor const_13_to_fp16 = const()[name = tensor("const_13_to_fp16"), val = tensor(0x0p+0)]; tensor x0_6_cast_fp16 = pad(constant_val = const_13_to_fp16, mode = x0_6_mode_0, pad = x0_6_pad_0, x = x_27_cast_fp16)[name = tensor("x0_6_cast_fp16")]; tensor concat_34_axis_0 = const()[name = tensor("concat_34_axis_0"), val = tensor(0)]; tensor concat_34_interleave_0 = const()[name = tensor("concat_34_interleave_0"), val = tensor(false)]; tensor gather_62_cast_uint16_to_int32 = cast(dtype = gather_62_cast_uint16_to_int32_dtype_0, x = gather_62_cast_uint16)[name = tensor("cast_225")]; tensor gather_64_cast_uint16_to_int32 = cast(dtype = gather_64_cast_uint16_to_int32_dtype_0, x = gather_64_cast_uint16)[name = tensor("cast_226")]; tensor concat_34 = concat(axis = concat_34_axis_0, interleave = concat_34_interleave_0, values = (gather_62_cast_uint16_to_int32, gather_63, var_21, gather_64_cast_uint16_to_int32))[name = tensor("concat_34")]; tensor x1_4_cast_fp16 = reshape(shape = concat_34, x = x0_6_cast_fp16)[name = tensor("x1_4_cast_fp16")]; tensor var_577_begin_0 = const()[name = tensor("op_577_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_577_end_0 = const()[name = tensor("op_577_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_577_end_mask_0 = const()[name = tensor("op_577_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_577_cast_fp16 = slice_by_index(begin = var_577_begin_0, end = var_577_end_0, end_mask = var_577_end_mask_0, x = x1_4_cast_fp16)[name = tensor("op_577_cast_fp16")]; tensor concat_35_axis_0 = const()[name = tensor("concat_35_axis_0"), val = tensor(0)]; tensor concat_35_interleave_0 = const()[name = tensor("concat_35_interleave_0"), val = tensor(false)]; tensor gather_65_cast_uint16_to_int32 = cast(dtype = gather_65_cast_uint16_to_int32_dtype_0, x = gather_65_cast_uint16)[name = tensor("cast_224")]; tensor concat_35 = concat(axis = concat_35_axis_0, interleave = concat_35_interleave_0, values = (gather_62_cast_uint16_to_int32, gather_63, gather_64_cast_uint16_to_int32, gather_65_cast_uint16_to_int32))[name = tensor("concat_35")]; tensor matrix_bd_4_cast_fp16 = reshape(shape = concat_35, x = var_577_cast_fp16)[name = tensor("matrix_bd_4_cast_fp16")]; tensor matrix_ac_4_transpose_x_0 = const()[name = tensor("matrix_ac_4_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_4_transpose_y_0 = const()[name = tensor("matrix_ac_4_transpose_y_0"), val = tensor(false)]; tensor transpose_198_perm_0 = const()[name = tensor("transpose_198_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_199_perm_0 = const()[name = tensor("transpose_199_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_199 = transpose(perm = transpose_199_perm_0, x = k_4_cast_fp16)[name = tensor("transpose_468")]; tensor transpose_198 = transpose(perm = transpose_198_perm_0, x = var_561_cast_fp16)[name = tensor("transpose_469")]; tensor matrix_ac_4_cast_fp16 = matmul(transpose_x = matrix_ac_4_transpose_x_0, transpose_y = matrix_ac_4_transpose_y_0, x = transpose_198, y = transpose_199)[name = tensor("matrix_ac_4_cast_fp16")]; tensor var_582_shape_cast_fp16 = shape(x = matrix_ac_4_cast_fp16)[name = tensor("op_582_shape_cast_fp16")]; tensor gather_66_axis_0 = const()[name = tensor("gather_66_axis_0"), val = tensor(0)]; tensor gather_66_batch_dims_0 = const()[name = tensor("gather_66_batch_dims_0"), val = tensor(0)]; tensor gather_66_validate_indices_0 = const()[name = tensor("gather_66_validate_indices_0"), val = tensor(false)]; tensor var_582_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_582_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_66_to_uint16 = const()[name = tensor("select_66_to_uint16"), val = tensor(3)]; tensor var_582_shape_cast_fp16_to_uint16 = cast(dtype = var_582_shape_cast_fp16_to_uint16_dtype_0, x = var_582_shape_cast_fp16)[name = tensor("cast_223")]; tensor gather_66_cast_uint16 = gather(axis = gather_66_axis_0, batch_dims = gather_66_batch_dims_0, indices = select_66_to_uint16, validate_indices = gather_66_validate_indices_0, x = var_582_shape_cast_fp16_to_uint16)[name = tensor("gather_66_cast_uint16")]; tensor gather_66_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_66_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_36_values0_0 = const()[name = tensor("concat_36_values0_0"), val = tensor(0)]; tensor concat_36_values1_0 = const()[name = tensor("concat_36_values1_0"), val = tensor(8)]; tensor concat_36_values2_0 = const()[name = tensor("concat_36_values2_0"), val = tensor(0)]; tensor concat_36_axis_0 = const()[name = tensor("concat_36_axis_0"), val = tensor(0)]; tensor concat_36_interleave_0 = const()[name = tensor("concat_36_interleave_0"), val = tensor(false)]; tensor gather_66_cast_uint16_to_int32 = cast(dtype = gather_66_cast_uint16_to_int32_dtype_0, x = gather_66_cast_uint16)[name = tensor("cast_222")]; tensor concat_36 = concat(axis = concat_36_axis_0, interleave = concat_36_interleave_0, values = (concat_36_values0_0, concat_36_values1_0, concat_36_values2_0, gather_66_cast_uint16_to_int32))[name = tensor("concat_36")]; tensor matrix_bd0_4_begin_0 = const()[name = tensor("matrix_bd0_4_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_4_end_mask_0 = const()[name = tensor("matrix_bd0_4_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_4_cast_fp16 = slice_by_index(begin = matrix_bd0_4_begin_0, end = concat_36, end_mask = matrix_bd0_4_end_mask_0, x = matrix_bd_4_cast_fp16)[name = tensor("matrix_bd0_4_cast_fp16")]; tensor var_587_cast_fp16 = add(x = matrix_ac_4_cast_fp16, y = matrix_bd0_4_cast_fp16)[name = tensor("op_587_cast_fp16")]; tensor _inversed_scores_4_y_0_to_fp16 = const()[name = tensor("_inversed_scores_4_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_4_cast_fp16 = mul(x = var_587_cast_fp16, y = _inversed_scores_4_y_0_to_fp16)[name = tensor("_inversed_scores_4_cast_fp16")]; tensor value_4_cast_fp16 = transpose(perm = value_4_perm_0, x = v_4_cast_fp16)[name = tensor("transpose_467")]; tensor var_590_shape_cast_fp16 = shape(x = value_4_cast_fp16)[name = tensor("op_590_shape_cast_fp16")]; tensor gather_67_axis_0 = const()[name = tensor("gather_67_axis_0"), val = tensor(0)]; tensor gather_67_batch_dims_0 = const()[name = tensor("gather_67_batch_dims_0"), val = tensor(0)]; tensor gather_67_validate_indices_0 = const()[name = tensor("gather_67_validate_indices_0"), val = tensor(false)]; tensor var_590_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_590_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_67_to_uint16 = const()[name = tensor("select_67_to_uint16"), val = tensor(0)]; tensor var_590_shape_cast_fp16_to_uint16 = cast(dtype = var_590_shape_cast_fp16_to_uint16_dtype_0, x = var_590_shape_cast_fp16)[name = tensor("cast_221")]; tensor gather_67_cast_uint16 = gather(axis = gather_67_axis_0, batch_dims = gather_67_batch_dims_0, indices = select_67_to_uint16, validate_indices = gather_67_validate_indices_0, x = var_590_shape_cast_fp16_to_uint16)[name = tensor("gather_67_cast_uint16")]; tensor gather_67_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_67_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_4_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_4_cast_fp16, cond = mask0_4)[name = tensor("scores0_4_cast_fp16")]; tensor var_593_cast_fp16 = softmax(axis = var_21, x = scores0_4_cast_fp16)[name = tensor("op_593_cast_fp16")]; tensor input_29_cast_fp16 = select(a = var_8_to_fp16, b = var_593_cast_fp16, cond = mask0_4)[name = tensor("input_29_cast_fp16")]; tensor x2_4_transpose_x_0 = const()[name = tensor("x2_4_transpose_x_0"), val = tensor(false)]; tensor x2_4_transpose_y_0 = const()[name = tensor("x2_4_transpose_y_0"), val = tensor(false)]; tensor x2_4_cast_fp16 = matmul(transpose_x = x2_4_transpose_x_0, transpose_y = x2_4_transpose_y_0, x = input_29_cast_fp16, y = value_4_cast_fp16)[name = tensor("x2_4_cast_fp16")]; tensor var_597_perm_0 = const()[name = tensor("op_597_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_37_axis_0 = const()[name = tensor("concat_37_axis_0"), val = tensor(0)]; tensor concat_37_interleave_0 = const()[name = tensor("concat_37_interleave_0"), val = tensor(false)]; tensor gather_67_cast_uint16_to_int32 = cast(dtype = gather_67_cast_uint16_to_int32_dtype_0, x = gather_67_cast_uint16)[name = tensor("cast_220")]; tensor concat_37 = concat(axis = concat_37_axis_0, interleave = concat_37_interleave_0, values = (gather_67_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_37")]; tensor var_597_cast_fp16 = transpose(perm = var_597_perm_0, x = x2_4_cast_fp16)[name = tensor("transpose_466")]; tensor input0_19_cast_fp16 = reshape(shape = concat_37, x = var_597_cast_fp16)[name = tensor("input0_19_cast_fp16")]; tensor encoder_layers_1_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26224960))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26749312))), name = tensor("encoder_layers_1_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_16_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_self_attn_linear_out_weight_to_fp16_palettized, x = input0_19_cast_fp16)[name = tensor("linear_16_cast_fp16")]; tensor input0_21_cast_fp16 = add(x = input_27_cast_fp16, y = linear_16_cast_fp16)[name = tensor("input0_21_cast_fp16")]; tensor x_31_axes_0 = const()[name = tensor("x_31_axes_0"), val = tensor([-1])]; tensor encoder_layers_1_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_1_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26749440)))]; tensor encoder_layers_1_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_1_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26751552)))]; tensor x_31_cast_fp16 = layer_norm(axes = x_31_axes_0, beta = encoder_layers_1_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_1_norm_conv_weight_to_fp16, x = input0_21_cast_fp16)[name = tensor("x_31_cast_fp16")]; tensor input_31_perm_0 = const()[name = tensor("input_31_perm_0"), val = tensor([0, 2, 1])]; tensor input0_23_pad_type_0 = const()[name = tensor("input0_23_pad_type_0"), val = tensor("valid")]; tensor input0_23_strides_0 = const()[name = tensor("input0_23_strides_0"), val = tensor([1])]; tensor input0_23_pad_0 = const()[name = tensor("input0_23_pad_0"), val = tensor([0, 0])]; tensor input0_23_dilations_0 = const()[name = tensor("input0_23_dilations_0"), val = tensor([1])]; tensor input0_23_groups_0 = const()[name = tensor("input0_23_groups_0"), val = tensor(1)]; tensor encoder_layers_1_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26753664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27802304))), name = tensor("encoder_layers_1_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_31_cast_fp16 = transpose(perm = input_31_perm_0, x = x_31_cast_fp16)[name = tensor("transpose_465")]; tensor input0_23_cast_fp16 = conv(dilations = input0_23_dilations_0, groups = input0_23_groups_0, pad = input0_23_pad_0, pad_type = input0_23_pad_type_0, strides = input0_23_strides_0, weight = encoder_layers_1_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_31_cast_fp16)[name = tensor("input0_23_cast_fp16")]; tensor x_33_split_num_splits_0 = const()[name = tensor("x_33_split_num_splits_0"), val = tensor(2)]; tensor x_33_split_axis_0 = const()[name = tensor("x_33_split_axis_0"), val = tensor(1)]; tensor x_33_split_cast_fp16_0, tensor x_33_split_cast_fp16_1 = split(axis = x_33_split_axis_0, num_splits = x_33_split_num_splits_0, x = input0_23_cast_fp16)[name = tensor("x_33_split_cast_fp16")]; tensor x_33_split_1_sigmoid_cast_fp16 = sigmoid(x = x_33_split_cast_fp16_1)[name = tensor("x_33_split_1_sigmoid_cast_fp16")]; tensor x_33_cast_fp16 = mul(x = x_33_split_cast_fp16_0, y = x_33_split_1_sigmoid_cast_fp16)[name = tensor("x_33_cast_fp16")]; tensor input0_25_cast_fp16 = select(a = var_8_to_fp16, b = x_33_cast_fp16, cond = var_457)[name = tensor("input0_25_cast_fp16")]; tensor input0_27_pad_0 = const()[name = tensor("input0_27_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_27_mode_0 = const()[name = tensor("input0_27_mode_0"), val = tensor("constant")]; tensor const_14_to_fp16 = const()[name = tensor("const_14_to_fp16"), val = tensor(0x0p+0)]; tensor input0_27_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = input0_27_mode_0, pad = input0_27_pad_0, x = input0_25_cast_fp16)[name = tensor("input0_27_cast_fp16")]; tensor input1_10_pad_type_0 = const()[name = tensor("input1_10_pad_type_0"), val = tensor("valid")]; tensor input1_10_groups_0 = const()[name = tensor("input1_10_groups_0"), val = tensor(1024)]; tensor input1_10_strides_0 = const()[name = tensor("input1_10_strides_0"), val = tensor([1])]; tensor input1_10_pad_0 = const()[name = tensor("input1_10_pad_0"), val = tensor([0, 0])]; tensor input1_10_dilations_0 = const()[name = tensor("input1_10_dilations_0"), val = tensor([1])]; tensor const_61_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27802432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27807104))), name = tensor("const_61_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_62_to_fp16 = const()[name = tensor("const_62_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27807232)))]; tensor input_33_cast_fp16 = conv(bias = const_62_to_fp16, dilations = input1_10_dilations_0, groups = input1_10_groups_0, pad = input1_10_pad_0, pad_type = input1_10_pad_type_0, strides = input1_10_strides_0, weight = const_61_to_fp16_palettized, x = input0_27_cast_fp16)[name = tensor("input_33_cast_fp16")]; tensor var_635_cast_fp16 = silu(x = input_33_cast_fp16)[name = tensor("op_635_cast_fp16")]; tensor x_35_pad_type_0 = const()[name = tensor("x_35_pad_type_0"), val = tensor("valid")]; tensor x_35_strides_0 = const()[name = tensor("x_35_strides_0"), val = tensor([1])]; tensor x_35_pad_0 = const()[name = tensor("x_35_pad_0"), val = tensor([0, 0])]; tensor x_35_dilations_0 = const()[name = tensor("x_35_dilations_0"), val = tensor([1])]; tensor x_35_groups_0 = const()[name = tensor("x_35_groups_0"), val = tensor(1)]; tensor encoder_layers_1_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27809344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28333696))), name = tensor("encoder_layers_1_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_35_cast_fp16 = conv(dilations = x_35_dilations_0, groups = x_35_groups_0, pad = x_35_pad_0, pad_type = x_35_pad_type_0, strides = x_35_strides_0, weight = encoder_layers_1_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_635_cast_fp16)[name = tensor("x_35_cast_fp16")]; tensor var_642_perm_0 = const()[name = tensor("op_642_perm_0"), val = tensor([0, 2, 1])]; tensor var_642_cast_fp16 = transpose(perm = var_642_perm_0, x = x_35_cast_fp16)[name = tensor("transpose_464")]; tensor input1_12_cast_fp16 = add(x = input0_21_cast_fp16, y = var_642_cast_fp16)[name = tensor("input1_12_cast_fp16")]; tensor input0_29_axes_0 = const()[name = tensor("input0_29_axes_0"), val = tensor([-1])]; tensor encoder_layers_1_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_1_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28333824)))]; tensor encoder_layers_1_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_1_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28335936)))]; tensor input0_29_cast_fp16 = layer_norm(axes = input0_29_axes_0, beta = encoder_layers_1_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_1_norm_feed_forward2_weight_to_fp16, x = input1_12_cast_fp16)[name = tensor("input0_29_cast_fp16")]; tensor encoder_layers_1_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28338048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30435264))), name = tensor("encoder_layers_1_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_17_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_1_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_29_cast_fp16)[name = tensor("linear_17_cast_fp16")]; tensor var_653_cast_fp16 = silu(x = linear_17_cast_fp16)[name = tensor("op_653_cast_fp16")]; tensor encoder_layers_1_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30435392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32532608))), name = tensor("encoder_layers_1_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_18_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_1_feed_forward2_linear2_weight_to_fp16_palettized, x = var_653_cast_fp16)[name = tensor("linear_18_cast_fp16")]; tensor var_658_to_fp16 = const()[name = tensor("op_658_to_fp16"), val = tensor(0x1p-1)]; tensor var_659_cast_fp16 = mul(x = linear_18_cast_fp16, y = var_658_to_fp16)[name = tensor("op_659_cast_fp16")]; tensor input2_6_cast_fp16 = add(x = input1_12_cast_fp16, y = var_659_cast_fp16)[name = tensor("input2_6_cast_fp16")]; tensor input0_31_axes_0 = const()[name = tensor("input0_31_axes_0"), val = tensor([-1])]; tensor encoder_layers_1_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_1_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32532736)))]; tensor encoder_layers_1_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_1_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32534848)))]; tensor input0_31_cast_fp16 = layer_norm(axes = input0_31_axes_0, beta = encoder_layers_1_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_1_norm_out_weight_to_fp16, x = input2_6_cast_fp16)[name = tensor("input0_31_cast_fp16")]; tensor input_37_axes_0 = const()[name = tensor("input_37_axes_0"), val = tensor([-1])]; tensor encoder_layers_2_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_2_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32536960)))]; tensor encoder_layers_2_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_2_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32539072)))]; tensor input_37_cast_fp16 = layer_norm(axes = input_37_axes_0, beta = encoder_layers_2_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_2_norm_feed_forward1_weight_to_fp16, x = input0_31_cast_fp16)[name = tensor("input_37_cast_fp16")]; tensor encoder_layers_2_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32541184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34638400))), name = tensor("encoder_layers_2_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_19_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_2_feed_forward1_linear1_weight_to_fp16_palettized, x = input_37_cast_fp16)[name = tensor("linear_19_cast_fp16")]; tensor var_682_cast_fp16 = silu(x = linear_19_cast_fp16)[name = tensor("op_682_cast_fp16")]; tensor encoder_layers_2_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34638528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36735744))), name = tensor("encoder_layers_2_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_20_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_feed_forward1_linear2_weight_to_fp16_palettized, x = var_682_cast_fp16)[name = tensor("linear_20_cast_fp16")]; tensor var_687_to_fp16 = const()[name = tensor("op_687_to_fp16"), val = tensor(0x1p-1)]; tensor var_688_cast_fp16 = mul(x = linear_20_cast_fp16, y = var_687_to_fp16)[name = tensor("op_688_cast_fp16")]; tensor input_41_cast_fp16 = add(x = input0_31_cast_fp16, y = var_688_cast_fp16)[name = tensor("input_41_cast_fp16")]; tensor query_6_axes_0 = const()[name = tensor("query_6_axes_0"), val = tensor([-1])]; tensor encoder_layers_2_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_2_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36735872)))]; tensor encoder_layers_2_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_2_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36737984)))]; tensor query_6_cast_fp16 = layer_norm(axes = query_6_axes_0, beta = encoder_layers_2_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_2_norm_self_att_weight_to_fp16, x = input_41_cast_fp16)[name = tensor("query_6_cast_fp16")]; tensor var_701_shape_cast_fp16 = shape(x = query_6_cast_fp16)[name = tensor("op_701_shape_cast_fp16")]; tensor gather_68_axis_0 = const()[name = tensor("gather_68_axis_0"), val = tensor(0)]; tensor gather_68_batch_dims_0 = const()[name = tensor("gather_68_batch_dims_0"), val = tensor(0)]; tensor gather_68_validate_indices_0 = const()[name = tensor("gather_68_validate_indices_0"), val = tensor(false)]; tensor var_701_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_701_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_68_to_uint16 = const()[name = tensor("select_68_to_uint16"), val = tensor(0)]; tensor var_701_shape_cast_fp16_to_uint16 = cast(dtype = var_701_shape_cast_fp16_to_uint16_dtype_0, x = var_701_shape_cast_fp16)[name = tensor("cast_219")]; tensor gather_68_cast_uint16 = gather(axis = gather_68_axis_0, batch_dims = gather_68_batch_dims_0, indices = select_68_to_uint16, validate_indices = gather_68_validate_indices_0, x = var_701_shape_cast_fp16_to_uint16)[name = tensor("gather_68_cast_uint16")]; tensor gather_68_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_68_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_2_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36740096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37264448))), name = tensor("encoder_layers_2_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_21_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_self_attn_linear_q_weight_to_fp16_palettized, x = query_6_cast_fp16)[name = tensor("linear_21_cast_fp16")]; tensor concat_38_axis_0 = const()[name = tensor("concat_38_axis_0"), val = tensor(0)]; tensor concat_38_interleave_0 = const()[name = tensor("concat_38_interleave_0"), val = tensor(false)]; tensor gather_68_cast_uint16_to_int32 = cast(dtype = gather_68_cast_uint16_to_int32_dtype_0, x = gather_68_cast_uint16)[name = tensor("cast_218")]; tensor concat_38 = concat(axis = concat_38_axis_0, interleave = concat_38_interleave_0, values = (gather_68_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_38")]; tensor q_6_cast_fp16 = reshape(shape = concat_38, x = linear_21_cast_fp16)[name = tensor("q_6_cast_fp16")]; tensor encoder_layers_2_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37264576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37788928))), name = tensor("encoder_layers_2_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_22_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_self_attn_linear_k_weight_to_fp16_palettized, x = query_6_cast_fp16)[name = tensor("linear_22_cast_fp16")]; tensor k_6_cast_fp16 = reshape(shape = concat_38, x = linear_22_cast_fp16)[name = tensor("k_6_cast_fp16")]; tensor encoder_layers_2_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37789056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38313408))), name = tensor("encoder_layers_2_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_23_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_self_attn_linear_v_weight_to_fp16_palettized, x = query_6_cast_fp16)[name = tensor("linear_23_cast_fp16")]; tensor v_6_cast_fp16 = reshape(shape = concat_38, x = linear_23_cast_fp16)[name = tensor("v_6_cast_fp16")]; tensor value_6_perm_0 = const()[name = tensor("value_6_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_2_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38313536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38837888))), name = tensor("encoder_layers_2_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_24_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_24_cast_fp16")]; tensor var_721 = const()[name = tensor("op_721"), val = tensor([1, -1, 8, 128])]; tensor p_6_cast_fp16 = reshape(shape = var_721, x = linear_24_cast_fp16)[name = tensor("p_6_cast_fp16")]; tensor encoder_layers_2_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_2_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38838016)))]; tensor var_724_cast_fp16 = add(x = q_6_cast_fp16, y = encoder_layers_2_self_attn_pos_bias_u_to_fp16)[name = tensor("op_724_cast_fp16")]; tensor encoder_layers_2_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_2_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38840128)))]; tensor var_726_cast_fp16 = add(x = q_6_cast_fp16, y = encoder_layers_2_self_attn_pos_bias_v_to_fp16)[name = tensor("op_726_cast_fp16")]; tensor x_43_transpose_x_0 = const()[name = tensor("x_43_transpose_x_0"), val = tensor(false)]; tensor x_43_transpose_y_0 = const()[name = tensor("x_43_transpose_y_0"), val = tensor(false)]; tensor transpose_200_perm_0 = const()[name = tensor("transpose_200_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_201_perm_0 = const()[name = tensor("transpose_201_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_201 = transpose(perm = transpose_201_perm_0, x = p_6_cast_fp16)[name = tensor("transpose_462")]; tensor transpose_200 = transpose(perm = transpose_200_perm_0, x = var_726_cast_fp16)[name = tensor("transpose_463")]; tensor x_43_cast_fp16 = matmul(transpose_x = x_43_transpose_x_0, transpose_y = x_43_transpose_y_0, x = transpose_200, y = transpose_201)[name = tensor("x_43_cast_fp16")]; tensor var_730_shape_cast_fp16 = shape(x = x_43_cast_fp16)[name = tensor("op_730_shape_cast_fp16")]; tensor gather_70_axis_0 = const()[name = tensor("gather_70_axis_0"), val = tensor(0)]; tensor gather_70_batch_dims_0 = const()[name = tensor("gather_70_batch_dims_0"), val = tensor(0)]; tensor gather_70_validate_indices_0 = const()[name = tensor("gather_70_validate_indices_0"), val = tensor(false)]; tensor var_730_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_730_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_70_to_uint16 = const()[name = tensor("select_70_to_uint16"), val = tensor(0)]; tensor var_730_shape_cast_fp16_to_uint16 = cast(dtype = var_730_shape_cast_fp16_to_uint16_dtype_0, x = var_730_shape_cast_fp16)[name = tensor("cast_217")]; tensor gather_70_cast_uint16 = gather(axis = gather_70_axis_0, batch_dims = gather_70_batch_dims_0, indices = select_70_to_uint16, validate_indices = gather_70_validate_indices_0, x = var_730_shape_cast_fp16_to_uint16)[name = tensor("gather_70_cast_uint16")]; tensor gather_70_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_70_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_71 = const()[name = tensor("gather_71"), val = tensor(8)]; tensor gather_72_axis_0 = const()[name = tensor("gather_72_axis_0"), val = tensor(0)]; tensor gather_72_batch_dims_0 = const()[name = tensor("gather_72_batch_dims_0"), val = tensor(0)]; tensor gather_72_validate_indices_0 = const()[name = tensor("gather_72_validate_indices_0"), val = tensor(false)]; tensor select_72_to_uint16 = const()[name = tensor("select_72_to_uint16"), val = tensor(2)]; tensor gather_72_cast_uint16 = gather(axis = gather_72_axis_0, batch_dims = gather_72_batch_dims_0, indices = select_72_to_uint16, validate_indices = gather_72_validate_indices_0, x = var_730_shape_cast_fp16_to_uint16)[name = tensor("gather_72_cast_uint16")]; tensor gather_72_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_72_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_73_axis_0 = const()[name = tensor("gather_73_axis_0"), val = tensor(0)]; tensor gather_73_batch_dims_0 = const()[name = tensor("gather_73_batch_dims_0"), val = tensor(0)]; tensor gather_73_validate_indices_0 = const()[name = tensor("gather_73_validate_indices_0"), val = tensor(false)]; tensor select_73_to_uint16 = const()[name = tensor("select_73_to_uint16"), val = tensor(3)]; tensor gather_73_cast_uint16 = gather(axis = gather_73_axis_0, batch_dims = gather_73_batch_dims_0, indices = select_73_to_uint16, validate_indices = gather_73_validate_indices_0, x = var_730_shape_cast_fp16_to_uint16)[name = tensor("gather_73_cast_uint16")]; tensor gather_73_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_73_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_8_pad_0 = const()[name = tensor("x0_8_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_8_mode_0 = const()[name = tensor("x0_8_mode_0"), val = tensor("constant")]; tensor const_15_to_fp16 = const()[name = tensor("const_15_to_fp16"), val = tensor(0x0p+0)]; tensor x0_8_cast_fp16 = pad(constant_val = const_15_to_fp16, mode = x0_8_mode_0, pad = x0_8_pad_0, x = x_43_cast_fp16)[name = tensor("x0_8_cast_fp16")]; tensor concat_41_axis_0 = const()[name = tensor("concat_41_axis_0"), val = tensor(0)]; tensor concat_41_interleave_0 = const()[name = tensor("concat_41_interleave_0"), val = tensor(false)]; tensor gather_70_cast_uint16_to_int32 = cast(dtype = gather_70_cast_uint16_to_int32_dtype_0, x = gather_70_cast_uint16)[name = tensor("cast_215")]; tensor gather_72_cast_uint16_to_int32 = cast(dtype = gather_72_cast_uint16_to_int32_dtype_0, x = gather_72_cast_uint16)[name = tensor("cast_216")]; tensor concat_41 = concat(axis = concat_41_axis_0, interleave = concat_41_interleave_0, values = (gather_70_cast_uint16_to_int32, gather_71, var_21, gather_72_cast_uint16_to_int32))[name = tensor("concat_41")]; tensor x1_6_cast_fp16 = reshape(shape = concat_41, x = x0_8_cast_fp16)[name = tensor("x1_6_cast_fp16")]; tensor var_740_begin_0 = const()[name = tensor("op_740_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_740_end_0 = const()[name = tensor("op_740_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_740_end_mask_0 = const()[name = tensor("op_740_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_740_cast_fp16 = slice_by_index(begin = var_740_begin_0, end = var_740_end_0, end_mask = var_740_end_mask_0, x = x1_6_cast_fp16)[name = tensor("op_740_cast_fp16")]; tensor concat_42_axis_0 = const()[name = tensor("concat_42_axis_0"), val = tensor(0)]; tensor concat_42_interleave_0 = const()[name = tensor("concat_42_interleave_0"), val = tensor(false)]; tensor gather_73_cast_uint16_to_int32 = cast(dtype = gather_73_cast_uint16_to_int32_dtype_0, x = gather_73_cast_uint16)[name = tensor("cast_214")]; tensor concat_42 = concat(axis = concat_42_axis_0, interleave = concat_42_interleave_0, values = (gather_70_cast_uint16_to_int32, gather_71, gather_72_cast_uint16_to_int32, gather_73_cast_uint16_to_int32))[name = tensor("concat_42")]; tensor matrix_bd_6_cast_fp16 = reshape(shape = concat_42, x = var_740_cast_fp16)[name = tensor("matrix_bd_6_cast_fp16")]; tensor matrix_ac_6_transpose_x_0 = const()[name = tensor("matrix_ac_6_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_6_transpose_y_0 = const()[name = tensor("matrix_ac_6_transpose_y_0"), val = tensor(false)]; tensor transpose_202_perm_0 = const()[name = tensor("transpose_202_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_203_perm_0 = const()[name = tensor("transpose_203_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_203 = transpose(perm = transpose_203_perm_0, x = k_6_cast_fp16)[name = tensor("transpose_460")]; tensor transpose_202 = transpose(perm = transpose_202_perm_0, x = var_724_cast_fp16)[name = tensor("transpose_461")]; tensor matrix_ac_6_cast_fp16 = matmul(transpose_x = matrix_ac_6_transpose_x_0, transpose_y = matrix_ac_6_transpose_y_0, x = transpose_202, y = transpose_203)[name = tensor("matrix_ac_6_cast_fp16")]; tensor var_745_shape_cast_fp16 = shape(x = matrix_ac_6_cast_fp16)[name = tensor("op_745_shape_cast_fp16")]; tensor gather_74_axis_0 = const()[name = tensor("gather_74_axis_0"), val = tensor(0)]; tensor gather_74_batch_dims_0 = const()[name = tensor("gather_74_batch_dims_0"), val = tensor(0)]; tensor gather_74_validate_indices_0 = const()[name = tensor("gather_74_validate_indices_0"), val = tensor(false)]; tensor var_745_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_745_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_74_to_uint16 = const()[name = tensor("select_74_to_uint16"), val = tensor(3)]; tensor var_745_shape_cast_fp16_to_uint16 = cast(dtype = var_745_shape_cast_fp16_to_uint16_dtype_0, x = var_745_shape_cast_fp16)[name = tensor("cast_213")]; tensor gather_74_cast_uint16 = gather(axis = gather_74_axis_0, batch_dims = gather_74_batch_dims_0, indices = select_74_to_uint16, validate_indices = gather_74_validate_indices_0, x = var_745_shape_cast_fp16_to_uint16)[name = tensor("gather_74_cast_uint16")]; tensor gather_74_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_74_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_43_values0_0 = const()[name = tensor("concat_43_values0_0"), val = tensor(0)]; tensor concat_43_values1_0 = const()[name = tensor("concat_43_values1_0"), val = tensor(8)]; tensor concat_43_values2_0 = const()[name = tensor("concat_43_values2_0"), val = tensor(0)]; tensor concat_43_axis_0 = const()[name = tensor("concat_43_axis_0"), val = tensor(0)]; tensor concat_43_interleave_0 = const()[name = tensor("concat_43_interleave_0"), val = tensor(false)]; tensor gather_74_cast_uint16_to_int32 = cast(dtype = gather_74_cast_uint16_to_int32_dtype_0, x = gather_74_cast_uint16)[name = tensor("cast_212")]; tensor concat_43 = concat(axis = concat_43_axis_0, interleave = concat_43_interleave_0, values = (concat_43_values0_0, concat_43_values1_0, concat_43_values2_0, gather_74_cast_uint16_to_int32))[name = tensor("concat_43")]; tensor matrix_bd0_6_begin_0 = const()[name = tensor("matrix_bd0_6_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_6_end_mask_0 = const()[name = tensor("matrix_bd0_6_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_6_cast_fp16 = slice_by_index(begin = matrix_bd0_6_begin_0, end = concat_43, end_mask = matrix_bd0_6_end_mask_0, x = matrix_bd_6_cast_fp16)[name = tensor("matrix_bd0_6_cast_fp16")]; tensor var_750_cast_fp16 = add(x = matrix_ac_6_cast_fp16, y = matrix_bd0_6_cast_fp16)[name = tensor("op_750_cast_fp16")]; tensor _inversed_scores_6_y_0_to_fp16 = const()[name = tensor("_inversed_scores_6_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_6_cast_fp16 = mul(x = var_750_cast_fp16, y = _inversed_scores_6_y_0_to_fp16)[name = tensor("_inversed_scores_6_cast_fp16")]; tensor value_6_cast_fp16 = transpose(perm = value_6_perm_0, x = v_6_cast_fp16)[name = tensor("transpose_459")]; tensor var_753_shape_cast_fp16 = shape(x = value_6_cast_fp16)[name = tensor("op_753_shape_cast_fp16")]; tensor gather_75_axis_0 = const()[name = tensor("gather_75_axis_0"), val = tensor(0)]; tensor gather_75_batch_dims_0 = const()[name = tensor("gather_75_batch_dims_0"), val = tensor(0)]; tensor gather_75_validate_indices_0 = const()[name = tensor("gather_75_validate_indices_0"), val = tensor(false)]; tensor var_753_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_753_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_75_to_uint16 = const()[name = tensor("select_75_to_uint16"), val = tensor(0)]; tensor var_753_shape_cast_fp16_to_uint16 = cast(dtype = var_753_shape_cast_fp16_to_uint16_dtype_0, x = var_753_shape_cast_fp16)[name = tensor("cast_211")]; tensor gather_75_cast_uint16 = gather(axis = gather_75_axis_0, batch_dims = gather_75_batch_dims_0, indices = select_75_to_uint16, validate_indices = gather_75_validate_indices_0, x = var_753_shape_cast_fp16_to_uint16)[name = tensor("gather_75_cast_uint16")]; tensor gather_75_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_75_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_6_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_6_cast_fp16, cond = mask0_4)[name = tensor("scores0_6_cast_fp16")]; tensor var_756_cast_fp16 = softmax(axis = var_21, x = scores0_6_cast_fp16)[name = tensor("op_756_cast_fp16")]; tensor input_43_cast_fp16 = select(a = var_8_to_fp16, b = var_756_cast_fp16, cond = mask0_4)[name = tensor("input_43_cast_fp16")]; tensor x2_6_transpose_x_0 = const()[name = tensor("x2_6_transpose_x_0"), val = tensor(false)]; tensor x2_6_transpose_y_0 = const()[name = tensor("x2_6_transpose_y_0"), val = tensor(false)]; tensor x2_6_cast_fp16 = matmul(transpose_x = x2_6_transpose_x_0, transpose_y = x2_6_transpose_y_0, x = input_43_cast_fp16, y = value_6_cast_fp16)[name = tensor("x2_6_cast_fp16")]; tensor var_760_perm_0 = const()[name = tensor("op_760_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_44_axis_0 = const()[name = tensor("concat_44_axis_0"), val = tensor(0)]; tensor concat_44_interleave_0 = const()[name = tensor("concat_44_interleave_0"), val = tensor(false)]; tensor gather_75_cast_uint16_to_int32 = cast(dtype = gather_75_cast_uint16_to_int32_dtype_0, x = gather_75_cast_uint16)[name = tensor("cast_210")]; tensor concat_44 = concat(axis = concat_44_axis_0, interleave = concat_44_interleave_0, values = (gather_75_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_44")]; tensor var_760_cast_fp16 = transpose(perm = var_760_perm_0, x = x2_6_cast_fp16)[name = tensor("transpose_458")]; tensor input0_33_cast_fp16 = reshape(shape = concat_44, x = var_760_cast_fp16)[name = tensor("input0_33_cast_fp16")]; tensor encoder_layers_2_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38842240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39366592))), name = tensor("encoder_layers_2_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_25_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_self_attn_linear_out_weight_to_fp16_palettized, x = input0_33_cast_fp16)[name = tensor("linear_25_cast_fp16")]; tensor input0_35_cast_fp16 = add(x = input_41_cast_fp16, y = linear_25_cast_fp16)[name = tensor("input0_35_cast_fp16")]; tensor x_47_axes_0 = const()[name = tensor("x_47_axes_0"), val = tensor([-1])]; tensor encoder_layers_2_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_2_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39366720)))]; tensor encoder_layers_2_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_2_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39368832)))]; tensor x_47_cast_fp16 = layer_norm(axes = x_47_axes_0, beta = encoder_layers_2_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_2_norm_conv_weight_to_fp16, x = input0_35_cast_fp16)[name = tensor("x_47_cast_fp16")]; tensor input_45_perm_0 = const()[name = tensor("input_45_perm_0"), val = tensor([0, 2, 1])]; tensor input0_37_pad_type_0 = const()[name = tensor("input0_37_pad_type_0"), val = tensor("valid")]; tensor input0_37_strides_0 = const()[name = tensor("input0_37_strides_0"), val = tensor([1])]; tensor input0_37_pad_0 = const()[name = tensor("input0_37_pad_0"), val = tensor([0, 0])]; tensor input0_37_dilations_0 = const()[name = tensor("input0_37_dilations_0"), val = tensor([1])]; tensor input0_37_groups_0 = const()[name = tensor("input0_37_groups_0"), val = tensor(1)]; tensor encoder_layers_2_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39370944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40419584))), name = tensor("encoder_layers_2_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_45_cast_fp16 = transpose(perm = input_45_perm_0, x = x_47_cast_fp16)[name = tensor("transpose_457")]; tensor input0_37_cast_fp16 = conv(dilations = input0_37_dilations_0, groups = input0_37_groups_0, pad = input0_37_pad_0, pad_type = input0_37_pad_type_0, strides = input0_37_strides_0, weight = encoder_layers_2_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_45_cast_fp16)[name = tensor("input0_37_cast_fp16")]; tensor x_49_split_num_splits_0 = const()[name = tensor("x_49_split_num_splits_0"), val = tensor(2)]; tensor x_49_split_axis_0 = const()[name = tensor("x_49_split_axis_0"), val = tensor(1)]; tensor x_49_split_cast_fp16_0, tensor x_49_split_cast_fp16_1 = split(axis = x_49_split_axis_0, num_splits = x_49_split_num_splits_0, x = input0_37_cast_fp16)[name = tensor("x_49_split_cast_fp16")]; tensor x_49_split_1_sigmoid_cast_fp16 = sigmoid(x = x_49_split_cast_fp16_1)[name = tensor("x_49_split_1_sigmoid_cast_fp16")]; tensor x_49_cast_fp16 = mul(x = x_49_split_cast_fp16_0, y = x_49_split_1_sigmoid_cast_fp16)[name = tensor("x_49_cast_fp16")]; tensor input0_39_cast_fp16 = select(a = var_8_to_fp16, b = x_49_cast_fp16, cond = var_457)[name = tensor("input0_39_cast_fp16")]; tensor input0_41_pad_0 = const()[name = tensor("input0_41_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_41_mode_0 = const()[name = tensor("input0_41_mode_0"), val = tensor("constant")]; tensor const_16_to_fp16 = const()[name = tensor("const_16_to_fp16"), val = tensor(0x0p+0)]; tensor input0_41_cast_fp16 = pad(constant_val = const_16_to_fp16, mode = input0_41_mode_0, pad = input0_41_pad_0, x = input0_39_cast_fp16)[name = tensor("input0_41_cast_fp16")]; tensor input1_14_pad_type_0 = const()[name = tensor("input1_14_pad_type_0"), val = tensor("valid")]; tensor input1_14_groups_0 = const()[name = tensor("input1_14_groups_0"), val = tensor(1024)]; tensor input1_14_strides_0 = const()[name = tensor("input1_14_strides_0"), val = tensor([1])]; tensor input1_14_pad_0 = const()[name = tensor("input1_14_pad_0"), val = tensor([0, 0])]; tensor input1_14_dilations_0 = const()[name = tensor("input1_14_dilations_0"), val = tensor([1])]; tensor const_63_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40419712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40424384))), name = tensor("const_63_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_64_to_fp16 = const()[name = tensor("const_64_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40424512)))]; tensor input_47_cast_fp16 = conv(bias = const_64_to_fp16, dilations = input1_14_dilations_0, groups = input1_14_groups_0, pad = input1_14_pad_0, pad_type = input1_14_pad_type_0, strides = input1_14_strides_0, weight = const_63_to_fp16_palettized, x = input0_41_cast_fp16)[name = tensor("input_47_cast_fp16")]; tensor var_798_cast_fp16 = silu(x = input_47_cast_fp16)[name = tensor("op_798_cast_fp16")]; tensor x_51_pad_type_0 = const()[name = tensor("x_51_pad_type_0"), val = tensor("valid")]; tensor x_51_strides_0 = const()[name = tensor("x_51_strides_0"), val = tensor([1])]; tensor x_51_pad_0 = const()[name = tensor("x_51_pad_0"), val = tensor([0, 0])]; tensor x_51_dilations_0 = const()[name = tensor("x_51_dilations_0"), val = tensor([1])]; tensor x_51_groups_0 = const()[name = tensor("x_51_groups_0"), val = tensor(1)]; tensor encoder_layers_2_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40426624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40950976))), name = tensor("encoder_layers_2_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_51_cast_fp16 = conv(dilations = x_51_dilations_0, groups = x_51_groups_0, pad = x_51_pad_0, pad_type = x_51_pad_type_0, strides = x_51_strides_0, weight = encoder_layers_2_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_798_cast_fp16)[name = tensor("x_51_cast_fp16")]; tensor var_805_perm_0 = const()[name = tensor("op_805_perm_0"), val = tensor([0, 2, 1])]; tensor var_805_cast_fp16 = transpose(perm = var_805_perm_0, x = x_51_cast_fp16)[name = tensor("transpose_456")]; tensor input1_16_cast_fp16 = add(x = input0_35_cast_fp16, y = var_805_cast_fp16)[name = tensor("input1_16_cast_fp16")]; tensor input0_43_axes_0 = const()[name = tensor("input0_43_axes_0"), val = tensor([-1])]; tensor encoder_layers_2_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_2_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40951104)))]; tensor encoder_layers_2_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_2_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40953216)))]; tensor input0_43_cast_fp16 = layer_norm(axes = input0_43_axes_0, beta = encoder_layers_2_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_2_norm_feed_forward2_weight_to_fp16, x = input1_16_cast_fp16)[name = tensor("input0_43_cast_fp16")]; tensor encoder_layers_2_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40955328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43052544))), name = tensor("encoder_layers_2_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_26_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_2_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_43_cast_fp16)[name = tensor("linear_26_cast_fp16")]; tensor var_816_cast_fp16 = silu(x = linear_26_cast_fp16)[name = tensor("op_816_cast_fp16")]; tensor encoder_layers_2_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43052672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45149888))), name = tensor("encoder_layers_2_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_27_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_2_feed_forward2_linear2_weight_to_fp16_palettized, x = var_816_cast_fp16)[name = tensor("linear_27_cast_fp16")]; tensor var_821_to_fp16 = const()[name = tensor("op_821_to_fp16"), val = tensor(0x1p-1)]; tensor var_822_cast_fp16 = mul(x = linear_27_cast_fp16, y = var_821_to_fp16)[name = tensor("op_822_cast_fp16")]; tensor input2_8_cast_fp16 = add(x = input1_16_cast_fp16, y = var_822_cast_fp16)[name = tensor("input2_8_cast_fp16")]; tensor input0_45_axes_0 = const()[name = tensor("input0_45_axes_0"), val = tensor([-1])]; tensor encoder_layers_2_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_2_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45150016)))]; tensor encoder_layers_2_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_2_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45152128)))]; tensor input0_45_cast_fp16 = layer_norm(axes = input0_45_axes_0, beta = encoder_layers_2_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_2_norm_out_weight_to_fp16, x = input2_8_cast_fp16)[name = tensor("input0_45_cast_fp16")]; tensor input_51_axes_0 = const()[name = tensor("input_51_axes_0"), val = tensor([-1])]; tensor encoder_layers_3_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_3_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45154240)))]; tensor encoder_layers_3_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_3_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45156352)))]; tensor input_51_cast_fp16 = layer_norm(axes = input_51_axes_0, beta = encoder_layers_3_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_3_norm_feed_forward1_weight_to_fp16, x = input0_45_cast_fp16)[name = tensor("input_51_cast_fp16")]; tensor encoder_layers_3_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45158464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47255680))), name = tensor("encoder_layers_3_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_28_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_3_feed_forward1_linear1_weight_to_fp16_palettized, x = input_51_cast_fp16)[name = tensor("linear_28_cast_fp16")]; tensor var_845_cast_fp16 = silu(x = linear_28_cast_fp16)[name = tensor("op_845_cast_fp16")]; tensor encoder_layers_3_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47255808))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49353024))), name = tensor("encoder_layers_3_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_29_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_feed_forward1_linear2_weight_to_fp16_palettized, x = var_845_cast_fp16)[name = tensor("linear_29_cast_fp16")]; tensor var_850_to_fp16 = const()[name = tensor("op_850_to_fp16"), val = tensor(0x1p-1)]; tensor var_851_cast_fp16 = mul(x = linear_29_cast_fp16, y = var_850_to_fp16)[name = tensor("op_851_cast_fp16")]; tensor input_55_cast_fp16 = add(x = input0_45_cast_fp16, y = var_851_cast_fp16)[name = tensor("input_55_cast_fp16")]; tensor query_8_axes_0 = const()[name = tensor("query_8_axes_0"), val = tensor([-1])]; tensor encoder_layers_3_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_3_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49353152)))]; tensor encoder_layers_3_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_3_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49355264)))]; tensor query_8_cast_fp16 = layer_norm(axes = query_8_axes_0, beta = encoder_layers_3_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_3_norm_self_att_weight_to_fp16, x = input_55_cast_fp16)[name = tensor("query_8_cast_fp16")]; tensor var_864_shape_cast_fp16 = shape(x = query_8_cast_fp16)[name = tensor("op_864_shape_cast_fp16")]; tensor gather_76_axis_0 = const()[name = tensor("gather_76_axis_0"), val = tensor(0)]; tensor gather_76_batch_dims_0 = const()[name = tensor("gather_76_batch_dims_0"), val = tensor(0)]; tensor gather_76_validate_indices_0 = const()[name = tensor("gather_76_validate_indices_0"), val = tensor(false)]; tensor var_864_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_864_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_76_to_uint16 = const()[name = tensor("select_76_to_uint16"), val = tensor(0)]; tensor var_864_shape_cast_fp16_to_uint16 = cast(dtype = var_864_shape_cast_fp16_to_uint16_dtype_0, x = var_864_shape_cast_fp16)[name = tensor("cast_209")]; tensor gather_76_cast_uint16 = gather(axis = gather_76_axis_0, batch_dims = gather_76_batch_dims_0, indices = select_76_to_uint16, validate_indices = gather_76_validate_indices_0, x = var_864_shape_cast_fp16_to_uint16)[name = tensor("gather_76_cast_uint16")]; tensor gather_76_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_76_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_3_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49357376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49881728))), name = tensor("encoder_layers_3_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_30_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_self_attn_linear_q_weight_to_fp16_palettized, x = query_8_cast_fp16)[name = tensor("linear_30_cast_fp16")]; tensor concat_45_axis_0 = const()[name = tensor("concat_45_axis_0"), val = tensor(0)]; tensor concat_45_interleave_0 = const()[name = tensor("concat_45_interleave_0"), val = tensor(false)]; tensor gather_76_cast_uint16_to_int32 = cast(dtype = gather_76_cast_uint16_to_int32_dtype_0, x = gather_76_cast_uint16)[name = tensor("cast_208")]; tensor concat_45 = concat(axis = concat_45_axis_0, interleave = concat_45_interleave_0, values = (gather_76_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_45")]; tensor q_8_cast_fp16 = reshape(shape = concat_45, x = linear_30_cast_fp16)[name = tensor("q_8_cast_fp16")]; tensor encoder_layers_3_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49881856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50406208))), name = tensor("encoder_layers_3_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_31_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_self_attn_linear_k_weight_to_fp16_palettized, x = query_8_cast_fp16)[name = tensor("linear_31_cast_fp16")]; tensor k_8_cast_fp16 = reshape(shape = concat_45, x = linear_31_cast_fp16)[name = tensor("k_8_cast_fp16")]; tensor encoder_layers_3_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50406336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50930688))), name = tensor("encoder_layers_3_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_32_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_self_attn_linear_v_weight_to_fp16_palettized, x = query_8_cast_fp16)[name = tensor("linear_32_cast_fp16")]; tensor v_8_cast_fp16 = reshape(shape = concat_45, x = linear_32_cast_fp16)[name = tensor("v_8_cast_fp16")]; tensor value_8_perm_0 = const()[name = tensor("value_8_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_3_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50930816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51455168))), name = tensor("encoder_layers_3_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_33_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_33_cast_fp16")]; tensor var_884 = const()[name = tensor("op_884"), val = tensor([1, -1, 8, 128])]; tensor p_8_cast_fp16 = reshape(shape = var_884, x = linear_33_cast_fp16)[name = tensor("p_8_cast_fp16")]; tensor encoder_layers_3_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_3_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51455296)))]; tensor var_887_cast_fp16 = add(x = q_8_cast_fp16, y = encoder_layers_3_self_attn_pos_bias_u_to_fp16)[name = tensor("op_887_cast_fp16")]; tensor encoder_layers_3_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_3_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51457408)))]; tensor var_889_cast_fp16 = add(x = q_8_cast_fp16, y = encoder_layers_3_self_attn_pos_bias_v_to_fp16)[name = tensor("op_889_cast_fp16")]; tensor x_59_transpose_x_0 = const()[name = tensor("x_59_transpose_x_0"), val = tensor(false)]; tensor x_59_transpose_y_0 = const()[name = tensor("x_59_transpose_y_0"), val = tensor(false)]; tensor transpose_204_perm_0 = const()[name = tensor("transpose_204_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_205_perm_0 = const()[name = tensor("transpose_205_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_205 = transpose(perm = transpose_205_perm_0, x = p_8_cast_fp16)[name = tensor("transpose_454")]; tensor transpose_204 = transpose(perm = transpose_204_perm_0, x = var_889_cast_fp16)[name = tensor("transpose_455")]; tensor x_59_cast_fp16 = matmul(transpose_x = x_59_transpose_x_0, transpose_y = x_59_transpose_y_0, x = transpose_204, y = transpose_205)[name = tensor("x_59_cast_fp16")]; tensor var_893_shape_cast_fp16 = shape(x = x_59_cast_fp16)[name = tensor("op_893_shape_cast_fp16")]; tensor gather_78_axis_0 = const()[name = tensor("gather_78_axis_0"), val = tensor(0)]; tensor gather_78_batch_dims_0 = const()[name = tensor("gather_78_batch_dims_0"), val = tensor(0)]; tensor gather_78_validate_indices_0 = const()[name = tensor("gather_78_validate_indices_0"), val = tensor(false)]; tensor var_893_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_893_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_78_to_uint16 = const()[name = tensor("select_78_to_uint16"), val = tensor(0)]; tensor var_893_shape_cast_fp16_to_uint16 = cast(dtype = var_893_shape_cast_fp16_to_uint16_dtype_0, x = var_893_shape_cast_fp16)[name = tensor("cast_207")]; tensor gather_78_cast_uint16 = gather(axis = gather_78_axis_0, batch_dims = gather_78_batch_dims_0, indices = select_78_to_uint16, validate_indices = gather_78_validate_indices_0, x = var_893_shape_cast_fp16_to_uint16)[name = tensor("gather_78_cast_uint16")]; tensor gather_78_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_78_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_79 = const()[name = tensor("gather_79"), val = tensor(8)]; tensor gather_80_axis_0 = const()[name = tensor("gather_80_axis_0"), val = tensor(0)]; tensor gather_80_batch_dims_0 = const()[name = tensor("gather_80_batch_dims_0"), val = tensor(0)]; tensor gather_80_validate_indices_0 = const()[name = tensor("gather_80_validate_indices_0"), val = tensor(false)]; tensor select_80_to_uint16 = const()[name = tensor("select_80_to_uint16"), val = tensor(2)]; tensor gather_80_cast_uint16 = gather(axis = gather_80_axis_0, batch_dims = gather_80_batch_dims_0, indices = select_80_to_uint16, validate_indices = gather_80_validate_indices_0, x = var_893_shape_cast_fp16_to_uint16)[name = tensor("gather_80_cast_uint16")]; tensor gather_80_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_80_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_81_axis_0 = const()[name = tensor("gather_81_axis_0"), val = tensor(0)]; tensor gather_81_batch_dims_0 = const()[name = tensor("gather_81_batch_dims_0"), val = tensor(0)]; tensor gather_81_validate_indices_0 = const()[name = tensor("gather_81_validate_indices_0"), val = tensor(false)]; tensor select_81_to_uint16 = const()[name = tensor("select_81_to_uint16"), val = tensor(3)]; tensor gather_81_cast_uint16 = gather(axis = gather_81_axis_0, batch_dims = gather_81_batch_dims_0, indices = select_81_to_uint16, validate_indices = gather_81_validate_indices_0, x = var_893_shape_cast_fp16_to_uint16)[name = tensor("gather_81_cast_uint16")]; tensor gather_81_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_81_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_10_pad_0 = const()[name = tensor("x0_10_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_10_mode_0 = const()[name = tensor("x0_10_mode_0"), val = tensor("constant")]; tensor const_17_to_fp16 = const()[name = tensor("const_17_to_fp16"), val = tensor(0x0p+0)]; tensor x0_10_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = x0_10_mode_0, pad = x0_10_pad_0, x = x_59_cast_fp16)[name = tensor("x0_10_cast_fp16")]; tensor concat_48_axis_0 = const()[name = tensor("concat_48_axis_0"), val = tensor(0)]; tensor concat_48_interleave_0 = const()[name = tensor("concat_48_interleave_0"), val = tensor(false)]; tensor gather_78_cast_uint16_to_int32 = cast(dtype = gather_78_cast_uint16_to_int32_dtype_0, x = gather_78_cast_uint16)[name = tensor("cast_205")]; tensor gather_80_cast_uint16_to_int32 = cast(dtype = gather_80_cast_uint16_to_int32_dtype_0, x = gather_80_cast_uint16)[name = tensor("cast_206")]; tensor concat_48 = concat(axis = concat_48_axis_0, interleave = concat_48_interleave_0, values = (gather_78_cast_uint16_to_int32, gather_79, var_21, gather_80_cast_uint16_to_int32))[name = tensor("concat_48")]; tensor x1_8_cast_fp16 = reshape(shape = concat_48, x = x0_10_cast_fp16)[name = tensor("x1_8_cast_fp16")]; tensor var_903_begin_0 = const()[name = tensor("op_903_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_903_end_0 = const()[name = tensor("op_903_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_903_end_mask_0 = const()[name = tensor("op_903_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_903_cast_fp16 = slice_by_index(begin = var_903_begin_0, end = var_903_end_0, end_mask = var_903_end_mask_0, x = x1_8_cast_fp16)[name = tensor("op_903_cast_fp16")]; tensor concat_49_axis_0 = const()[name = tensor("concat_49_axis_0"), val = tensor(0)]; tensor concat_49_interleave_0 = const()[name = tensor("concat_49_interleave_0"), val = tensor(false)]; tensor gather_81_cast_uint16_to_int32 = cast(dtype = gather_81_cast_uint16_to_int32_dtype_0, x = gather_81_cast_uint16)[name = tensor("cast_204")]; tensor concat_49 = concat(axis = concat_49_axis_0, interleave = concat_49_interleave_0, values = (gather_78_cast_uint16_to_int32, gather_79, gather_80_cast_uint16_to_int32, gather_81_cast_uint16_to_int32))[name = tensor("concat_49")]; tensor matrix_bd_8_cast_fp16 = reshape(shape = concat_49, x = var_903_cast_fp16)[name = tensor("matrix_bd_8_cast_fp16")]; tensor matrix_ac_8_transpose_x_0 = const()[name = tensor("matrix_ac_8_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_8_transpose_y_0 = const()[name = tensor("matrix_ac_8_transpose_y_0"), val = tensor(false)]; tensor transpose_206_perm_0 = const()[name = tensor("transpose_206_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_207_perm_0 = const()[name = tensor("transpose_207_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_207 = transpose(perm = transpose_207_perm_0, x = k_8_cast_fp16)[name = tensor("transpose_452")]; tensor transpose_206 = transpose(perm = transpose_206_perm_0, x = var_887_cast_fp16)[name = tensor("transpose_453")]; tensor matrix_ac_8_cast_fp16 = matmul(transpose_x = matrix_ac_8_transpose_x_0, transpose_y = matrix_ac_8_transpose_y_0, x = transpose_206, y = transpose_207)[name = tensor("matrix_ac_8_cast_fp16")]; tensor var_908_shape_cast_fp16 = shape(x = matrix_ac_8_cast_fp16)[name = tensor("op_908_shape_cast_fp16")]; tensor gather_82_axis_0 = const()[name = tensor("gather_82_axis_0"), val = tensor(0)]; tensor gather_82_batch_dims_0 = const()[name = tensor("gather_82_batch_dims_0"), val = tensor(0)]; tensor gather_82_validate_indices_0 = const()[name = tensor("gather_82_validate_indices_0"), val = tensor(false)]; tensor var_908_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_908_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_82_to_uint16 = const()[name = tensor("select_82_to_uint16"), val = tensor(3)]; tensor var_908_shape_cast_fp16_to_uint16 = cast(dtype = var_908_shape_cast_fp16_to_uint16_dtype_0, x = var_908_shape_cast_fp16)[name = tensor("cast_203")]; tensor gather_82_cast_uint16 = gather(axis = gather_82_axis_0, batch_dims = gather_82_batch_dims_0, indices = select_82_to_uint16, validate_indices = gather_82_validate_indices_0, x = var_908_shape_cast_fp16_to_uint16)[name = tensor("gather_82_cast_uint16")]; tensor gather_82_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_82_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_50_values0_0 = const()[name = tensor("concat_50_values0_0"), val = tensor(0)]; tensor concat_50_values1_0 = const()[name = tensor("concat_50_values1_0"), val = tensor(8)]; tensor concat_50_values2_0 = const()[name = tensor("concat_50_values2_0"), val = tensor(0)]; tensor concat_50_axis_0 = const()[name = tensor("concat_50_axis_0"), val = tensor(0)]; tensor concat_50_interleave_0 = const()[name = tensor("concat_50_interleave_0"), val = tensor(false)]; tensor gather_82_cast_uint16_to_int32 = cast(dtype = gather_82_cast_uint16_to_int32_dtype_0, x = gather_82_cast_uint16)[name = tensor("cast_202")]; tensor concat_50 = concat(axis = concat_50_axis_0, interleave = concat_50_interleave_0, values = (concat_50_values0_0, concat_50_values1_0, concat_50_values2_0, gather_82_cast_uint16_to_int32))[name = tensor("concat_50")]; tensor matrix_bd0_8_begin_0 = const()[name = tensor("matrix_bd0_8_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_8_end_mask_0 = const()[name = tensor("matrix_bd0_8_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_8_cast_fp16 = slice_by_index(begin = matrix_bd0_8_begin_0, end = concat_50, end_mask = matrix_bd0_8_end_mask_0, x = matrix_bd_8_cast_fp16)[name = tensor("matrix_bd0_8_cast_fp16")]; tensor var_913_cast_fp16 = add(x = matrix_ac_8_cast_fp16, y = matrix_bd0_8_cast_fp16)[name = tensor("op_913_cast_fp16")]; tensor _inversed_scores_8_y_0_to_fp16 = const()[name = tensor("_inversed_scores_8_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_8_cast_fp16 = mul(x = var_913_cast_fp16, y = _inversed_scores_8_y_0_to_fp16)[name = tensor("_inversed_scores_8_cast_fp16")]; tensor value_8_cast_fp16 = transpose(perm = value_8_perm_0, x = v_8_cast_fp16)[name = tensor("transpose_451")]; tensor var_916_shape_cast_fp16 = shape(x = value_8_cast_fp16)[name = tensor("op_916_shape_cast_fp16")]; tensor gather_83_axis_0 = const()[name = tensor("gather_83_axis_0"), val = tensor(0)]; tensor gather_83_batch_dims_0 = const()[name = tensor("gather_83_batch_dims_0"), val = tensor(0)]; tensor gather_83_validate_indices_0 = const()[name = tensor("gather_83_validate_indices_0"), val = tensor(false)]; tensor var_916_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_916_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_83_to_uint16 = const()[name = tensor("select_83_to_uint16"), val = tensor(0)]; tensor var_916_shape_cast_fp16_to_uint16 = cast(dtype = var_916_shape_cast_fp16_to_uint16_dtype_0, x = var_916_shape_cast_fp16)[name = tensor("cast_201")]; tensor gather_83_cast_uint16 = gather(axis = gather_83_axis_0, batch_dims = gather_83_batch_dims_0, indices = select_83_to_uint16, validate_indices = gather_83_validate_indices_0, x = var_916_shape_cast_fp16_to_uint16)[name = tensor("gather_83_cast_uint16")]; tensor gather_83_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_83_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_8_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_8_cast_fp16, cond = mask0_4)[name = tensor("scores0_8_cast_fp16")]; tensor var_919_cast_fp16 = softmax(axis = var_21, x = scores0_8_cast_fp16)[name = tensor("op_919_cast_fp16")]; tensor input_57_cast_fp16 = select(a = var_8_to_fp16, b = var_919_cast_fp16, cond = mask0_4)[name = tensor("input_57_cast_fp16")]; tensor x2_8_transpose_x_0 = const()[name = tensor("x2_8_transpose_x_0"), val = tensor(false)]; tensor x2_8_transpose_y_0 = const()[name = tensor("x2_8_transpose_y_0"), val = tensor(false)]; tensor x2_8_cast_fp16 = matmul(transpose_x = x2_8_transpose_x_0, transpose_y = x2_8_transpose_y_0, x = input_57_cast_fp16, y = value_8_cast_fp16)[name = tensor("x2_8_cast_fp16")]; tensor var_923_perm_0 = const()[name = tensor("op_923_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_51_axis_0 = const()[name = tensor("concat_51_axis_0"), val = tensor(0)]; tensor concat_51_interleave_0 = const()[name = tensor("concat_51_interleave_0"), val = tensor(false)]; tensor gather_83_cast_uint16_to_int32 = cast(dtype = gather_83_cast_uint16_to_int32_dtype_0, x = gather_83_cast_uint16)[name = tensor("cast_200")]; tensor concat_51 = concat(axis = concat_51_axis_0, interleave = concat_51_interleave_0, values = (gather_83_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_51")]; tensor var_923_cast_fp16 = transpose(perm = var_923_perm_0, x = x2_8_cast_fp16)[name = tensor("transpose_450")]; tensor input0_47_cast_fp16 = reshape(shape = concat_51, x = var_923_cast_fp16)[name = tensor("input0_47_cast_fp16")]; tensor encoder_layers_3_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51459520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51983872))), name = tensor("encoder_layers_3_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_34_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_self_attn_linear_out_weight_to_fp16_palettized, x = input0_47_cast_fp16)[name = tensor("linear_34_cast_fp16")]; tensor input0_49_cast_fp16 = add(x = input_55_cast_fp16, y = linear_34_cast_fp16)[name = tensor("input0_49_cast_fp16")]; tensor x_63_axes_0 = const()[name = tensor("x_63_axes_0"), val = tensor([-1])]; tensor encoder_layers_3_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_3_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51984000)))]; tensor encoder_layers_3_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_3_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51986112)))]; tensor x_63_cast_fp16 = layer_norm(axes = x_63_axes_0, beta = encoder_layers_3_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_3_norm_conv_weight_to_fp16, x = input0_49_cast_fp16)[name = tensor("x_63_cast_fp16")]; tensor input_59_perm_0 = const()[name = tensor("input_59_perm_0"), val = tensor([0, 2, 1])]; tensor input0_51_pad_type_0 = const()[name = tensor("input0_51_pad_type_0"), val = tensor("valid")]; tensor input0_51_strides_0 = const()[name = tensor("input0_51_strides_0"), val = tensor([1])]; tensor input0_51_pad_0 = const()[name = tensor("input0_51_pad_0"), val = tensor([0, 0])]; tensor input0_51_dilations_0 = const()[name = tensor("input0_51_dilations_0"), val = tensor([1])]; tensor input0_51_groups_0 = const()[name = tensor("input0_51_groups_0"), val = tensor(1)]; tensor encoder_layers_3_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51988224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53036864))), name = tensor("encoder_layers_3_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_59_cast_fp16 = transpose(perm = input_59_perm_0, x = x_63_cast_fp16)[name = tensor("transpose_449")]; tensor input0_51_cast_fp16 = conv(dilations = input0_51_dilations_0, groups = input0_51_groups_0, pad = input0_51_pad_0, pad_type = input0_51_pad_type_0, strides = input0_51_strides_0, weight = encoder_layers_3_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_59_cast_fp16)[name = tensor("input0_51_cast_fp16")]; tensor x_65_split_num_splits_0 = const()[name = tensor("x_65_split_num_splits_0"), val = tensor(2)]; tensor x_65_split_axis_0 = const()[name = tensor("x_65_split_axis_0"), val = tensor(1)]; tensor x_65_split_cast_fp16_0, tensor x_65_split_cast_fp16_1 = split(axis = x_65_split_axis_0, num_splits = x_65_split_num_splits_0, x = input0_51_cast_fp16)[name = tensor("x_65_split_cast_fp16")]; tensor x_65_split_1_sigmoid_cast_fp16 = sigmoid(x = x_65_split_cast_fp16_1)[name = tensor("x_65_split_1_sigmoid_cast_fp16")]; tensor x_65_cast_fp16 = mul(x = x_65_split_cast_fp16_0, y = x_65_split_1_sigmoid_cast_fp16)[name = tensor("x_65_cast_fp16")]; tensor input0_53_cast_fp16 = select(a = var_8_to_fp16, b = x_65_cast_fp16, cond = var_457)[name = tensor("input0_53_cast_fp16")]; tensor input0_55_pad_0 = const()[name = tensor("input0_55_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_55_mode_0 = const()[name = tensor("input0_55_mode_0"), val = tensor("constant")]; tensor const_18_to_fp16 = const()[name = tensor("const_18_to_fp16"), val = tensor(0x0p+0)]; tensor input0_55_cast_fp16 = pad(constant_val = const_18_to_fp16, mode = input0_55_mode_0, pad = input0_55_pad_0, x = input0_53_cast_fp16)[name = tensor("input0_55_cast_fp16")]; tensor input1_18_pad_type_0 = const()[name = tensor("input1_18_pad_type_0"), val = tensor("valid")]; tensor input1_18_groups_0 = const()[name = tensor("input1_18_groups_0"), val = tensor(1024)]; tensor input1_18_strides_0 = const()[name = tensor("input1_18_strides_0"), val = tensor([1])]; tensor input1_18_pad_0 = const()[name = tensor("input1_18_pad_0"), val = tensor([0, 0])]; tensor input1_18_dilations_0 = const()[name = tensor("input1_18_dilations_0"), val = tensor([1])]; tensor const_65_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53036992))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53041664))), name = tensor("const_65_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_66_to_fp16 = const()[name = tensor("const_66_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53041792)))]; tensor input_61_cast_fp16 = conv(bias = const_66_to_fp16, dilations = input1_18_dilations_0, groups = input1_18_groups_0, pad = input1_18_pad_0, pad_type = input1_18_pad_type_0, strides = input1_18_strides_0, weight = const_65_to_fp16_palettized, x = input0_55_cast_fp16)[name = tensor("input_61_cast_fp16")]; tensor var_961_cast_fp16 = silu(x = input_61_cast_fp16)[name = tensor("op_961_cast_fp16")]; tensor x_67_pad_type_0 = const()[name = tensor("x_67_pad_type_0"), val = tensor("valid")]; tensor x_67_strides_0 = const()[name = tensor("x_67_strides_0"), val = tensor([1])]; tensor x_67_pad_0 = const()[name = tensor("x_67_pad_0"), val = tensor([0, 0])]; tensor x_67_dilations_0 = const()[name = tensor("x_67_dilations_0"), val = tensor([1])]; tensor x_67_groups_0 = const()[name = tensor("x_67_groups_0"), val = tensor(1)]; tensor encoder_layers_3_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53043904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53568256))), name = tensor("encoder_layers_3_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_67_cast_fp16 = conv(dilations = x_67_dilations_0, groups = x_67_groups_0, pad = x_67_pad_0, pad_type = x_67_pad_type_0, strides = x_67_strides_0, weight = encoder_layers_3_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_961_cast_fp16)[name = tensor("x_67_cast_fp16")]; tensor var_968_perm_0 = const()[name = tensor("op_968_perm_0"), val = tensor([0, 2, 1])]; tensor var_968_cast_fp16 = transpose(perm = var_968_perm_0, x = x_67_cast_fp16)[name = tensor("transpose_448")]; tensor input1_20_cast_fp16 = add(x = input0_49_cast_fp16, y = var_968_cast_fp16)[name = tensor("input1_20_cast_fp16")]; tensor input0_57_axes_0 = const()[name = tensor("input0_57_axes_0"), val = tensor([-1])]; tensor encoder_layers_3_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_3_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53568384)))]; tensor encoder_layers_3_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_3_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53570496)))]; tensor input0_57_cast_fp16 = layer_norm(axes = input0_57_axes_0, beta = encoder_layers_3_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_3_norm_feed_forward2_weight_to_fp16, x = input1_20_cast_fp16)[name = tensor("input0_57_cast_fp16")]; tensor encoder_layers_3_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53572608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55669824))), name = tensor("encoder_layers_3_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_35_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_3_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_57_cast_fp16)[name = tensor("linear_35_cast_fp16")]; tensor var_979_cast_fp16 = silu(x = linear_35_cast_fp16)[name = tensor("op_979_cast_fp16")]; tensor encoder_layers_3_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55669952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57767168))), name = tensor("encoder_layers_3_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_36_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_3_feed_forward2_linear2_weight_to_fp16_palettized, x = var_979_cast_fp16)[name = tensor("linear_36_cast_fp16")]; tensor var_984_to_fp16 = const()[name = tensor("op_984_to_fp16"), val = tensor(0x1p-1)]; tensor var_985_cast_fp16 = mul(x = linear_36_cast_fp16, y = var_984_to_fp16)[name = tensor("op_985_cast_fp16")]; tensor input2_10_cast_fp16 = add(x = input1_20_cast_fp16, y = var_985_cast_fp16)[name = tensor("input2_10_cast_fp16")]; tensor input0_59_axes_0 = const()[name = tensor("input0_59_axes_0"), val = tensor([-1])]; tensor encoder_layers_3_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_3_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57767296)))]; tensor encoder_layers_3_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_3_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57769408)))]; tensor input0_59_cast_fp16 = layer_norm(axes = input0_59_axes_0, beta = encoder_layers_3_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_3_norm_out_weight_to_fp16, x = input2_10_cast_fp16)[name = tensor("input0_59_cast_fp16")]; tensor input_65_axes_0 = const()[name = tensor("input_65_axes_0"), val = tensor([-1])]; tensor encoder_layers_4_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_4_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57771520)))]; tensor encoder_layers_4_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_4_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57773632)))]; tensor input_65_cast_fp16 = layer_norm(axes = input_65_axes_0, beta = encoder_layers_4_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_4_norm_feed_forward1_weight_to_fp16, x = input0_59_cast_fp16)[name = tensor("input_65_cast_fp16")]; tensor encoder_layers_4_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57775744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59872960))), name = tensor("encoder_layers_4_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_37_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_4_feed_forward1_linear1_weight_to_fp16_palettized, x = input_65_cast_fp16)[name = tensor("linear_37_cast_fp16")]; tensor var_1008_cast_fp16 = silu(x = linear_37_cast_fp16)[name = tensor("op_1008_cast_fp16")]; tensor encoder_layers_4_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59873088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61970304))), name = tensor("encoder_layers_4_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_38_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1008_cast_fp16)[name = tensor("linear_38_cast_fp16")]; tensor var_1013_to_fp16 = const()[name = tensor("op_1013_to_fp16"), val = tensor(0x1p-1)]; tensor var_1014_cast_fp16 = mul(x = linear_38_cast_fp16, y = var_1013_to_fp16)[name = tensor("op_1014_cast_fp16")]; tensor input_69_cast_fp16 = add(x = input0_59_cast_fp16, y = var_1014_cast_fp16)[name = tensor("input_69_cast_fp16")]; tensor query_10_axes_0 = const()[name = tensor("query_10_axes_0"), val = tensor([-1])]; tensor encoder_layers_4_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_4_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61970432)))]; tensor encoder_layers_4_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_4_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61972544)))]; tensor query_10_cast_fp16 = layer_norm(axes = query_10_axes_0, beta = encoder_layers_4_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_4_norm_self_att_weight_to_fp16, x = input_69_cast_fp16)[name = tensor("query_10_cast_fp16")]; tensor var_1027_shape_cast_fp16 = shape(x = query_10_cast_fp16)[name = tensor("op_1027_shape_cast_fp16")]; tensor gather_84_axis_0 = const()[name = tensor("gather_84_axis_0"), val = tensor(0)]; tensor gather_84_batch_dims_0 = const()[name = tensor("gather_84_batch_dims_0"), val = tensor(0)]; tensor gather_84_validate_indices_0 = const()[name = tensor("gather_84_validate_indices_0"), val = tensor(false)]; tensor var_1027_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1027_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_84_to_uint16 = const()[name = tensor("select_84_to_uint16"), val = tensor(0)]; tensor var_1027_shape_cast_fp16_to_uint16 = cast(dtype = var_1027_shape_cast_fp16_to_uint16_dtype_0, x = var_1027_shape_cast_fp16)[name = tensor("cast_199")]; tensor gather_84_cast_uint16 = gather(axis = gather_84_axis_0, batch_dims = gather_84_batch_dims_0, indices = select_84_to_uint16, validate_indices = gather_84_validate_indices_0, x = var_1027_shape_cast_fp16_to_uint16)[name = tensor("gather_84_cast_uint16")]; tensor gather_84_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_84_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_4_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61974656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62499008))), name = tensor("encoder_layers_4_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_39_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_self_attn_linear_q_weight_to_fp16_palettized, x = query_10_cast_fp16)[name = tensor("linear_39_cast_fp16")]; tensor concat_52_axis_0 = const()[name = tensor("concat_52_axis_0"), val = tensor(0)]; tensor concat_52_interleave_0 = const()[name = tensor("concat_52_interleave_0"), val = tensor(false)]; tensor gather_84_cast_uint16_to_int32 = cast(dtype = gather_84_cast_uint16_to_int32_dtype_0, x = gather_84_cast_uint16)[name = tensor("cast_198")]; tensor concat_52 = concat(axis = concat_52_axis_0, interleave = concat_52_interleave_0, values = (gather_84_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_52")]; tensor q_10_cast_fp16 = reshape(shape = concat_52, x = linear_39_cast_fp16)[name = tensor("q_10_cast_fp16")]; tensor encoder_layers_4_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62499136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63023488))), name = tensor("encoder_layers_4_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_40_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_self_attn_linear_k_weight_to_fp16_palettized, x = query_10_cast_fp16)[name = tensor("linear_40_cast_fp16")]; tensor k_10_cast_fp16 = reshape(shape = concat_52, x = linear_40_cast_fp16)[name = tensor("k_10_cast_fp16")]; tensor encoder_layers_4_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63023616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63547968))), name = tensor("encoder_layers_4_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_41_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_self_attn_linear_v_weight_to_fp16_palettized, x = query_10_cast_fp16)[name = tensor("linear_41_cast_fp16")]; tensor v_10_cast_fp16 = reshape(shape = concat_52, x = linear_41_cast_fp16)[name = tensor("v_10_cast_fp16")]; tensor value_10_perm_0 = const()[name = tensor("value_10_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_4_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63548096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64072448))), name = tensor("encoder_layers_4_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_42_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_42_cast_fp16")]; tensor var_1047 = const()[name = tensor("op_1047"), val = tensor([1, -1, 8, 128])]; tensor p_10_cast_fp16 = reshape(shape = var_1047, x = linear_42_cast_fp16)[name = tensor("p_10_cast_fp16")]; tensor encoder_layers_4_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_4_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64072576)))]; tensor var_1050_cast_fp16 = add(x = q_10_cast_fp16, y = encoder_layers_4_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1050_cast_fp16")]; tensor encoder_layers_4_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_4_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64074688)))]; tensor var_1052_cast_fp16 = add(x = q_10_cast_fp16, y = encoder_layers_4_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1052_cast_fp16")]; tensor x_75_transpose_x_0 = const()[name = tensor("x_75_transpose_x_0"), val = tensor(false)]; tensor x_75_transpose_y_0 = const()[name = tensor("x_75_transpose_y_0"), val = tensor(false)]; tensor transpose_208_perm_0 = const()[name = tensor("transpose_208_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_209_perm_0 = const()[name = tensor("transpose_209_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_209 = transpose(perm = transpose_209_perm_0, x = p_10_cast_fp16)[name = tensor("transpose_446")]; tensor transpose_208 = transpose(perm = transpose_208_perm_0, x = var_1052_cast_fp16)[name = tensor("transpose_447")]; tensor x_75_cast_fp16 = matmul(transpose_x = x_75_transpose_x_0, transpose_y = x_75_transpose_y_0, x = transpose_208, y = transpose_209)[name = tensor("x_75_cast_fp16")]; tensor var_1056_shape_cast_fp16 = shape(x = x_75_cast_fp16)[name = tensor("op_1056_shape_cast_fp16")]; tensor gather_86_axis_0 = const()[name = tensor("gather_86_axis_0"), val = tensor(0)]; tensor gather_86_batch_dims_0 = const()[name = tensor("gather_86_batch_dims_0"), val = tensor(0)]; tensor gather_86_validate_indices_0 = const()[name = tensor("gather_86_validate_indices_0"), val = tensor(false)]; tensor var_1056_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1056_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_86_to_uint16 = const()[name = tensor("select_86_to_uint16"), val = tensor(0)]; tensor var_1056_shape_cast_fp16_to_uint16 = cast(dtype = var_1056_shape_cast_fp16_to_uint16_dtype_0, x = var_1056_shape_cast_fp16)[name = tensor("cast_197")]; tensor gather_86_cast_uint16 = gather(axis = gather_86_axis_0, batch_dims = gather_86_batch_dims_0, indices = select_86_to_uint16, validate_indices = gather_86_validate_indices_0, x = var_1056_shape_cast_fp16_to_uint16)[name = tensor("gather_86_cast_uint16")]; tensor gather_86_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_86_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_87 = const()[name = tensor("gather_87"), val = tensor(8)]; tensor gather_88_axis_0 = const()[name = tensor("gather_88_axis_0"), val = tensor(0)]; tensor gather_88_batch_dims_0 = const()[name = tensor("gather_88_batch_dims_0"), val = tensor(0)]; tensor gather_88_validate_indices_0 = const()[name = tensor("gather_88_validate_indices_0"), val = tensor(false)]; tensor select_88_to_uint16 = const()[name = tensor("select_88_to_uint16"), val = tensor(2)]; tensor gather_88_cast_uint16 = gather(axis = gather_88_axis_0, batch_dims = gather_88_batch_dims_0, indices = select_88_to_uint16, validate_indices = gather_88_validate_indices_0, x = var_1056_shape_cast_fp16_to_uint16)[name = tensor("gather_88_cast_uint16")]; tensor gather_88_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_88_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_89_axis_0 = const()[name = tensor("gather_89_axis_0"), val = tensor(0)]; tensor gather_89_batch_dims_0 = const()[name = tensor("gather_89_batch_dims_0"), val = tensor(0)]; tensor gather_89_validate_indices_0 = const()[name = tensor("gather_89_validate_indices_0"), val = tensor(false)]; tensor select_89_to_uint16 = const()[name = tensor("select_89_to_uint16"), val = tensor(3)]; tensor gather_89_cast_uint16 = gather(axis = gather_89_axis_0, batch_dims = gather_89_batch_dims_0, indices = select_89_to_uint16, validate_indices = gather_89_validate_indices_0, x = var_1056_shape_cast_fp16_to_uint16)[name = tensor("gather_89_cast_uint16")]; tensor gather_89_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_89_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_12_pad_0 = const()[name = tensor("x0_12_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_12_mode_0 = const()[name = tensor("x0_12_mode_0"), val = tensor("constant")]; tensor const_19_to_fp16 = const()[name = tensor("const_19_to_fp16"), val = tensor(0x0p+0)]; tensor x0_12_cast_fp16 = pad(constant_val = const_19_to_fp16, mode = x0_12_mode_0, pad = x0_12_pad_0, x = x_75_cast_fp16)[name = tensor("x0_12_cast_fp16")]; tensor concat_55_axis_0 = const()[name = tensor("concat_55_axis_0"), val = tensor(0)]; tensor concat_55_interleave_0 = const()[name = tensor("concat_55_interleave_0"), val = tensor(false)]; tensor gather_86_cast_uint16_to_int32 = cast(dtype = gather_86_cast_uint16_to_int32_dtype_0, x = gather_86_cast_uint16)[name = tensor("cast_195")]; tensor gather_88_cast_uint16_to_int32 = cast(dtype = gather_88_cast_uint16_to_int32_dtype_0, x = gather_88_cast_uint16)[name = tensor("cast_196")]; tensor concat_55 = concat(axis = concat_55_axis_0, interleave = concat_55_interleave_0, values = (gather_86_cast_uint16_to_int32, gather_87, var_21, gather_88_cast_uint16_to_int32))[name = tensor("concat_55")]; tensor x1_10_cast_fp16 = reshape(shape = concat_55, x = x0_12_cast_fp16)[name = tensor("x1_10_cast_fp16")]; tensor var_1066_begin_0 = const()[name = tensor("op_1066_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1066_end_0 = const()[name = tensor("op_1066_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_1066_end_mask_0 = const()[name = tensor("op_1066_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1066_cast_fp16 = slice_by_index(begin = var_1066_begin_0, end = var_1066_end_0, end_mask = var_1066_end_mask_0, x = x1_10_cast_fp16)[name = tensor("op_1066_cast_fp16")]; tensor concat_56_axis_0 = const()[name = tensor("concat_56_axis_0"), val = tensor(0)]; tensor concat_56_interleave_0 = const()[name = tensor("concat_56_interleave_0"), val = tensor(false)]; tensor gather_89_cast_uint16_to_int32 = cast(dtype = gather_89_cast_uint16_to_int32_dtype_0, x = gather_89_cast_uint16)[name = tensor("cast_194")]; tensor concat_56 = concat(axis = concat_56_axis_0, interleave = concat_56_interleave_0, values = (gather_86_cast_uint16_to_int32, gather_87, gather_88_cast_uint16_to_int32, gather_89_cast_uint16_to_int32))[name = tensor("concat_56")]; tensor matrix_bd_10_cast_fp16 = reshape(shape = concat_56, x = var_1066_cast_fp16)[name = tensor("matrix_bd_10_cast_fp16")]; tensor matrix_ac_10_transpose_x_0 = const()[name = tensor("matrix_ac_10_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_10_transpose_y_0 = const()[name = tensor("matrix_ac_10_transpose_y_0"), val = tensor(false)]; tensor transpose_210_perm_0 = const()[name = tensor("transpose_210_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_211_perm_0 = const()[name = tensor("transpose_211_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_211 = transpose(perm = transpose_211_perm_0, x = k_10_cast_fp16)[name = tensor("transpose_444")]; tensor transpose_210 = transpose(perm = transpose_210_perm_0, x = var_1050_cast_fp16)[name = tensor("transpose_445")]; tensor matrix_ac_10_cast_fp16 = matmul(transpose_x = matrix_ac_10_transpose_x_0, transpose_y = matrix_ac_10_transpose_y_0, x = transpose_210, y = transpose_211)[name = tensor("matrix_ac_10_cast_fp16")]; tensor var_1071_shape_cast_fp16 = shape(x = matrix_ac_10_cast_fp16)[name = tensor("op_1071_shape_cast_fp16")]; tensor gather_90_axis_0 = const()[name = tensor("gather_90_axis_0"), val = tensor(0)]; tensor gather_90_batch_dims_0 = const()[name = tensor("gather_90_batch_dims_0"), val = tensor(0)]; tensor gather_90_validate_indices_0 = const()[name = tensor("gather_90_validate_indices_0"), val = tensor(false)]; tensor var_1071_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1071_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_90_to_uint16 = const()[name = tensor("select_90_to_uint16"), val = tensor(3)]; tensor var_1071_shape_cast_fp16_to_uint16 = cast(dtype = var_1071_shape_cast_fp16_to_uint16_dtype_0, x = var_1071_shape_cast_fp16)[name = tensor("cast_193")]; tensor gather_90_cast_uint16 = gather(axis = gather_90_axis_0, batch_dims = gather_90_batch_dims_0, indices = select_90_to_uint16, validate_indices = gather_90_validate_indices_0, x = var_1071_shape_cast_fp16_to_uint16)[name = tensor("gather_90_cast_uint16")]; tensor gather_90_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_90_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_57_values0_0 = const()[name = tensor("concat_57_values0_0"), val = tensor(0)]; tensor concat_57_values1_0 = const()[name = tensor("concat_57_values1_0"), val = tensor(8)]; tensor concat_57_values2_0 = const()[name = tensor("concat_57_values2_0"), val = tensor(0)]; tensor concat_57_axis_0 = const()[name = tensor("concat_57_axis_0"), val = tensor(0)]; tensor concat_57_interleave_0 = const()[name = tensor("concat_57_interleave_0"), val = tensor(false)]; tensor gather_90_cast_uint16_to_int32 = cast(dtype = gather_90_cast_uint16_to_int32_dtype_0, x = gather_90_cast_uint16)[name = tensor("cast_192")]; tensor concat_57 = concat(axis = concat_57_axis_0, interleave = concat_57_interleave_0, values = (concat_57_values0_0, concat_57_values1_0, concat_57_values2_0, gather_90_cast_uint16_to_int32))[name = tensor("concat_57")]; tensor matrix_bd0_10_begin_0 = const()[name = tensor("matrix_bd0_10_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_10_end_mask_0 = const()[name = tensor("matrix_bd0_10_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_10_cast_fp16 = slice_by_index(begin = matrix_bd0_10_begin_0, end = concat_57, end_mask = matrix_bd0_10_end_mask_0, x = matrix_bd_10_cast_fp16)[name = tensor("matrix_bd0_10_cast_fp16")]; tensor var_1076_cast_fp16 = add(x = matrix_ac_10_cast_fp16, y = matrix_bd0_10_cast_fp16)[name = tensor("op_1076_cast_fp16")]; tensor _inversed_scores_10_y_0_to_fp16 = const()[name = tensor("_inversed_scores_10_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_10_cast_fp16 = mul(x = var_1076_cast_fp16, y = _inversed_scores_10_y_0_to_fp16)[name = tensor("_inversed_scores_10_cast_fp16")]; tensor value_10_cast_fp16 = transpose(perm = value_10_perm_0, x = v_10_cast_fp16)[name = tensor("transpose_443")]; tensor var_1079_shape_cast_fp16 = shape(x = value_10_cast_fp16)[name = tensor("op_1079_shape_cast_fp16")]; tensor gather_91_axis_0 = const()[name = tensor("gather_91_axis_0"), val = tensor(0)]; tensor gather_91_batch_dims_0 = const()[name = tensor("gather_91_batch_dims_0"), val = tensor(0)]; tensor gather_91_validate_indices_0 = const()[name = tensor("gather_91_validate_indices_0"), val = tensor(false)]; tensor var_1079_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1079_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_91_to_uint16 = const()[name = tensor("select_91_to_uint16"), val = tensor(0)]; tensor var_1079_shape_cast_fp16_to_uint16 = cast(dtype = var_1079_shape_cast_fp16_to_uint16_dtype_0, x = var_1079_shape_cast_fp16)[name = tensor("cast_191")]; tensor gather_91_cast_uint16 = gather(axis = gather_91_axis_0, batch_dims = gather_91_batch_dims_0, indices = select_91_to_uint16, validate_indices = gather_91_validate_indices_0, x = var_1079_shape_cast_fp16_to_uint16)[name = tensor("gather_91_cast_uint16")]; tensor gather_91_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_91_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_10_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_10_cast_fp16, cond = mask0_4)[name = tensor("scores0_10_cast_fp16")]; tensor var_1082_cast_fp16 = softmax(axis = var_21, x = scores0_10_cast_fp16)[name = tensor("op_1082_cast_fp16")]; tensor input_71_cast_fp16 = select(a = var_8_to_fp16, b = var_1082_cast_fp16, cond = mask0_4)[name = tensor("input_71_cast_fp16")]; tensor x2_10_transpose_x_0 = const()[name = tensor("x2_10_transpose_x_0"), val = tensor(false)]; tensor x2_10_transpose_y_0 = const()[name = tensor("x2_10_transpose_y_0"), val = tensor(false)]; tensor x2_10_cast_fp16 = matmul(transpose_x = x2_10_transpose_x_0, transpose_y = x2_10_transpose_y_0, x = input_71_cast_fp16, y = value_10_cast_fp16)[name = tensor("x2_10_cast_fp16")]; tensor var_1086_perm_0 = const()[name = tensor("op_1086_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_58_axis_0 = const()[name = tensor("concat_58_axis_0"), val = tensor(0)]; tensor concat_58_interleave_0 = const()[name = tensor("concat_58_interleave_0"), val = tensor(false)]; tensor gather_91_cast_uint16_to_int32 = cast(dtype = gather_91_cast_uint16_to_int32_dtype_0, x = gather_91_cast_uint16)[name = tensor("cast_190")]; tensor concat_58 = concat(axis = concat_58_axis_0, interleave = concat_58_interleave_0, values = (gather_91_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_58")]; tensor var_1086_cast_fp16 = transpose(perm = var_1086_perm_0, x = x2_10_cast_fp16)[name = tensor("transpose_442")]; tensor input0_61_cast_fp16 = reshape(shape = concat_58, x = var_1086_cast_fp16)[name = tensor("input0_61_cast_fp16")]; tensor encoder_layers_4_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64076800))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64601152))), name = tensor("encoder_layers_4_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_43_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_self_attn_linear_out_weight_to_fp16_palettized, x = input0_61_cast_fp16)[name = tensor("linear_43_cast_fp16")]; tensor input0_63_cast_fp16 = add(x = input_69_cast_fp16, y = linear_43_cast_fp16)[name = tensor("input0_63_cast_fp16")]; tensor x_79_axes_0 = const()[name = tensor("x_79_axes_0"), val = tensor([-1])]; tensor encoder_layers_4_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_4_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64601280)))]; tensor encoder_layers_4_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_4_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64603392)))]; tensor x_79_cast_fp16 = layer_norm(axes = x_79_axes_0, beta = encoder_layers_4_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_4_norm_conv_weight_to_fp16, x = input0_63_cast_fp16)[name = tensor("x_79_cast_fp16")]; tensor input_73_perm_0 = const()[name = tensor("input_73_perm_0"), val = tensor([0, 2, 1])]; tensor input0_65_pad_type_0 = const()[name = tensor("input0_65_pad_type_0"), val = tensor("valid")]; tensor input0_65_strides_0 = const()[name = tensor("input0_65_strides_0"), val = tensor([1])]; tensor input0_65_pad_0 = const()[name = tensor("input0_65_pad_0"), val = tensor([0, 0])]; tensor input0_65_dilations_0 = const()[name = tensor("input0_65_dilations_0"), val = tensor([1])]; tensor input0_65_groups_0 = const()[name = tensor("input0_65_groups_0"), val = tensor(1)]; tensor encoder_layers_4_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64605504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65654144))), name = tensor("encoder_layers_4_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_73_cast_fp16 = transpose(perm = input_73_perm_0, x = x_79_cast_fp16)[name = tensor("transpose_441")]; tensor input0_65_cast_fp16 = conv(dilations = input0_65_dilations_0, groups = input0_65_groups_0, pad = input0_65_pad_0, pad_type = input0_65_pad_type_0, strides = input0_65_strides_0, weight = encoder_layers_4_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_73_cast_fp16)[name = tensor("input0_65_cast_fp16")]; tensor x_81_split_num_splits_0 = const()[name = tensor("x_81_split_num_splits_0"), val = tensor(2)]; tensor x_81_split_axis_0 = const()[name = tensor("x_81_split_axis_0"), val = tensor(1)]; tensor x_81_split_cast_fp16_0, tensor x_81_split_cast_fp16_1 = split(axis = x_81_split_axis_0, num_splits = x_81_split_num_splits_0, x = input0_65_cast_fp16)[name = tensor("x_81_split_cast_fp16")]; tensor x_81_split_1_sigmoid_cast_fp16 = sigmoid(x = x_81_split_cast_fp16_1)[name = tensor("x_81_split_1_sigmoid_cast_fp16")]; tensor x_81_cast_fp16 = mul(x = x_81_split_cast_fp16_0, y = x_81_split_1_sigmoid_cast_fp16)[name = tensor("x_81_cast_fp16")]; tensor input0_67_cast_fp16 = select(a = var_8_to_fp16, b = x_81_cast_fp16, cond = var_457)[name = tensor("input0_67_cast_fp16")]; tensor input0_69_pad_0 = const()[name = tensor("input0_69_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_69_mode_0 = const()[name = tensor("input0_69_mode_0"), val = tensor("constant")]; tensor const_20_to_fp16 = const()[name = tensor("const_20_to_fp16"), val = tensor(0x0p+0)]; tensor input0_69_cast_fp16 = pad(constant_val = const_20_to_fp16, mode = input0_69_mode_0, pad = input0_69_pad_0, x = input0_67_cast_fp16)[name = tensor("input0_69_cast_fp16")]; tensor input1_22_pad_type_0 = const()[name = tensor("input1_22_pad_type_0"), val = tensor("valid")]; tensor input1_22_groups_0 = const()[name = tensor("input1_22_groups_0"), val = tensor(1024)]; tensor input1_22_strides_0 = const()[name = tensor("input1_22_strides_0"), val = tensor([1])]; tensor input1_22_pad_0 = const()[name = tensor("input1_22_pad_0"), val = tensor([0, 0])]; tensor input1_22_dilations_0 = const()[name = tensor("input1_22_dilations_0"), val = tensor([1])]; tensor const_67_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65654272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65658944))), name = tensor("const_67_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_68_to_fp16 = const()[name = tensor("const_68_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65659072)))]; tensor input_75_cast_fp16 = conv(bias = const_68_to_fp16, dilations = input1_22_dilations_0, groups = input1_22_groups_0, pad = input1_22_pad_0, pad_type = input1_22_pad_type_0, strides = input1_22_strides_0, weight = const_67_to_fp16_palettized, x = input0_69_cast_fp16)[name = tensor("input_75_cast_fp16")]; tensor var_1124_cast_fp16 = silu(x = input_75_cast_fp16)[name = tensor("op_1124_cast_fp16")]; tensor x_83_pad_type_0 = const()[name = tensor("x_83_pad_type_0"), val = tensor("valid")]; tensor x_83_strides_0 = const()[name = tensor("x_83_strides_0"), val = tensor([1])]; tensor x_83_pad_0 = const()[name = tensor("x_83_pad_0"), val = tensor([0, 0])]; tensor x_83_dilations_0 = const()[name = tensor("x_83_dilations_0"), val = tensor([1])]; tensor x_83_groups_0 = const()[name = tensor("x_83_groups_0"), val = tensor(1)]; tensor encoder_layers_4_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65661184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66185536))), name = tensor("encoder_layers_4_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_83_cast_fp16 = conv(dilations = x_83_dilations_0, groups = x_83_groups_0, pad = x_83_pad_0, pad_type = x_83_pad_type_0, strides = x_83_strides_0, weight = encoder_layers_4_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1124_cast_fp16)[name = tensor("x_83_cast_fp16")]; tensor var_1131_perm_0 = const()[name = tensor("op_1131_perm_0"), val = tensor([0, 2, 1])]; tensor var_1131_cast_fp16 = transpose(perm = var_1131_perm_0, x = x_83_cast_fp16)[name = tensor("transpose_440")]; tensor input1_24_cast_fp16 = add(x = input0_63_cast_fp16, y = var_1131_cast_fp16)[name = tensor("input1_24_cast_fp16")]; tensor input0_71_axes_0 = const()[name = tensor("input0_71_axes_0"), val = tensor([-1])]; tensor encoder_layers_4_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_4_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66185664)))]; tensor encoder_layers_4_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_4_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66187776)))]; tensor input0_71_cast_fp16 = layer_norm(axes = input0_71_axes_0, beta = encoder_layers_4_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_4_norm_feed_forward2_weight_to_fp16, x = input1_24_cast_fp16)[name = tensor("input0_71_cast_fp16")]; tensor encoder_layers_4_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66189888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68287104))), name = tensor("encoder_layers_4_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_44_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_4_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_71_cast_fp16)[name = tensor("linear_44_cast_fp16")]; tensor var_1142_cast_fp16 = silu(x = linear_44_cast_fp16)[name = tensor("op_1142_cast_fp16")]; tensor encoder_layers_4_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68287232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70384448))), name = tensor("encoder_layers_4_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_45_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_4_feed_forward2_linear2_weight_to_fp16_palettized, x = var_1142_cast_fp16)[name = tensor("linear_45_cast_fp16")]; tensor var_1147_to_fp16 = const()[name = tensor("op_1147_to_fp16"), val = tensor(0x1p-1)]; tensor var_1148_cast_fp16 = mul(x = linear_45_cast_fp16, y = var_1147_to_fp16)[name = tensor("op_1148_cast_fp16")]; tensor input2_12_cast_fp16 = add(x = input1_24_cast_fp16, y = var_1148_cast_fp16)[name = tensor("input2_12_cast_fp16")]; tensor input0_73_axes_0 = const()[name = tensor("input0_73_axes_0"), val = tensor([-1])]; tensor encoder_layers_4_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_4_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70384576)))]; tensor encoder_layers_4_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_4_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70386688)))]; tensor input0_73_cast_fp16 = layer_norm(axes = input0_73_axes_0, beta = encoder_layers_4_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_4_norm_out_weight_to_fp16, x = input2_12_cast_fp16)[name = tensor("input0_73_cast_fp16")]; tensor input_79_axes_0 = const()[name = tensor("input_79_axes_0"), val = tensor([-1])]; tensor encoder_layers_5_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_5_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70388800)))]; tensor encoder_layers_5_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_5_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70390912)))]; tensor input_79_cast_fp16 = layer_norm(axes = input_79_axes_0, beta = encoder_layers_5_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_5_norm_feed_forward1_weight_to_fp16, x = input0_73_cast_fp16)[name = tensor("input_79_cast_fp16")]; tensor encoder_layers_5_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70393024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72490240))), name = tensor("encoder_layers_5_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_46_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_5_feed_forward1_linear1_weight_to_fp16_palettized, x = input_79_cast_fp16)[name = tensor("linear_46_cast_fp16")]; tensor var_1171_cast_fp16 = silu(x = linear_46_cast_fp16)[name = tensor("op_1171_cast_fp16")]; tensor encoder_layers_5_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72490368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74587584))), name = tensor("encoder_layers_5_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_47_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1171_cast_fp16)[name = tensor("linear_47_cast_fp16")]; tensor var_1176_to_fp16 = const()[name = tensor("op_1176_to_fp16"), val = tensor(0x1p-1)]; tensor var_1177_cast_fp16 = mul(x = linear_47_cast_fp16, y = var_1176_to_fp16)[name = tensor("op_1177_cast_fp16")]; tensor input_83_cast_fp16 = add(x = input0_73_cast_fp16, y = var_1177_cast_fp16)[name = tensor("input_83_cast_fp16")]; tensor query_12_axes_0 = const()[name = tensor("query_12_axes_0"), val = tensor([-1])]; tensor encoder_layers_5_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_5_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74587712)))]; tensor encoder_layers_5_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_5_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74589824)))]; tensor query_12_cast_fp16 = layer_norm(axes = query_12_axes_0, beta = encoder_layers_5_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_5_norm_self_att_weight_to_fp16, x = input_83_cast_fp16)[name = tensor("query_12_cast_fp16")]; tensor var_1190_shape_cast_fp16 = shape(x = query_12_cast_fp16)[name = tensor("op_1190_shape_cast_fp16")]; tensor gather_92_axis_0 = const()[name = tensor("gather_92_axis_0"), val = tensor(0)]; tensor gather_92_batch_dims_0 = const()[name = tensor("gather_92_batch_dims_0"), val = tensor(0)]; tensor gather_92_validate_indices_0 = const()[name = tensor("gather_92_validate_indices_0"), val = tensor(false)]; tensor var_1190_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1190_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_92_to_uint16 = const()[name = tensor("select_92_to_uint16"), val = tensor(0)]; tensor var_1190_shape_cast_fp16_to_uint16 = cast(dtype = var_1190_shape_cast_fp16_to_uint16_dtype_0, x = var_1190_shape_cast_fp16)[name = tensor("cast_189")]; tensor gather_92_cast_uint16 = gather(axis = gather_92_axis_0, batch_dims = gather_92_batch_dims_0, indices = select_92_to_uint16, validate_indices = gather_92_validate_indices_0, x = var_1190_shape_cast_fp16_to_uint16)[name = tensor("gather_92_cast_uint16")]; tensor gather_92_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_92_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_5_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74591936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75116288))), name = tensor("encoder_layers_5_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_48_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_self_attn_linear_q_weight_to_fp16_palettized, x = query_12_cast_fp16)[name = tensor("linear_48_cast_fp16")]; tensor concat_59_axis_0 = const()[name = tensor("concat_59_axis_0"), val = tensor(0)]; tensor concat_59_interleave_0 = const()[name = tensor("concat_59_interleave_0"), val = tensor(false)]; tensor gather_92_cast_uint16_to_int32 = cast(dtype = gather_92_cast_uint16_to_int32_dtype_0, x = gather_92_cast_uint16)[name = tensor("cast_188")]; tensor concat_59 = concat(axis = concat_59_axis_0, interleave = concat_59_interleave_0, values = (gather_92_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_59")]; tensor q_12_cast_fp16 = reshape(shape = concat_59, x = linear_48_cast_fp16)[name = tensor("q_12_cast_fp16")]; tensor encoder_layers_5_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75116416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75640768))), name = tensor("encoder_layers_5_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_49_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_self_attn_linear_k_weight_to_fp16_palettized, x = query_12_cast_fp16)[name = tensor("linear_49_cast_fp16")]; tensor k_12_cast_fp16 = reshape(shape = concat_59, x = linear_49_cast_fp16)[name = tensor("k_12_cast_fp16")]; tensor encoder_layers_5_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75640896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76165248))), name = tensor("encoder_layers_5_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_50_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_self_attn_linear_v_weight_to_fp16_palettized, x = query_12_cast_fp16)[name = tensor("linear_50_cast_fp16")]; tensor v_12_cast_fp16 = reshape(shape = concat_59, x = linear_50_cast_fp16)[name = tensor("v_12_cast_fp16")]; tensor value_12_perm_0 = const()[name = tensor("value_12_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_5_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76165376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76689728))), name = tensor("encoder_layers_5_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_51_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_51_cast_fp16")]; tensor var_1210 = const()[name = tensor("op_1210"), val = tensor([1, -1, 8, 128])]; tensor p_12_cast_fp16 = reshape(shape = var_1210, x = linear_51_cast_fp16)[name = tensor("p_12_cast_fp16")]; tensor encoder_layers_5_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_5_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76689856)))]; tensor var_1213_cast_fp16 = add(x = q_12_cast_fp16, y = encoder_layers_5_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1213_cast_fp16")]; tensor encoder_layers_5_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_5_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76691968)))]; tensor var_1215_cast_fp16 = add(x = q_12_cast_fp16, y = encoder_layers_5_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1215_cast_fp16")]; tensor x_91_transpose_x_0 = const()[name = tensor("x_91_transpose_x_0"), val = tensor(false)]; tensor x_91_transpose_y_0 = const()[name = tensor("x_91_transpose_y_0"), val = tensor(false)]; tensor transpose_212_perm_0 = const()[name = tensor("transpose_212_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_213_perm_0 = const()[name = tensor("transpose_213_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_213 = transpose(perm = transpose_213_perm_0, x = p_12_cast_fp16)[name = tensor("transpose_438")]; tensor transpose_212 = transpose(perm = transpose_212_perm_0, x = var_1215_cast_fp16)[name = tensor("transpose_439")]; tensor x_91_cast_fp16 = matmul(transpose_x = x_91_transpose_x_0, transpose_y = x_91_transpose_y_0, x = transpose_212, y = transpose_213)[name = tensor("x_91_cast_fp16")]; tensor var_1219_shape_cast_fp16 = shape(x = x_91_cast_fp16)[name = tensor("op_1219_shape_cast_fp16")]; tensor gather_94_axis_0 = const()[name = tensor("gather_94_axis_0"), val = tensor(0)]; tensor gather_94_batch_dims_0 = const()[name = tensor("gather_94_batch_dims_0"), val = tensor(0)]; tensor gather_94_validate_indices_0 = const()[name = tensor("gather_94_validate_indices_0"), val = tensor(false)]; tensor var_1219_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1219_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_94_to_uint16 = const()[name = tensor("select_94_to_uint16"), val = tensor(0)]; tensor var_1219_shape_cast_fp16_to_uint16 = cast(dtype = var_1219_shape_cast_fp16_to_uint16_dtype_0, x = var_1219_shape_cast_fp16)[name = tensor("cast_187")]; tensor gather_94_cast_uint16 = gather(axis = gather_94_axis_0, batch_dims = gather_94_batch_dims_0, indices = select_94_to_uint16, validate_indices = gather_94_validate_indices_0, x = var_1219_shape_cast_fp16_to_uint16)[name = tensor("gather_94_cast_uint16")]; tensor gather_94_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_94_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_95 = const()[name = tensor("gather_95"), val = tensor(8)]; tensor gather_96_axis_0 = const()[name = tensor("gather_96_axis_0"), val = tensor(0)]; tensor gather_96_batch_dims_0 = const()[name = tensor("gather_96_batch_dims_0"), val = tensor(0)]; tensor gather_96_validate_indices_0 = const()[name = tensor("gather_96_validate_indices_0"), val = tensor(false)]; tensor select_96_to_uint16 = const()[name = tensor("select_96_to_uint16"), val = tensor(2)]; tensor gather_96_cast_uint16 = gather(axis = gather_96_axis_0, batch_dims = gather_96_batch_dims_0, indices = select_96_to_uint16, validate_indices = gather_96_validate_indices_0, x = var_1219_shape_cast_fp16_to_uint16)[name = tensor("gather_96_cast_uint16")]; tensor gather_96_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_96_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_97_axis_0 = const()[name = tensor("gather_97_axis_0"), val = tensor(0)]; tensor gather_97_batch_dims_0 = const()[name = tensor("gather_97_batch_dims_0"), val = tensor(0)]; tensor gather_97_validate_indices_0 = const()[name = tensor("gather_97_validate_indices_0"), val = tensor(false)]; tensor select_97_to_uint16 = const()[name = tensor("select_97_to_uint16"), val = tensor(3)]; tensor gather_97_cast_uint16 = gather(axis = gather_97_axis_0, batch_dims = gather_97_batch_dims_0, indices = select_97_to_uint16, validate_indices = gather_97_validate_indices_0, x = var_1219_shape_cast_fp16_to_uint16)[name = tensor("gather_97_cast_uint16")]; tensor gather_97_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_97_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_14_pad_0 = const()[name = tensor("x0_14_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_14_mode_0 = const()[name = tensor("x0_14_mode_0"), val = tensor("constant")]; tensor const_21_to_fp16 = const()[name = tensor("const_21_to_fp16"), val = tensor(0x0p+0)]; tensor x0_14_cast_fp16 = pad(constant_val = const_21_to_fp16, mode = x0_14_mode_0, pad = x0_14_pad_0, x = x_91_cast_fp16)[name = tensor("x0_14_cast_fp16")]; tensor concat_62_axis_0 = const()[name = tensor("concat_62_axis_0"), val = tensor(0)]; tensor concat_62_interleave_0 = const()[name = tensor("concat_62_interleave_0"), val = tensor(false)]; tensor gather_94_cast_uint16_to_int32 = cast(dtype = gather_94_cast_uint16_to_int32_dtype_0, x = gather_94_cast_uint16)[name = tensor("cast_185")]; tensor gather_96_cast_uint16_to_int32 = cast(dtype = gather_96_cast_uint16_to_int32_dtype_0, x = gather_96_cast_uint16)[name = tensor("cast_186")]; tensor concat_62 = concat(axis = concat_62_axis_0, interleave = concat_62_interleave_0, values = (gather_94_cast_uint16_to_int32, gather_95, var_21, gather_96_cast_uint16_to_int32))[name = tensor("concat_62")]; tensor x1_12_cast_fp16 = reshape(shape = concat_62, x = x0_14_cast_fp16)[name = tensor("x1_12_cast_fp16")]; tensor var_1229_begin_0 = const()[name = tensor("op_1229_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1229_end_0 = const()[name = tensor("op_1229_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_1229_end_mask_0 = const()[name = tensor("op_1229_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1229_cast_fp16 = slice_by_index(begin = var_1229_begin_0, end = var_1229_end_0, end_mask = var_1229_end_mask_0, x = x1_12_cast_fp16)[name = tensor("op_1229_cast_fp16")]; tensor concat_63_axis_0 = const()[name = tensor("concat_63_axis_0"), val = tensor(0)]; tensor concat_63_interleave_0 = const()[name = tensor("concat_63_interleave_0"), val = tensor(false)]; tensor gather_97_cast_uint16_to_int32 = cast(dtype = gather_97_cast_uint16_to_int32_dtype_0, x = gather_97_cast_uint16)[name = tensor("cast_184")]; tensor concat_63 = concat(axis = concat_63_axis_0, interleave = concat_63_interleave_0, values = (gather_94_cast_uint16_to_int32, gather_95, gather_96_cast_uint16_to_int32, gather_97_cast_uint16_to_int32))[name = tensor("concat_63")]; tensor matrix_bd_12_cast_fp16 = reshape(shape = concat_63, x = var_1229_cast_fp16)[name = tensor("matrix_bd_12_cast_fp16")]; tensor matrix_ac_12_transpose_x_0 = const()[name = tensor("matrix_ac_12_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_12_transpose_y_0 = const()[name = tensor("matrix_ac_12_transpose_y_0"), val = tensor(false)]; tensor transpose_214_perm_0 = const()[name = tensor("transpose_214_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_215_perm_0 = const()[name = tensor("transpose_215_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_215 = transpose(perm = transpose_215_perm_0, x = k_12_cast_fp16)[name = tensor("transpose_436")]; tensor transpose_214 = transpose(perm = transpose_214_perm_0, x = var_1213_cast_fp16)[name = tensor("transpose_437")]; tensor matrix_ac_12_cast_fp16 = matmul(transpose_x = matrix_ac_12_transpose_x_0, transpose_y = matrix_ac_12_transpose_y_0, x = transpose_214, y = transpose_215)[name = tensor("matrix_ac_12_cast_fp16")]; tensor var_1234_shape_cast_fp16 = shape(x = matrix_ac_12_cast_fp16)[name = tensor("op_1234_shape_cast_fp16")]; tensor gather_98_axis_0 = const()[name = tensor("gather_98_axis_0"), val = tensor(0)]; tensor gather_98_batch_dims_0 = const()[name = tensor("gather_98_batch_dims_0"), val = tensor(0)]; tensor gather_98_validate_indices_0 = const()[name = tensor("gather_98_validate_indices_0"), val = tensor(false)]; tensor var_1234_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1234_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_98_to_uint16 = const()[name = tensor("select_98_to_uint16"), val = tensor(3)]; tensor var_1234_shape_cast_fp16_to_uint16 = cast(dtype = var_1234_shape_cast_fp16_to_uint16_dtype_0, x = var_1234_shape_cast_fp16)[name = tensor("cast_183")]; tensor gather_98_cast_uint16 = gather(axis = gather_98_axis_0, batch_dims = gather_98_batch_dims_0, indices = select_98_to_uint16, validate_indices = gather_98_validate_indices_0, x = var_1234_shape_cast_fp16_to_uint16)[name = tensor("gather_98_cast_uint16")]; tensor gather_98_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_98_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_64_values0_0 = const()[name = tensor("concat_64_values0_0"), val = tensor(0)]; tensor concat_64_values1_0 = const()[name = tensor("concat_64_values1_0"), val = tensor(8)]; tensor concat_64_values2_0 = const()[name = tensor("concat_64_values2_0"), val = tensor(0)]; tensor concat_64_axis_0 = const()[name = tensor("concat_64_axis_0"), val = tensor(0)]; tensor concat_64_interleave_0 = const()[name = tensor("concat_64_interleave_0"), val = tensor(false)]; tensor gather_98_cast_uint16_to_int32 = cast(dtype = gather_98_cast_uint16_to_int32_dtype_0, x = gather_98_cast_uint16)[name = tensor("cast_182")]; tensor concat_64 = concat(axis = concat_64_axis_0, interleave = concat_64_interleave_0, values = (concat_64_values0_0, concat_64_values1_0, concat_64_values2_0, gather_98_cast_uint16_to_int32))[name = tensor("concat_64")]; tensor matrix_bd0_12_begin_0 = const()[name = tensor("matrix_bd0_12_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_12_end_mask_0 = const()[name = tensor("matrix_bd0_12_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_12_cast_fp16 = slice_by_index(begin = matrix_bd0_12_begin_0, end = concat_64, end_mask = matrix_bd0_12_end_mask_0, x = matrix_bd_12_cast_fp16)[name = tensor("matrix_bd0_12_cast_fp16")]; tensor var_1239_cast_fp16 = add(x = matrix_ac_12_cast_fp16, y = matrix_bd0_12_cast_fp16)[name = tensor("op_1239_cast_fp16")]; tensor _inversed_scores_12_y_0_to_fp16 = const()[name = tensor("_inversed_scores_12_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_12_cast_fp16 = mul(x = var_1239_cast_fp16, y = _inversed_scores_12_y_0_to_fp16)[name = tensor("_inversed_scores_12_cast_fp16")]; tensor value_12_cast_fp16 = transpose(perm = value_12_perm_0, x = v_12_cast_fp16)[name = tensor("transpose_435")]; tensor var_1242_shape_cast_fp16 = shape(x = value_12_cast_fp16)[name = tensor("op_1242_shape_cast_fp16")]; tensor gather_99_axis_0 = const()[name = tensor("gather_99_axis_0"), val = tensor(0)]; tensor gather_99_batch_dims_0 = const()[name = tensor("gather_99_batch_dims_0"), val = tensor(0)]; tensor gather_99_validate_indices_0 = const()[name = tensor("gather_99_validate_indices_0"), val = tensor(false)]; tensor var_1242_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1242_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_99_to_uint16 = const()[name = tensor("select_99_to_uint16"), val = tensor(0)]; tensor var_1242_shape_cast_fp16_to_uint16 = cast(dtype = var_1242_shape_cast_fp16_to_uint16_dtype_0, x = var_1242_shape_cast_fp16)[name = tensor("cast_181")]; tensor gather_99_cast_uint16 = gather(axis = gather_99_axis_0, batch_dims = gather_99_batch_dims_0, indices = select_99_to_uint16, validate_indices = gather_99_validate_indices_0, x = var_1242_shape_cast_fp16_to_uint16)[name = tensor("gather_99_cast_uint16")]; tensor gather_99_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_99_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_12_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_12_cast_fp16, cond = mask0_4)[name = tensor("scores0_12_cast_fp16")]; tensor var_1245_cast_fp16 = softmax(axis = var_21, x = scores0_12_cast_fp16)[name = tensor("op_1245_cast_fp16")]; tensor input_85_cast_fp16 = select(a = var_8_to_fp16, b = var_1245_cast_fp16, cond = mask0_4)[name = tensor("input_85_cast_fp16")]; tensor x2_12_transpose_x_0 = const()[name = tensor("x2_12_transpose_x_0"), val = tensor(false)]; tensor x2_12_transpose_y_0 = const()[name = tensor("x2_12_transpose_y_0"), val = tensor(false)]; tensor x2_12_cast_fp16 = matmul(transpose_x = x2_12_transpose_x_0, transpose_y = x2_12_transpose_y_0, x = input_85_cast_fp16, y = value_12_cast_fp16)[name = tensor("x2_12_cast_fp16")]; tensor var_1249_perm_0 = const()[name = tensor("op_1249_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_65_axis_0 = const()[name = tensor("concat_65_axis_0"), val = tensor(0)]; tensor concat_65_interleave_0 = const()[name = tensor("concat_65_interleave_0"), val = tensor(false)]; tensor gather_99_cast_uint16_to_int32 = cast(dtype = gather_99_cast_uint16_to_int32_dtype_0, x = gather_99_cast_uint16)[name = tensor("cast_180")]; tensor concat_65 = concat(axis = concat_65_axis_0, interleave = concat_65_interleave_0, values = (gather_99_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_65")]; tensor var_1249_cast_fp16 = transpose(perm = var_1249_perm_0, x = x2_12_cast_fp16)[name = tensor("transpose_434")]; tensor input0_75_cast_fp16 = reshape(shape = concat_65, x = var_1249_cast_fp16)[name = tensor("input0_75_cast_fp16")]; tensor encoder_layers_5_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76694080))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77218432))), name = tensor("encoder_layers_5_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_52_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_self_attn_linear_out_weight_to_fp16_palettized, x = input0_75_cast_fp16)[name = tensor("linear_52_cast_fp16")]; tensor input0_77_cast_fp16 = add(x = input_83_cast_fp16, y = linear_52_cast_fp16)[name = tensor("input0_77_cast_fp16")]; tensor x_95_axes_0 = const()[name = tensor("x_95_axes_0"), val = tensor([-1])]; tensor encoder_layers_5_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_5_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77218560)))]; tensor encoder_layers_5_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_5_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77220672)))]; tensor x_95_cast_fp16 = layer_norm(axes = x_95_axes_0, beta = encoder_layers_5_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_5_norm_conv_weight_to_fp16, x = input0_77_cast_fp16)[name = tensor("x_95_cast_fp16")]; tensor input_87_perm_0 = const()[name = tensor("input_87_perm_0"), val = tensor([0, 2, 1])]; tensor input0_79_pad_type_0 = const()[name = tensor("input0_79_pad_type_0"), val = tensor("valid")]; tensor input0_79_strides_0 = const()[name = tensor("input0_79_strides_0"), val = tensor([1])]; tensor input0_79_pad_0 = const()[name = tensor("input0_79_pad_0"), val = tensor([0, 0])]; tensor input0_79_dilations_0 = const()[name = tensor("input0_79_dilations_0"), val = tensor([1])]; tensor input0_79_groups_0 = const()[name = tensor("input0_79_groups_0"), val = tensor(1)]; tensor encoder_layers_5_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77222784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78271424))), name = tensor("encoder_layers_5_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_87_cast_fp16 = transpose(perm = input_87_perm_0, x = x_95_cast_fp16)[name = tensor("transpose_433")]; tensor input0_79_cast_fp16 = conv(dilations = input0_79_dilations_0, groups = input0_79_groups_0, pad = input0_79_pad_0, pad_type = input0_79_pad_type_0, strides = input0_79_strides_0, weight = encoder_layers_5_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_87_cast_fp16)[name = tensor("input0_79_cast_fp16")]; tensor x_97_split_num_splits_0 = const()[name = tensor("x_97_split_num_splits_0"), val = tensor(2)]; tensor x_97_split_axis_0 = const()[name = tensor("x_97_split_axis_0"), val = tensor(1)]; tensor x_97_split_cast_fp16_0, tensor x_97_split_cast_fp16_1 = split(axis = x_97_split_axis_0, num_splits = x_97_split_num_splits_0, x = input0_79_cast_fp16)[name = tensor("x_97_split_cast_fp16")]; tensor x_97_split_1_sigmoid_cast_fp16 = sigmoid(x = x_97_split_cast_fp16_1)[name = tensor("x_97_split_1_sigmoid_cast_fp16")]; tensor x_97_cast_fp16 = mul(x = x_97_split_cast_fp16_0, y = x_97_split_1_sigmoid_cast_fp16)[name = tensor("x_97_cast_fp16")]; tensor input0_81_cast_fp16 = select(a = var_8_to_fp16, b = x_97_cast_fp16, cond = var_457)[name = tensor("input0_81_cast_fp16")]; tensor input0_83_pad_0 = const()[name = tensor("input0_83_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_83_mode_0 = const()[name = tensor("input0_83_mode_0"), val = tensor("constant")]; tensor const_22_to_fp16 = const()[name = tensor("const_22_to_fp16"), val = tensor(0x0p+0)]; tensor input0_83_cast_fp16 = pad(constant_val = const_22_to_fp16, mode = input0_83_mode_0, pad = input0_83_pad_0, x = input0_81_cast_fp16)[name = tensor("input0_83_cast_fp16")]; tensor input1_26_pad_type_0 = const()[name = tensor("input1_26_pad_type_0"), val = tensor("valid")]; tensor input1_26_groups_0 = const()[name = tensor("input1_26_groups_0"), val = tensor(1024)]; tensor input1_26_strides_0 = const()[name = tensor("input1_26_strides_0"), val = tensor([1])]; tensor input1_26_pad_0 = const()[name = tensor("input1_26_pad_0"), val = tensor([0, 0])]; tensor input1_26_dilations_0 = const()[name = tensor("input1_26_dilations_0"), val = tensor([1])]; tensor const_69_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78271552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78276224))), name = tensor("const_69_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_70_to_fp16 = const()[name = tensor("const_70_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78276352)))]; tensor input_89_cast_fp16 = conv(bias = const_70_to_fp16, dilations = input1_26_dilations_0, groups = input1_26_groups_0, pad = input1_26_pad_0, pad_type = input1_26_pad_type_0, strides = input1_26_strides_0, weight = const_69_to_fp16_palettized, x = input0_83_cast_fp16)[name = tensor("input_89_cast_fp16")]; tensor var_1287_cast_fp16 = silu(x = input_89_cast_fp16)[name = tensor("op_1287_cast_fp16")]; tensor x_99_pad_type_0 = const()[name = tensor("x_99_pad_type_0"), val = tensor("valid")]; tensor x_99_strides_0 = const()[name = tensor("x_99_strides_0"), val = tensor([1])]; tensor x_99_pad_0 = const()[name = tensor("x_99_pad_0"), val = tensor([0, 0])]; tensor x_99_dilations_0 = const()[name = tensor("x_99_dilations_0"), val = tensor([1])]; tensor x_99_groups_0 = const()[name = tensor("x_99_groups_0"), val = tensor(1)]; tensor encoder_layers_5_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78278464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78802816))), name = tensor("encoder_layers_5_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_99_cast_fp16 = conv(dilations = x_99_dilations_0, groups = x_99_groups_0, pad = x_99_pad_0, pad_type = x_99_pad_type_0, strides = x_99_strides_0, weight = encoder_layers_5_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1287_cast_fp16)[name = tensor("x_99_cast_fp16")]; tensor var_1294_perm_0 = const()[name = tensor("op_1294_perm_0"), val = tensor([0, 2, 1])]; tensor var_1294_cast_fp16 = transpose(perm = var_1294_perm_0, x = x_99_cast_fp16)[name = tensor("transpose_432")]; tensor input1_28_cast_fp16 = add(x = input0_77_cast_fp16, y = var_1294_cast_fp16)[name = tensor("input1_28_cast_fp16")]; tensor input0_85_axes_0 = const()[name = tensor("input0_85_axes_0"), val = tensor([-1])]; tensor encoder_layers_5_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_5_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78802944)))]; tensor encoder_layers_5_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_5_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78805056)))]; tensor input0_85_cast_fp16 = layer_norm(axes = input0_85_axes_0, beta = encoder_layers_5_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_5_norm_feed_forward2_weight_to_fp16, x = input1_28_cast_fp16)[name = tensor("input0_85_cast_fp16")]; tensor encoder_layers_5_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78807168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80904384))), name = tensor("encoder_layers_5_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_53_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_5_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_85_cast_fp16)[name = tensor("linear_53_cast_fp16")]; tensor var_1305_cast_fp16 = silu(x = linear_53_cast_fp16)[name = tensor("op_1305_cast_fp16")]; tensor encoder_layers_5_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80904512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83001728))), name = tensor("encoder_layers_5_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_54_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_5_feed_forward2_linear2_weight_to_fp16_palettized, x = var_1305_cast_fp16)[name = tensor("linear_54_cast_fp16")]; tensor var_1310_to_fp16 = const()[name = tensor("op_1310_to_fp16"), val = tensor(0x1p-1)]; tensor var_1311_cast_fp16 = mul(x = linear_54_cast_fp16, y = var_1310_to_fp16)[name = tensor("op_1311_cast_fp16")]; tensor input2_14_cast_fp16 = add(x = input1_28_cast_fp16, y = var_1311_cast_fp16)[name = tensor("input2_14_cast_fp16")]; tensor input0_87_axes_0 = const()[name = tensor("input0_87_axes_0"), val = tensor([-1])]; tensor encoder_layers_5_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_5_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83001856)))]; tensor encoder_layers_5_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_5_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83003968)))]; tensor input0_87_cast_fp16 = layer_norm(axes = input0_87_axes_0, beta = encoder_layers_5_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_5_norm_out_weight_to_fp16, x = input2_14_cast_fp16)[name = tensor("input0_87_cast_fp16")]; tensor input_93_axes_0 = const()[name = tensor("input_93_axes_0"), val = tensor([-1])]; tensor encoder_layers_6_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_6_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83006080)))]; tensor encoder_layers_6_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_6_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83008192)))]; tensor input_93_cast_fp16 = layer_norm(axes = input_93_axes_0, beta = encoder_layers_6_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_6_norm_feed_forward1_weight_to_fp16, x = input0_87_cast_fp16)[name = tensor("input_93_cast_fp16")]; tensor encoder_layers_6_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83010304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85107520))), name = tensor("encoder_layers_6_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_55_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_6_feed_forward1_linear1_weight_to_fp16_palettized, x = input_93_cast_fp16)[name = tensor("linear_55_cast_fp16")]; tensor var_1334_cast_fp16 = silu(x = linear_55_cast_fp16)[name = tensor("op_1334_cast_fp16")]; tensor encoder_layers_6_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85107648))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87204864))), name = tensor("encoder_layers_6_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_56_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1334_cast_fp16)[name = tensor("linear_56_cast_fp16")]; tensor var_1339_to_fp16 = const()[name = tensor("op_1339_to_fp16"), val = tensor(0x1p-1)]; tensor var_1340_cast_fp16 = mul(x = linear_56_cast_fp16, y = var_1339_to_fp16)[name = tensor("op_1340_cast_fp16")]; tensor input_97_cast_fp16 = add(x = input0_87_cast_fp16, y = var_1340_cast_fp16)[name = tensor("input_97_cast_fp16")]; tensor query_14_axes_0 = const()[name = tensor("query_14_axes_0"), val = tensor([-1])]; tensor encoder_layers_6_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_6_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87204992)))]; tensor encoder_layers_6_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_6_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87207104)))]; tensor query_14_cast_fp16 = layer_norm(axes = query_14_axes_0, beta = encoder_layers_6_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_6_norm_self_att_weight_to_fp16, x = input_97_cast_fp16)[name = tensor("query_14_cast_fp16")]; tensor var_1353_shape_cast_fp16 = shape(x = query_14_cast_fp16)[name = tensor("op_1353_shape_cast_fp16")]; tensor gather_100_axis_0 = const()[name = tensor("gather_100_axis_0"), val = tensor(0)]; tensor gather_100_batch_dims_0 = const()[name = tensor("gather_100_batch_dims_0"), val = tensor(0)]; tensor gather_100_validate_indices_0 = const()[name = tensor("gather_100_validate_indices_0"), val = tensor(false)]; tensor var_1353_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1353_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_100_to_uint16 = const()[name = tensor("select_100_to_uint16"), val = tensor(0)]; tensor var_1353_shape_cast_fp16_to_uint16 = cast(dtype = var_1353_shape_cast_fp16_to_uint16_dtype_0, x = var_1353_shape_cast_fp16)[name = tensor("cast_179")]; tensor gather_100_cast_uint16 = gather(axis = gather_100_axis_0, batch_dims = gather_100_batch_dims_0, indices = select_100_to_uint16, validate_indices = gather_100_validate_indices_0, x = var_1353_shape_cast_fp16_to_uint16)[name = tensor("gather_100_cast_uint16")]; tensor gather_100_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_100_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_6_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87209216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87733568))), name = tensor("encoder_layers_6_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_57_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_self_attn_linear_q_weight_to_fp16_palettized, x = query_14_cast_fp16)[name = tensor("linear_57_cast_fp16")]; tensor concat_66_axis_0 = const()[name = tensor("concat_66_axis_0"), val = tensor(0)]; tensor concat_66_interleave_0 = const()[name = tensor("concat_66_interleave_0"), val = tensor(false)]; tensor gather_100_cast_uint16_to_int32 = cast(dtype = gather_100_cast_uint16_to_int32_dtype_0, x = gather_100_cast_uint16)[name = tensor("cast_178")]; tensor concat_66 = concat(axis = concat_66_axis_0, interleave = concat_66_interleave_0, values = (gather_100_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_66")]; tensor q_14_cast_fp16 = reshape(shape = concat_66, x = linear_57_cast_fp16)[name = tensor("q_14_cast_fp16")]; tensor encoder_layers_6_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87733696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88258048))), name = tensor("encoder_layers_6_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_58_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_self_attn_linear_k_weight_to_fp16_palettized, x = query_14_cast_fp16)[name = tensor("linear_58_cast_fp16")]; tensor k_14_cast_fp16 = reshape(shape = concat_66, x = linear_58_cast_fp16)[name = tensor("k_14_cast_fp16")]; tensor encoder_layers_6_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88258176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88782528))), name = tensor("encoder_layers_6_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_59_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_self_attn_linear_v_weight_to_fp16_palettized, x = query_14_cast_fp16)[name = tensor("linear_59_cast_fp16")]; tensor v_14_cast_fp16 = reshape(shape = concat_66, x = linear_59_cast_fp16)[name = tensor("v_14_cast_fp16")]; tensor value_14_perm_0 = const()[name = tensor("value_14_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_6_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88782656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89307008))), name = tensor("encoder_layers_6_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_60_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_60_cast_fp16")]; tensor var_1373 = const()[name = tensor("op_1373"), val = tensor([1, -1, 8, 128])]; tensor p_14_cast_fp16 = reshape(shape = var_1373, x = linear_60_cast_fp16)[name = tensor("p_14_cast_fp16")]; tensor encoder_layers_6_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_6_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89307136)))]; tensor var_1376_cast_fp16 = add(x = q_14_cast_fp16, y = encoder_layers_6_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1376_cast_fp16")]; tensor encoder_layers_6_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_6_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89309248)))]; tensor var_1378_cast_fp16 = add(x = q_14_cast_fp16, y = encoder_layers_6_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1378_cast_fp16")]; tensor x_107_transpose_x_0 = const()[name = tensor("x_107_transpose_x_0"), val = tensor(false)]; tensor x_107_transpose_y_0 = const()[name = tensor("x_107_transpose_y_0"), val = tensor(false)]; tensor transpose_216_perm_0 = const()[name = tensor("transpose_216_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_217_perm_0 = const()[name = tensor("transpose_217_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_217 = transpose(perm = transpose_217_perm_0, x = p_14_cast_fp16)[name = tensor("transpose_430")]; tensor transpose_216 = transpose(perm = transpose_216_perm_0, x = var_1378_cast_fp16)[name = tensor("transpose_431")]; tensor x_107_cast_fp16 = matmul(transpose_x = x_107_transpose_x_0, transpose_y = x_107_transpose_y_0, x = transpose_216, y = transpose_217)[name = tensor("x_107_cast_fp16")]; tensor var_1382_shape_cast_fp16 = shape(x = x_107_cast_fp16)[name = tensor("op_1382_shape_cast_fp16")]; tensor gather_102_axis_0 = const()[name = tensor("gather_102_axis_0"), val = tensor(0)]; tensor gather_102_batch_dims_0 = const()[name = tensor("gather_102_batch_dims_0"), val = tensor(0)]; tensor gather_102_validate_indices_0 = const()[name = tensor("gather_102_validate_indices_0"), val = tensor(false)]; tensor var_1382_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1382_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_102_to_uint16 = const()[name = tensor("select_102_to_uint16"), val = tensor(0)]; tensor var_1382_shape_cast_fp16_to_uint16 = cast(dtype = var_1382_shape_cast_fp16_to_uint16_dtype_0, x = var_1382_shape_cast_fp16)[name = tensor("cast_177")]; tensor gather_102_cast_uint16 = gather(axis = gather_102_axis_0, batch_dims = gather_102_batch_dims_0, indices = select_102_to_uint16, validate_indices = gather_102_validate_indices_0, x = var_1382_shape_cast_fp16_to_uint16)[name = tensor("gather_102_cast_uint16")]; tensor gather_102_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_102_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_103 = const()[name = tensor("gather_103"), val = tensor(8)]; tensor gather_104_axis_0 = const()[name = tensor("gather_104_axis_0"), val = tensor(0)]; tensor gather_104_batch_dims_0 = const()[name = tensor("gather_104_batch_dims_0"), val = tensor(0)]; tensor gather_104_validate_indices_0 = const()[name = tensor("gather_104_validate_indices_0"), val = tensor(false)]; tensor select_104_to_uint16 = const()[name = tensor("select_104_to_uint16"), val = tensor(2)]; tensor gather_104_cast_uint16 = gather(axis = gather_104_axis_0, batch_dims = gather_104_batch_dims_0, indices = select_104_to_uint16, validate_indices = gather_104_validate_indices_0, x = var_1382_shape_cast_fp16_to_uint16)[name = tensor("gather_104_cast_uint16")]; tensor gather_104_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_104_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_105_axis_0 = const()[name = tensor("gather_105_axis_0"), val = tensor(0)]; tensor gather_105_batch_dims_0 = const()[name = tensor("gather_105_batch_dims_0"), val = tensor(0)]; tensor gather_105_validate_indices_0 = const()[name = tensor("gather_105_validate_indices_0"), val = tensor(false)]; tensor select_105_to_uint16 = const()[name = tensor("select_105_to_uint16"), val = tensor(3)]; tensor gather_105_cast_uint16 = gather(axis = gather_105_axis_0, batch_dims = gather_105_batch_dims_0, indices = select_105_to_uint16, validate_indices = gather_105_validate_indices_0, x = var_1382_shape_cast_fp16_to_uint16)[name = tensor("gather_105_cast_uint16")]; tensor gather_105_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_105_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_16_pad_0 = const()[name = tensor("x0_16_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_16_mode_0 = const()[name = tensor("x0_16_mode_0"), val = tensor("constant")]; tensor const_23_to_fp16 = const()[name = tensor("const_23_to_fp16"), val = tensor(0x0p+0)]; tensor x0_16_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = x0_16_mode_0, pad = x0_16_pad_0, x = x_107_cast_fp16)[name = tensor("x0_16_cast_fp16")]; tensor concat_69_axis_0 = const()[name = tensor("concat_69_axis_0"), val = tensor(0)]; tensor concat_69_interleave_0 = const()[name = tensor("concat_69_interleave_0"), val = tensor(false)]; tensor gather_102_cast_uint16_to_int32 = cast(dtype = gather_102_cast_uint16_to_int32_dtype_0, x = gather_102_cast_uint16)[name = tensor("cast_175")]; tensor gather_104_cast_uint16_to_int32 = cast(dtype = gather_104_cast_uint16_to_int32_dtype_0, x = gather_104_cast_uint16)[name = tensor("cast_176")]; tensor concat_69 = concat(axis = concat_69_axis_0, interleave = concat_69_interleave_0, values = (gather_102_cast_uint16_to_int32, gather_103, var_21, gather_104_cast_uint16_to_int32))[name = tensor("concat_69")]; tensor x1_14_cast_fp16 = reshape(shape = concat_69, x = x0_16_cast_fp16)[name = tensor("x1_14_cast_fp16")]; tensor var_1392_begin_0 = const()[name = tensor("op_1392_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1392_end_0 = const()[name = tensor("op_1392_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_1392_end_mask_0 = const()[name = tensor("op_1392_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1392_cast_fp16 = slice_by_index(begin = var_1392_begin_0, end = var_1392_end_0, end_mask = var_1392_end_mask_0, x = x1_14_cast_fp16)[name = tensor("op_1392_cast_fp16")]; tensor concat_70_axis_0 = const()[name = tensor("concat_70_axis_0"), val = tensor(0)]; tensor concat_70_interleave_0 = const()[name = tensor("concat_70_interleave_0"), val = tensor(false)]; tensor gather_105_cast_uint16_to_int32 = cast(dtype = gather_105_cast_uint16_to_int32_dtype_0, x = gather_105_cast_uint16)[name = tensor("cast_174")]; tensor concat_70 = concat(axis = concat_70_axis_0, interleave = concat_70_interleave_0, values = (gather_102_cast_uint16_to_int32, gather_103, gather_104_cast_uint16_to_int32, gather_105_cast_uint16_to_int32))[name = tensor("concat_70")]; tensor matrix_bd_14_cast_fp16 = reshape(shape = concat_70, x = var_1392_cast_fp16)[name = tensor("matrix_bd_14_cast_fp16")]; tensor matrix_ac_14_transpose_x_0 = const()[name = tensor("matrix_ac_14_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_14_transpose_y_0 = const()[name = tensor("matrix_ac_14_transpose_y_0"), val = tensor(false)]; tensor transpose_218_perm_0 = const()[name = tensor("transpose_218_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_219_perm_0 = const()[name = tensor("transpose_219_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_219 = transpose(perm = transpose_219_perm_0, x = k_14_cast_fp16)[name = tensor("transpose_428")]; tensor transpose_218 = transpose(perm = transpose_218_perm_0, x = var_1376_cast_fp16)[name = tensor("transpose_429")]; tensor matrix_ac_14_cast_fp16 = matmul(transpose_x = matrix_ac_14_transpose_x_0, transpose_y = matrix_ac_14_transpose_y_0, x = transpose_218, y = transpose_219)[name = tensor("matrix_ac_14_cast_fp16")]; tensor var_1397_shape_cast_fp16 = shape(x = matrix_ac_14_cast_fp16)[name = tensor("op_1397_shape_cast_fp16")]; tensor gather_106_axis_0 = const()[name = tensor("gather_106_axis_0"), val = tensor(0)]; tensor gather_106_batch_dims_0 = const()[name = tensor("gather_106_batch_dims_0"), val = tensor(0)]; tensor gather_106_validate_indices_0 = const()[name = tensor("gather_106_validate_indices_0"), val = tensor(false)]; tensor var_1397_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1397_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_106_to_uint16 = const()[name = tensor("select_106_to_uint16"), val = tensor(3)]; tensor var_1397_shape_cast_fp16_to_uint16 = cast(dtype = var_1397_shape_cast_fp16_to_uint16_dtype_0, x = var_1397_shape_cast_fp16)[name = tensor("cast_173")]; tensor gather_106_cast_uint16 = gather(axis = gather_106_axis_0, batch_dims = gather_106_batch_dims_0, indices = select_106_to_uint16, validate_indices = gather_106_validate_indices_0, x = var_1397_shape_cast_fp16_to_uint16)[name = tensor("gather_106_cast_uint16")]; tensor gather_106_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_106_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_71_values0_0 = const()[name = tensor("concat_71_values0_0"), val = tensor(0)]; tensor concat_71_values1_0 = const()[name = tensor("concat_71_values1_0"), val = tensor(8)]; tensor concat_71_values2_0 = const()[name = tensor("concat_71_values2_0"), val = tensor(0)]; tensor concat_71_axis_0 = const()[name = tensor("concat_71_axis_0"), val = tensor(0)]; tensor concat_71_interleave_0 = const()[name = tensor("concat_71_interleave_0"), val = tensor(false)]; tensor gather_106_cast_uint16_to_int32 = cast(dtype = gather_106_cast_uint16_to_int32_dtype_0, x = gather_106_cast_uint16)[name = tensor("cast_172")]; tensor concat_71 = concat(axis = concat_71_axis_0, interleave = concat_71_interleave_0, values = (concat_71_values0_0, concat_71_values1_0, concat_71_values2_0, gather_106_cast_uint16_to_int32))[name = tensor("concat_71")]; tensor matrix_bd0_14_begin_0 = const()[name = tensor("matrix_bd0_14_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_14_end_mask_0 = const()[name = tensor("matrix_bd0_14_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_14_cast_fp16 = slice_by_index(begin = matrix_bd0_14_begin_0, end = concat_71, end_mask = matrix_bd0_14_end_mask_0, x = matrix_bd_14_cast_fp16)[name = tensor("matrix_bd0_14_cast_fp16")]; tensor var_1402_cast_fp16 = add(x = matrix_ac_14_cast_fp16, y = matrix_bd0_14_cast_fp16)[name = tensor("op_1402_cast_fp16")]; tensor _inversed_scores_14_y_0_to_fp16 = const()[name = tensor("_inversed_scores_14_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_14_cast_fp16 = mul(x = var_1402_cast_fp16, y = _inversed_scores_14_y_0_to_fp16)[name = tensor("_inversed_scores_14_cast_fp16")]; tensor value_14_cast_fp16 = transpose(perm = value_14_perm_0, x = v_14_cast_fp16)[name = tensor("transpose_427")]; tensor var_1405_shape_cast_fp16 = shape(x = value_14_cast_fp16)[name = tensor("op_1405_shape_cast_fp16")]; tensor gather_107_axis_0 = const()[name = tensor("gather_107_axis_0"), val = tensor(0)]; tensor gather_107_batch_dims_0 = const()[name = tensor("gather_107_batch_dims_0"), val = tensor(0)]; tensor gather_107_validate_indices_0 = const()[name = tensor("gather_107_validate_indices_0"), val = tensor(false)]; tensor var_1405_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1405_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_107_to_uint16 = const()[name = tensor("select_107_to_uint16"), val = tensor(0)]; tensor var_1405_shape_cast_fp16_to_uint16 = cast(dtype = var_1405_shape_cast_fp16_to_uint16_dtype_0, x = var_1405_shape_cast_fp16)[name = tensor("cast_171")]; tensor gather_107_cast_uint16 = gather(axis = gather_107_axis_0, batch_dims = gather_107_batch_dims_0, indices = select_107_to_uint16, validate_indices = gather_107_validate_indices_0, x = var_1405_shape_cast_fp16_to_uint16)[name = tensor("gather_107_cast_uint16")]; tensor gather_107_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_107_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_14_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_14_cast_fp16, cond = mask0_4)[name = tensor("scores0_14_cast_fp16")]; tensor var_1408_cast_fp16 = softmax(axis = var_21, x = scores0_14_cast_fp16)[name = tensor("op_1408_cast_fp16")]; tensor input_99_cast_fp16 = select(a = var_8_to_fp16, b = var_1408_cast_fp16, cond = mask0_4)[name = tensor("input_99_cast_fp16")]; tensor x2_14_transpose_x_0 = const()[name = tensor("x2_14_transpose_x_0"), val = tensor(false)]; tensor x2_14_transpose_y_0 = const()[name = tensor("x2_14_transpose_y_0"), val = tensor(false)]; tensor x2_14_cast_fp16 = matmul(transpose_x = x2_14_transpose_x_0, transpose_y = x2_14_transpose_y_0, x = input_99_cast_fp16, y = value_14_cast_fp16)[name = tensor("x2_14_cast_fp16")]; tensor var_1412_perm_0 = const()[name = tensor("op_1412_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_72_axis_0 = const()[name = tensor("concat_72_axis_0"), val = tensor(0)]; tensor concat_72_interleave_0 = const()[name = tensor("concat_72_interleave_0"), val = tensor(false)]; tensor gather_107_cast_uint16_to_int32 = cast(dtype = gather_107_cast_uint16_to_int32_dtype_0, x = gather_107_cast_uint16)[name = tensor("cast_170")]; tensor concat_72 = concat(axis = concat_72_axis_0, interleave = concat_72_interleave_0, values = (gather_107_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_72")]; tensor var_1412_cast_fp16 = transpose(perm = var_1412_perm_0, x = x2_14_cast_fp16)[name = tensor("transpose_426")]; tensor input0_89_cast_fp16 = reshape(shape = concat_72, x = var_1412_cast_fp16)[name = tensor("input0_89_cast_fp16")]; tensor encoder_layers_6_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89311360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89835712))), name = tensor("encoder_layers_6_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_61_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_self_attn_linear_out_weight_to_fp16_palettized, x = input0_89_cast_fp16)[name = tensor("linear_61_cast_fp16")]; tensor input0_91_cast_fp16 = add(x = input_97_cast_fp16, y = linear_61_cast_fp16)[name = tensor("input0_91_cast_fp16")]; tensor x_111_axes_0 = const()[name = tensor("x_111_axes_0"), val = tensor([-1])]; tensor encoder_layers_6_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_6_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89835840)))]; tensor encoder_layers_6_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_6_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89837952)))]; tensor x_111_cast_fp16 = layer_norm(axes = x_111_axes_0, beta = encoder_layers_6_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_6_norm_conv_weight_to_fp16, x = input0_91_cast_fp16)[name = tensor("x_111_cast_fp16")]; tensor input_101_perm_0 = const()[name = tensor("input_101_perm_0"), val = tensor([0, 2, 1])]; tensor input0_93_pad_type_0 = const()[name = tensor("input0_93_pad_type_0"), val = tensor("valid")]; tensor input0_93_strides_0 = const()[name = tensor("input0_93_strides_0"), val = tensor([1])]; tensor input0_93_pad_0 = const()[name = tensor("input0_93_pad_0"), val = tensor([0, 0])]; tensor input0_93_dilations_0 = const()[name = tensor("input0_93_dilations_0"), val = tensor([1])]; tensor input0_93_groups_0 = const()[name = tensor("input0_93_groups_0"), val = tensor(1)]; tensor encoder_layers_6_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89840064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90888704))), name = tensor("encoder_layers_6_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_101_cast_fp16 = transpose(perm = input_101_perm_0, x = x_111_cast_fp16)[name = tensor("transpose_425")]; tensor input0_93_cast_fp16 = conv(dilations = input0_93_dilations_0, groups = input0_93_groups_0, pad = input0_93_pad_0, pad_type = input0_93_pad_type_0, strides = input0_93_strides_0, weight = encoder_layers_6_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_101_cast_fp16)[name = tensor("input0_93_cast_fp16")]; tensor x_113_split_num_splits_0 = const()[name = tensor("x_113_split_num_splits_0"), val = tensor(2)]; tensor x_113_split_axis_0 = const()[name = tensor("x_113_split_axis_0"), val = tensor(1)]; tensor x_113_split_cast_fp16_0, tensor x_113_split_cast_fp16_1 = split(axis = x_113_split_axis_0, num_splits = x_113_split_num_splits_0, x = input0_93_cast_fp16)[name = tensor("x_113_split_cast_fp16")]; tensor x_113_split_1_sigmoid_cast_fp16 = sigmoid(x = x_113_split_cast_fp16_1)[name = tensor("x_113_split_1_sigmoid_cast_fp16")]; tensor x_113_cast_fp16 = mul(x = x_113_split_cast_fp16_0, y = x_113_split_1_sigmoid_cast_fp16)[name = tensor("x_113_cast_fp16")]; tensor input0_95_cast_fp16 = select(a = var_8_to_fp16, b = x_113_cast_fp16, cond = var_457)[name = tensor("input0_95_cast_fp16")]; tensor input0_97_pad_0 = const()[name = tensor("input0_97_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_97_mode_0 = const()[name = tensor("input0_97_mode_0"), val = tensor("constant")]; tensor const_24_to_fp16 = const()[name = tensor("const_24_to_fp16"), val = tensor(0x0p+0)]; tensor input0_97_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input0_97_mode_0, pad = input0_97_pad_0, x = input0_95_cast_fp16)[name = tensor("input0_97_cast_fp16")]; tensor input1_30_pad_type_0 = const()[name = tensor("input1_30_pad_type_0"), val = tensor("valid")]; tensor input1_30_groups_0 = const()[name = tensor("input1_30_groups_0"), val = tensor(1024)]; tensor input1_30_strides_0 = const()[name = tensor("input1_30_strides_0"), val = tensor([1])]; tensor input1_30_pad_0 = const()[name = tensor("input1_30_pad_0"), val = tensor([0, 0])]; tensor input1_30_dilations_0 = const()[name = tensor("input1_30_dilations_0"), val = tensor([1])]; tensor const_71_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90888832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90893504))), name = tensor("const_71_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90893632)))]; tensor input_103_cast_fp16 = conv(bias = const_72_to_fp16, dilations = input1_30_dilations_0, groups = input1_30_groups_0, pad = input1_30_pad_0, pad_type = input1_30_pad_type_0, strides = input1_30_strides_0, weight = const_71_to_fp16_palettized, x = input0_97_cast_fp16)[name = tensor("input_103_cast_fp16")]; tensor var_1450_cast_fp16 = silu(x = input_103_cast_fp16)[name = tensor("op_1450_cast_fp16")]; tensor x_115_pad_type_0 = const()[name = tensor("x_115_pad_type_0"), val = tensor("valid")]; tensor x_115_strides_0 = const()[name = tensor("x_115_strides_0"), val = tensor([1])]; tensor x_115_pad_0 = const()[name = tensor("x_115_pad_0"), val = tensor([0, 0])]; tensor x_115_dilations_0 = const()[name = tensor("x_115_dilations_0"), val = tensor([1])]; tensor x_115_groups_0 = const()[name = tensor("x_115_groups_0"), val = tensor(1)]; tensor encoder_layers_6_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90895744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91420096))), name = tensor("encoder_layers_6_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_115_cast_fp16 = conv(dilations = x_115_dilations_0, groups = x_115_groups_0, pad = x_115_pad_0, pad_type = x_115_pad_type_0, strides = x_115_strides_0, weight = encoder_layers_6_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1450_cast_fp16)[name = tensor("x_115_cast_fp16")]; tensor var_1457_perm_0 = const()[name = tensor("op_1457_perm_0"), val = tensor([0, 2, 1])]; tensor var_1457_cast_fp16 = transpose(perm = var_1457_perm_0, x = x_115_cast_fp16)[name = tensor("transpose_424")]; tensor input1_32_cast_fp16 = add(x = input0_91_cast_fp16, y = var_1457_cast_fp16)[name = tensor("input1_32_cast_fp16")]; tensor input0_99_axes_0 = const()[name = tensor("input0_99_axes_0"), val = tensor([-1])]; tensor encoder_layers_6_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_6_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91420224)))]; tensor encoder_layers_6_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_6_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91422336)))]; tensor input0_99_cast_fp16 = layer_norm(axes = input0_99_axes_0, beta = encoder_layers_6_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_6_norm_feed_forward2_weight_to_fp16, x = input1_32_cast_fp16)[name = tensor("input0_99_cast_fp16")]; tensor encoder_layers_6_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91424448))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93521664))), name = tensor("encoder_layers_6_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_62_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_6_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_99_cast_fp16)[name = tensor("linear_62_cast_fp16")]; tensor var_1468_cast_fp16 = silu(x = linear_62_cast_fp16)[name = tensor("op_1468_cast_fp16")]; tensor encoder_layers_6_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93521792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95619008))), name = tensor("encoder_layers_6_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_63_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_6_feed_forward2_linear2_weight_to_fp16_palettized, x = var_1468_cast_fp16)[name = tensor("linear_63_cast_fp16")]; tensor var_1473_to_fp16 = const()[name = tensor("op_1473_to_fp16"), val = tensor(0x1p-1)]; tensor var_1474_cast_fp16 = mul(x = linear_63_cast_fp16, y = var_1473_to_fp16)[name = tensor("op_1474_cast_fp16")]; tensor input2_16_cast_fp16 = add(x = input1_32_cast_fp16, y = var_1474_cast_fp16)[name = tensor("input2_16_cast_fp16")]; tensor input0_101_axes_0 = const()[name = tensor("input0_101_axes_0"), val = tensor([-1])]; tensor encoder_layers_6_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_6_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95619136)))]; tensor encoder_layers_6_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_6_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95621248)))]; tensor input0_101_cast_fp16 = layer_norm(axes = input0_101_axes_0, beta = encoder_layers_6_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_6_norm_out_weight_to_fp16, x = input2_16_cast_fp16)[name = tensor("input0_101_cast_fp16")]; tensor input_107_axes_0 = const()[name = tensor("input_107_axes_0"), val = tensor([-1])]; tensor encoder_layers_7_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_7_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95623360)))]; tensor encoder_layers_7_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_7_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95625472)))]; tensor input_107_cast_fp16 = layer_norm(axes = input_107_axes_0, beta = encoder_layers_7_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_7_norm_feed_forward1_weight_to_fp16, x = input0_101_cast_fp16)[name = tensor("input_107_cast_fp16")]; tensor encoder_layers_7_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95627584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97724800))), name = tensor("encoder_layers_7_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_64_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_7_feed_forward1_linear1_weight_to_fp16_palettized, x = input_107_cast_fp16)[name = tensor("linear_64_cast_fp16")]; tensor var_1497_cast_fp16 = silu(x = linear_64_cast_fp16)[name = tensor("op_1497_cast_fp16")]; tensor encoder_layers_7_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97724928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99822144))), name = tensor("encoder_layers_7_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_65_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1497_cast_fp16)[name = tensor("linear_65_cast_fp16")]; tensor var_1502_to_fp16 = const()[name = tensor("op_1502_to_fp16"), val = tensor(0x1p-1)]; tensor var_1503_cast_fp16 = mul(x = linear_65_cast_fp16, y = var_1502_to_fp16)[name = tensor("op_1503_cast_fp16")]; tensor input_111_cast_fp16 = add(x = input0_101_cast_fp16, y = var_1503_cast_fp16)[name = tensor("input_111_cast_fp16")]; tensor query_16_axes_0 = const()[name = tensor("query_16_axes_0"), val = tensor([-1])]; tensor encoder_layers_7_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_7_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99822272)))]; tensor encoder_layers_7_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_7_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99824384)))]; tensor query_16_cast_fp16 = layer_norm(axes = query_16_axes_0, beta = encoder_layers_7_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_7_norm_self_att_weight_to_fp16, x = input_111_cast_fp16)[name = tensor("query_16_cast_fp16")]; tensor var_1516_shape_cast_fp16 = shape(x = query_16_cast_fp16)[name = tensor("op_1516_shape_cast_fp16")]; tensor gather_108_axis_0 = const()[name = tensor("gather_108_axis_0"), val = tensor(0)]; tensor gather_108_batch_dims_0 = const()[name = tensor("gather_108_batch_dims_0"), val = tensor(0)]; tensor gather_108_validate_indices_0 = const()[name = tensor("gather_108_validate_indices_0"), val = tensor(false)]; tensor var_1516_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1516_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_108_to_uint16 = const()[name = tensor("select_108_to_uint16"), val = tensor(0)]; tensor var_1516_shape_cast_fp16_to_uint16 = cast(dtype = var_1516_shape_cast_fp16_to_uint16_dtype_0, x = var_1516_shape_cast_fp16)[name = tensor("cast_169")]; tensor gather_108_cast_uint16 = gather(axis = gather_108_axis_0, batch_dims = gather_108_batch_dims_0, indices = select_108_to_uint16, validate_indices = gather_108_validate_indices_0, x = var_1516_shape_cast_fp16_to_uint16)[name = tensor("gather_108_cast_uint16")]; tensor gather_108_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_108_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_7_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99826496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100350848))), name = tensor("encoder_layers_7_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_66_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_self_attn_linear_q_weight_to_fp16_palettized, x = query_16_cast_fp16)[name = tensor("linear_66_cast_fp16")]; tensor concat_73_axis_0 = const()[name = tensor("concat_73_axis_0"), val = tensor(0)]; tensor concat_73_interleave_0 = const()[name = tensor("concat_73_interleave_0"), val = tensor(false)]; tensor gather_108_cast_uint16_to_int32 = cast(dtype = gather_108_cast_uint16_to_int32_dtype_0, x = gather_108_cast_uint16)[name = tensor("cast_168")]; tensor concat_73 = concat(axis = concat_73_axis_0, interleave = concat_73_interleave_0, values = (gather_108_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_73")]; tensor q_16_cast_fp16 = reshape(shape = concat_73, x = linear_66_cast_fp16)[name = tensor("q_16_cast_fp16")]; tensor encoder_layers_7_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100350976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100875328))), name = tensor("encoder_layers_7_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_67_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_self_attn_linear_k_weight_to_fp16_palettized, x = query_16_cast_fp16)[name = tensor("linear_67_cast_fp16")]; tensor k_16_cast_fp16 = reshape(shape = concat_73, x = linear_67_cast_fp16)[name = tensor("k_16_cast_fp16")]; tensor encoder_layers_7_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100875456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101399808))), name = tensor("encoder_layers_7_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_68_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_self_attn_linear_v_weight_to_fp16_palettized, x = query_16_cast_fp16)[name = tensor("linear_68_cast_fp16")]; tensor v_16_cast_fp16 = reshape(shape = concat_73, x = linear_68_cast_fp16)[name = tensor("v_16_cast_fp16")]; tensor value_16_perm_0 = const()[name = tensor("value_16_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_7_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101399936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101924288))), name = tensor("encoder_layers_7_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_69_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_69_cast_fp16")]; tensor var_1536 = const()[name = tensor("op_1536"), val = tensor([1, -1, 8, 128])]; tensor p_16_cast_fp16 = reshape(shape = var_1536, x = linear_69_cast_fp16)[name = tensor("p_16_cast_fp16")]; tensor encoder_layers_7_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_7_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101924416)))]; tensor var_1539_cast_fp16 = add(x = q_16_cast_fp16, y = encoder_layers_7_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1539_cast_fp16")]; tensor encoder_layers_7_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_7_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101926528)))]; tensor var_1541_cast_fp16 = add(x = q_16_cast_fp16, y = encoder_layers_7_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1541_cast_fp16")]; tensor x_123_transpose_x_0 = const()[name = tensor("x_123_transpose_x_0"), val = tensor(false)]; tensor x_123_transpose_y_0 = const()[name = tensor("x_123_transpose_y_0"), val = tensor(false)]; tensor transpose_220_perm_0 = const()[name = tensor("transpose_220_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_221_perm_0 = const()[name = tensor("transpose_221_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_221 = transpose(perm = transpose_221_perm_0, x = p_16_cast_fp16)[name = tensor("transpose_422")]; tensor transpose_220 = transpose(perm = transpose_220_perm_0, x = var_1541_cast_fp16)[name = tensor("transpose_423")]; tensor x_123_cast_fp16 = matmul(transpose_x = x_123_transpose_x_0, transpose_y = x_123_transpose_y_0, x = transpose_220, y = transpose_221)[name = tensor("x_123_cast_fp16")]; tensor var_1545_shape_cast_fp16 = shape(x = x_123_cast_fp16)[name = tensor("op_1545_shape_cast_fp16")]; tensor gather_110_axis_0 = const()[name = tensor("gather_110_axis_0"), val = tensor(0)]; tensor gather_110_batch_dims_0 = const()[name = tensor("gather_110_batch_dims_0"), val = tensor(0)]; tensor gather_110_validate_indices_0 = const()[name = tensor("gather_110_validate_indices_0"), val = tensor(false)]; tensor var_1545_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1545_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_110_to_uint16 = const()[name = tensor("select_110_to_uint16"), val = tensor(0)]; tensor var_1545_shape_cast_fp16_to_uint16 = cast(dtype = var_1545_shape_cast_fp16_to_uint16_dtype_0, x = var_1545_shape_cast_fp16)[name = tensor("cast_167")]; tensor gather_110_cast_uint16 = gather(axis = gather_110_axis_0, batch_dims = gather_110_batch_dims_0, indices = select_110_to_uint16, validate_indices = gather_110_validate_indices_0, x = var_1545_shape_cast_fp16_to_uint16)[name = tensor("gather_110_cast_uint16")]; tensor gather_110_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_110_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_111 = const()[name = tensor("gather_111"), val = tensor(8)]; tensor gather_112_axis_0 = const()[name = tensor("gather_112_axis_0"), val = tensor(0)]; tensor gather_112_batch_dims_0 = const()[name = tensor("gather_112_batch_dims_0"), val = tensor(0)]; tensor gather_112_validate_indices_0 = const()[name = tensor("gather_112_validate_indices_0"), val = tensor(false)]; tensor select_112_to_uint16 = const()[name = tensor("select_112_to_uint16"), val = tensor(2)]; tensor gather_112_cast_uint16 = gather(axis = gather_112_axis_0, batch_dims = gather_112_batch_dims_0, indices = select_112_to_uint16, validate_indices = gather_112_validate_indices_0, x = var_1545_shape_cast_fp16_to_uint16)[name = tensor("gather_112_cast_uint16")]; tensor gather_112_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_112_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_113_axis_0 = const()[name = tensor("gather_113_axis_0"), val = tensor(0)]; tensor gather_113_batch_dims_0 = const()[name = tensor("gather_113_batch_dims_0"), val = tensor(0)]; tensor gather_113_validate_indices_0 = const()[name = tensor("gather_113_validate_indices_0"), val = tensor(false)]; tensor select_113_to_uint16 = const()[name = tensor("select_113_to_uint16"), val = tensor(3)]; tensor gather_113_cast_uint16 = gather(axis = gather_113_axis_0, batch_dims = gather_113_batch_dims_0, indices = select_113_to_uint16, validate_indices = gather_113_validate_indices_0, x = var_1545_shape_cast_fp16_to_uint16)[name = tensor("gather_113_cast_uint16")]; tensor gather_113_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_113_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_18_pad_0 = const()[name = tensor("x0_18_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_18_mode_0 = const()[name = tensor("x0_18_mode_0"), val = tensor("constant")]; tensor const_25_to_fp16 = const()[name = tensor("const_25_to_fp16"), val = tensor(0x0p+0)]; tensor x0_18_cast_fp16 = pad(constant_val = const_25_to_fp16, mode = x0_18_mode_0, pad = x0_18_pad_0, x = x_123_cast_fp16)[name = tensor("x0_18_cast_fp16")]; tensor concat_76_axis_0 = const()[name = tensor("concat_76_axis_0"), val = tensor(0)]; tensor concat_76_interleave_0 = const()[name = tensor("concat_76_interleave_0"), val = tensor(false)]; tensor gather_110_cast_uint16_to_int32 = cast(dtype = gather_110_cast_uint16_to_int32_dtype_0, x = gather_110_cast_uint16)[name = tensor("cast_165")]; tensor gather_112_cast_uint16_to_int32 = cast(dtype = gather_112_cast_uint16_to_int32_dtype_0, x = gather_112_cast_uint16)[name = tensor("cast_166")]; tensor concat_76 = concat(axis = concat_76_axis_0, interleave = concat_76_interleave_0, values = (gather_110_cast_uint16_to_int32, gather_111, var_21, gather_112_cast_uint16_to_int32))[name = tensor("concat_76")]; tensor x1_16_cast_fp16 = reshape(shape = concat_76, x = x0_18_cast_fp16)[name = tensor("x1_16_cast_fp16")]; tensor var_1555_begin_0 = const()[name = tensor("op_1555_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1555_end_0 = const()[name = tensor("op_1555_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_1555_end_mask_0 = const()[name = tensor("op_1555_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1555_cast_fp16 = slice_by_index(begin = var_1555_begin_0, end = var_1555_end_0, end_mask = var_1555_end_mask_0, x = x1_16_cast_fp16)[name = tensor("op_1555_cast_fp16")]; tensor concat_77_axis_0 = const()[name = tensor("concat_77_axis_0"), val = tensor(0)]; tensor concat_77_interleave_0 = const()[name = tensor("concat_77_interleave_0"), val = tensor(false)]; tensor gather_113_cast_uint16_to_int32 = cast(dtype = gather_113_cast_uint16_to_int32_dtype_0, x = gather_113_cast_uint16)[name = tensor("cast_164")]; tensor concat_77 = concat(axis = concat_77_axis_0, interleave = concat_77_interleave_0, values = (gather_110_cast_uint16_to_int32, gather_111, gather_112_cast_uint16_to_int32, gather_113_cast_uint16_to_int32))[name = tensor("concat_77")]; tensor matrix_bd_16_cast_fp16 = reshape(shape = concat_77, x = var_1555_cast_fp16)[name = tensor("matrix_bd_16_cast_fp16")]; tensor matrix_ac_16_transpose_x_0 = const()[name = tensor("matrix_ac_16_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_16_transpose_y_0 = const()[name = tensor("matrix_ac_16_transpose_y_0"), val = tensor(false)]; tensor transpose_222_perm_0 = const()[name = tensor("transpose_222_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_223_perm_0 = const()[name = tensor("transpose_223_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_223 = transpose(perm = transpose_223_perm_0, x = k_16_cast_fp16)[name = tensor("transpose_420")]; tensor transpose_222 = transpose(perm = transpose_222_perm_0, x = var_1539_cast_fp16)[name = tensor("transpose_421")]; tensor matrix_ac_16_cast_fp16 = matmul(transpose_x = matrix_ac_16_transpose_x_0, transpose_y = matrix_ac_16_transpose_y_0, x = transpose_222, y = transpose_223)[name = tensor("matrix_ac_16_cast_fp16")]; tensor var_1560_shape_cast_fp16 = shape(x = matrix_ac_16_cast_fp16)[name = tensor("op_1560_shape_cast_fp16")]; tensor gather_114_axis_0 = const()[name = tensor("gather_114_axis_0"), val = tensor(0)]; tensor gather_114_batch_dims_0 = const()[name = tensor("gather_114_batch_dims_0"), val = tensor(0)]; tensor gather_114_validate_indices_0 = const()[name = tensor("gather_114_validate_indices_0"), val = tensor(false)]; tensor var_1560_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1560_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_114_to_uint16 = const()[name = tensor("select_114_to_uint16"), val = tensor(3)]; tensor var_1560_shape_cast_fp16_to_uint16 = cast(dtype = var_1560_shape_cast_fp16_to_uint16_dtype_0, x = var_1560_shape_cast_fp16)[name = tensor("cast_163")]; tensor gather_114_cast_uint16 = gather(axis = gather_114_axis_0, batch_dims = gather_114_batch_dims_0, indices = select_114_to_uint16, validate_indices = gather_114_validate_indices_0, x = var_1560_shape_cast_fp16_to_uint16)[name = tensor("gather_114_cast_uint16")]; tensor gather_114_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_114_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_78_values0_0 = const()[name = tensor("concat_78_values0_0"), val = tensor(0)]; tensor concat_78_values1_0 = const()[name = tensor("concat_78_values1_0"), val = tensor(8)]; tensor concat_78_values2_0 = const()[name = tensor("concat_78_values2_0"), val = tensor(0)]; tensor concat_78_axis_0 = const()[name = tensor("concat_78_axis_0"), val = tensor(0)]; tensor concat_78_interleave_0 = const()[name = tensor("concat_78_interleave_0"), val = tensor(false)]; tensor gather_114_cast_uint16_to_int32 = cast(dtype = gather_114_cast_uint16_to_int32_dtype_0, x = gather_114_cast_uint16)[name = tensor("cast_162")]; tensor concat_78 = concat(axis = concat_78_axis_0, interleave = concat_78_interleave_0, values = (concat_78_values0_0, concat_78_values1_0, concat_78_values2_0, gather_114_cast_uint16_to_int32))[name = tensor("concat_78")]; tensor matrix_bd0_16_begin_0 = const()[name = tensor("matrix_bd0_16_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_16_end_mask_0 = const()[name = tensor("matrix_bd0_16_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_16_cast_fp16 = slice_by_index(begin = matrix_bd0_16_begin_0, end = concat_78, end_mask = matrix_bd0_16_end_mask_0, x = matrix_bd_16_cast_fp16)[name = tensor("matrix_bd0_16_cast_fp16")]; tensor var_1565_cast_fp16 = add(x = matrix_ac_16_cast_fp16, y = matrix_bd0_16_cast_fp16)[name = tensor("op_1565_cast_fp16")]; tensor _inversed_scores_16_y_0_to_fp16 = const()[name = tensor("_inversed_scores_16_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_16_cast_fp16 = mul(x = var_1565_cast_fp16, y = _inversed_scores_16_y_0_to_fp16)[name = tensor("_inversed_scores_16_cast_fp16")]; tensor value_16_cast_fp16 = transpose(perm = value_16_perm_0, x = v_16_cast_fp16)[name = tensor("transpose_419")]; tensor var_1568_shape_cast_fp16 = shape(x = value_16_cast_fp16)[name = tensor("op_1568_shape_cast_fp16")]; tensor gather_115_axis_0 = const()[name = tensor("gather_115_axis_0"), val = tensor(0)]; tensor gather_115_batch_dims_0 = const()[name = tensor("gather_115_batch_dims_0"), val = tensor(0)]; tensor gather_115_validate_indices_0 = const()[name = tensor("gather_115_validate_indices_0"), val = tensor(false)]; tensor var_1568_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1568_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_115_to_uint16 = const()[name = tensor("select_115_to_uint16"), val = tensor(0)]; tensor var_1568_shape_cast_fp16_to_uint16 = cast(dtype = var_1568_shape_cast_fp16_to_uint16_dtype_0, x = var_1568_shape_cast_fp16)[name = tensor("cast_161")]; tensor gather_115_cast_uint16 = gather(axis = gather_115_axis_0, batch_dims = gather_115_batch_dims_0, indices = select_115_to_uint16, validate_indices = gather_115_validate_indices_0, x = var_1568_shape_cast_fp16_to_uint16)[name = tensor("gather_115_cast_uint16")]; tensor gather_115_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_115_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_16_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_16_cast_fp16, cond = mask0_4)[name = tensor("scores0_16_cast_fp16")]; tensor var_1571_cast_fp16 = softmax(axis = var_21, x = scores0_16_cast_fp16)[name = tensor("op_1571_cast_fp16")]; tensor input_113_cast_fp16 = select(a = var_8_to_fp16, b = var_1571_cast_fp16, cond = mask0_4)[name = tensor("input_113_cast_fp16")]; tensor x2_16_transpose_x_0 = const()[name = tensor("x2_16_transpose_x_0"), val = tensor(false)]; tensor x2_16_transpose_y_0 = const()[name = tensor("x2_16_transpose_y_0"), val = tensor(false)]; tensor x2_16_cast_fp16 = matmul(transpose_x = x2_16_transpose_x_0, transpose_y = x2_16_transpose_y_0, x = input_113_cast_fp16, y = value_16_cast_fp16)[name = tensor("x2_16_cast_fp16")]; tensor var_1575_perm_0 = const()[name = tensor("op_1575_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_79_axis_0 = const()[name = tensor("concat_79_axis_0"), val = tensor(0)]; tensor concat_79_interleave_0 = const()[name = tensor("concat_79_interleave_0"), val = tensor(false)]; tensor gather_115_cast_uint16_to_int32 = cast(dtype = gather_115_cast_uint16_to_int32_dtype_0, x = gather_115_cast_uint16)[name = tensor("cast_160")]; tensor concat_79 = concat(axis = concat_79_axis_0, interleave = concat_79_interleave_0, values = (gather_115_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_79")]; tensor var_1575_cast_fp16 = transpose(perm = var_1575_perm_0, x = x2_16_cast_fp16)[name = tensor("transpose_418")]; tensor input0_103_cast_fp16 = reshape(shape = concat_79, x = var_1575_cast_fp16)[name = tensor("input0_103_cast_fp16")]; tensor encoder_layers_7_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101928640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102452992))), name = tensor("encoder_layers_7_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_70_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_self_attn_linear_out_weight_to_fp16_palettized, x = input0_103_cast_fp16)[name = tensor("linear_70_cast_fp16")]; tensor input0_105_cast_fp16 = add(x = input_111_cast_fp16, y = linear_70_cast_fp16)[name = tensor("input0_105_cast_fp16")]; tensor x_127_axes_0 = const()[name = tensor("x_127_axes_0"), val = tensor([-1])]; tensor encoder_layers_7_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_7_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102453120)))]; tensor encoder_layers_7_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_7_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102455232)))]; tensor x_127_cast_fp16 = layer_norm(axes = x_127_axes_0, beta = encoder_layers_7_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_7_norm_conv_weight_to_fp16, x = input0_105_cast_fp16)[name = tensor("x_127_cast_fp16")]; tensor input_115_perm_0 = const()[name = tensor("input_115_perm_0"), val = tensor([0, 2, 1])]; tensor input0_107_pad_type_0 = const()[name = tensor("input0_107_pad_type_0"), val = tensor("valid")]; tensor input0_107_strides_0 = const()[name = tensor("input0_107_strides_0"), val = tensor([1])]; tensor input0_107_pad_0 = const()[name = tensor("input0_107_pad_0"), val = tensor([0, 0])]; tensor input0_107_dilations_0 = const()[name = tensor("input0_107_dilations_0"), val = tensor([1])]; tensor input0_107_groups_0 = const()[name = tensor("input0_107_groups_0"), val = tensor(1)]; tensor encoder_layers_7_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102457344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103505984))), name = tensor("encoder_layers_7_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_115_cast_fp16 = transpose(perm = input_115_perm_0, x = x_127_cast_fp16)[name = tensor("transpose_417")]; tensor input0_107_cast_fp16 = conv(dilations = input0_107_dilations_0, groups = input0_107_groups_0, pad = input0_107_pad_0, pad_type = input0_107_pad_type_0, strides = input0_107_strides_0, weight = encoder_layers_7_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_115_cast_fp16)[name = tensor("input0_107_cast_fp16")]; tensor x_129_split_num_splits_0 = const()[name = tensor("x_129_split_num_splits_0"), val = tensor(2)]; tensor x_129_split_axis_0 = const()[name = tensor("x_129_split_axis_0"), val = tensor(1)]; tensor x_129_split_cast_fp16_0, tensor x_129_split_cast_fp16_1 = split(axis = x_129_split_axis_0, num_splits = x_129_split_num_splits_0, x = input0_107_cast_fp16)[name = tensor("x_129_split_cast_fp16")]; tensor x_129_split_1_sigmoid_cast_fp16 = sigmoid(x = x_129_split_cast_fp16_1)[name = tensor("x_129_split_1_sigmoid_cast_fp16")]; tensor x_129_cast_fp16 = mul(x = x_129_split_cast_fp16_0, y = x_129_split_1_sigmoid_cast_fp16)[name = tensor("x_129_cast_fp16")]; tensor input0_109_cast_fp16 = select(a = var_8_to_fp16, b = x_129_cast_fp16, cond = var_457)[name = tensor("input0_109_cast_fp16")]; tensor input0_111_pad_0 = const()[name = tensor("input0_111_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_111_mode_0 = const()[name = tensor("input0_111_mode_0"), val = tensor("constant")]; tensor const_26_to_fp16 = const()[name = tensor("const_26_to_fp16"), val = tensor(0x0p+0)]; tensor input0_111_cast_fp16 = pad(constant_val = const_26_to_fp16, mode = input0_111_mode_0, pad = input0_111_pad_0, x = input0_109_cast_fp16)[name = tensor("input0_111_cast_fp16")]; tensor input1_34_pad_type_0 = const()[name = tensor("input1_34_pad_type_0"), val = tensor("valid")]; tensor input1_34_groups_0 = const()[name = tensor("input1_34_groups_0"), val = tensor(1024)]; tensor input1_34_strides_0 = const()[name = tensor("input1_34_strides_0"), val = tensor([1])]; tensor input1_34_pad_0 = const()[name = tensor("input1_34_pad_0"), val = tensor([0, 0])]; tensor input1_34_dilations_0 = const()[name = tensor("input1_34_dilations_0"), val = tensor([1])]; tensor const_73_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103506112))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103510784))), name = tensor("const_73_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_74_to_fp16 = const()[name = tensor("const_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103510912)))]; tensor input_117_cast_fp16 = conv(bias = const_74_to_fp16, dilations = input1_34_dilations_0, groups = input1_34_groups_0, pad = input1_34_pad_0, pad_type = input1_34_pad_type_0, strides = input1_34_strides_0, weight = const_73_to_fp16_palettized, x = input0_111_cast_fp16)[name = tensor("input_117_cast_fp16")]; tensor var_1613_cast_fp16 = silu(x = input_117_cast_fp16)[name = tensor("op_1613_cast_fp16")]; tensor x_131_pad_type_0 = const()[name = tensor("x_131_pad_type_0"), val = tensor("valid")]; tensor x_131_strides_0 = const()[name = tensor("x_131_strides_0"), val = tensor([1])]; tensor x_131_pad_0 = const()[name = tensor("x_131_pad_0"), val = tensor([0, 0])]; tensor x_131_dilations_0 = const()[name = tensor("x_131_dilations_0"), val = tensor([1])]; tensor x_131_groups_0 = const()[name = tensor("x_131_groups_0"), val = tensor(1)]; tensor encoder_layers_7_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103513024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104037376))), name = tensor("encoder_layers_7_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_131_cast_fp16 = conv(dilations = x_131_dilations_0, groups = x_131_groups_0, pad = x_131_pad_0, pad_type = x_131_pad_type_0, strides = x_131_strides_0, weight = encoder_layers_7_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1613_cast_fp16)[name = tensor("x_131_cast_fp16")]; tensor var_1620_perm_0 = const()[name = tensor("op_1620_perm_0"), val = tensor([0, 2, 1])]; tensor var_1620_cast_fp16 = transpose(perm = var_1620_perm_0, x = x_131_cast_fp16)[name = tensor("transpose_416")]; tensor input1_36_cast_fp16 = add(x = input0_105_cast_fp16, y = var_1620_cast_fp16)[name = tensor("input1_36_cast_fp16")]; tensor input0_113_axes_0 = const()[name = tensor("input0_113_axes_0"), val = tensor([-1])]; tensor encoder_layers_7_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_7_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104037504)))]; tensor encoder_layers_7_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_7_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104039616)))]; tensor input0_113_cast_fp16 = layer_norm(axes = input0_113_axes_0, beta = encoder_layers_7_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_7_norm_feed_forward2_weight_to_fp16, x = input1_36_cast_fp16)[name = tensor("input0_113_cast_fp16")]; tensor encoder_layers_7_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104041728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106138944))), name = tensor("encoder_layers_7_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_71_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_7_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_113_cast_fp16)[name = tensor("linear_71_cast_fp16")]; tensor var_1631_cast_fp16 = silu(x = linear_71_cast_fp16)[name = tensor("op_1631_cast_fp16")]; tensor encoder_layers_7_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106139072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108236288))), name = tensor("encoder_layers_7_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_72_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_7_feed_forward2_linear2_weight_to_fp16_palettized, x = var_1631_cast_fp16)[name = tensor("linear_72_cast_fp16")]; tensor var_1636_to_fp16 = const()[name = tensor("op_1636_to_fp16"), val = tensor(0x1p-1)]; tensor var_1637_cast_fp16 = mul(x = linear_72_cast_fp16, y = var_1636_to_fp16)[name = tensor("op_1637_cast_fp16")]; tensor input2_18_cast_fp16 = add(x = input1_36_cast_fp16, y = var_1637_cast_fp16)[name = tensor("input2_18_cast_fp16")]; tensor input0_115_axes_0 = const()[name = tensor("input0_115_axes_0"), val = tensor([-1])]; tensor encoder_layers_7_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_7_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108236416)))]; tensor encoder_layers_7_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_7_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108238528)))]; tensor input0_115_cast_fp16 = layer_norm(axes = input0_115_axes_0, beta = encoder_layers_7_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_7_norm_out_weight_to_fp16, x = input2_18_cast_fp16)[name = tensor("input0_115_cast_fp16")]; tensor input_121_axes_0 = const()[name = tensor("input_121_axes_0"), val = tensor([-1])]; tensor encoder_layers_8_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_8_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108240640)))]; tensor encoder_layers_8_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_8_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108242752)))]; tensor input_121_cast_fp16 = layer_norm(axes = input_121_axes_0, beta = encoder_layers_8_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_8_norm_feed_forward1_weight_to_fp16, x = input0_115_cast_fp16)[name = tensor("input_121_cast_fp16")]; tensor encoder_layers_8_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(108244864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110342080))), name = tensor("encoder_layers_8_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_73_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_8_feed_forward1_linear1_weight_to_fp16_palettized, x = input_121_cast_fp16)[name = tensor("linear_73_cast_fp16")]; tensor var_1660_cast_fp16 = silu(x = linear_73_cast_fp16)[name = tensor("op_1660_cast_fp16")]; tensor encoder_layers_8_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(110342208))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112439424))), name = tensor("encoder_layers_8_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_74_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1660_cast_fp16)[name = tensor("linear_74_cast_fp16")]; tensor var_1665_to_fp16 = const()[name = tensor("op_1665_to_fp16"), val = tensor(0x1p-1)]; tensor var_1666_cast_fp16 = mul(x = linear_74_cast_fp16, y = var_1665_to_fp16)[name = tensor("op_1666_cast_fp16")]; tensor input_125_cast_fp16 = add(x = input0_115_cast_fp16, y = var_1666_cast_fp16)[name = tensor("input_125_cast_fp16")]; tensor query_18_axes_0 = const()[name = tensor("query_18_axes_0"), val = tensor([-1])]; tensor encoder_layers_8_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_8_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112439552)))]; tensor encoder_layers_8_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_8_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112441664)))]; tensor query_18_cast_fp16 = layer_norm(axes = query_18_axes_0, beta = encoder_layers_8_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_8_norm_self_att_weight_to_fp16, x = input_125_cast_fp16)[name = tensor("query_18_cast_fp16")]; tensor var_1679_shape_cast_fp16 = shape(x = query_18_cast_fp16)[name = tensor("op_1679_shape_cast_fp16")]; tensor gather_116_axis_0 = const()[name = tensor("gather_116_axis_0"), val = tensor(0)]; tensor gather_116_batch_dims_0 = const()[name = tensor("gather_116_batch_dims_0"), val = tensor(0)]; tensor gather_116_validate_indices_0 = const()[name = tensor("gather_116_validate_indices_0"), val = tensor(false)]; tensor var_1679_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1679_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_116_to_uint16 = const()[name = tensor("select_116_to_uint16"), val = tensor(0)]; tensor var_1679_shape_cast_fp16_to_uint16 = cast(dtype = var_1679_shape_cast_fp16_to_uint16_dtype_0, x = var_1679_shape_cast_fp16)[name = tensor("cast_159")]; tensor gather_116_cast_uint16 = gather(axis = gather_116_axis_0, batch_dims = gather_116_batch_dims_0, indices = select_116_to_uint16, validate_indices = gather_116_validate_indices_0, x = var_1679_shape_cast_fp16_to_uint16)[name = tensor("gather_116_cast_uint16")]; tensor gather_116_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_116_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_8_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112443776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112968128))), name = tensor("encoder_layers_8_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_75_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_self_attn_linear_q_weight_to_fp16_palettized, x = query_18_cast_fp16)[name = tensor("linear_75_cast_fp16")]; tensor concat_80_axis_0 = const()[name = tensor("concat_80_axis_0"), val = tensor(0)]; tensor concat_80_interleave_0 = const()[name = tensor("concat_80_interleave_0"), val = tensor(false)]; tensor gather_116_cast_uint16_to_int32 = cast(dtype = gather_116_cast_uint16_to_int32_dtype_0, x = gather_116_cast_uint16)[name = tensor("cast_158")]; tensor concat_80 = concat(axis = concat_80_axis_0, interleave = concat_80_interleave_0, values = (gather_116_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_80")]; tensor q_18_cast_fp16 = reshape(shape = concat_80, x = linear_75_cast_fp16)[name = tensor("q_18_cast_fp16")]; tensor encoder_layers_8_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(112968256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113492608))), name = tensor("encoder_layers_8_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_76_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_self_attn_linear_k_weight_to_fp16_palettized, x = query_18_cast_fp16)[name = tensor("linear_76_cast_fp16")]; tensor k_18_cast_fp16 = reshape(shape = concat_80, x = linear_76_cast_fp16)[name = tensor("k_18_cast_fp16")]; tensor encoder_layers_8_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(113492736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114017088))), name = tensor("encoder_layers_8_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_77_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_self_attn_linear_v_weight_to_fp16_palettized, x = query_18_cast_fp16)[name = tensor("linear_77_cast_fp16")]; tensor v_18_cast_fp16 = reshape(shape = concat_80, x = linear_77_cast_fp16)[name = tensor("v_18_cast_fp16")]; tensor value_18_perm_0 = const()[name = tensor("value_18_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_8_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114017216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114541568))), name = tensor("encoder_layers_8_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_78_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_78_cast_fp16")]; tensor var_1699 = const()[name = tensor("op_1699"), val = tensor([1, -1, 8, 128])]; tensor p_18_cast_fp16 = reshape(shape = var_1699, x = linear_78_cast_fp16)[name = tensor("p_18_cast_fp16")]; tensor encoder_layers_8_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_8_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114541696)))]; tensor var_1702_cast_fp16 = add(x = q_18_cast_fp16, y = encoder_layers_8_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1702_cast_fp16")]; tensor encoder_layers_8_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_8_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114543808)))]; tensor var_1704_cast_fp16 = add(x = q_18_cast_fp16, y = encoder_layers_8_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1704_cast_fp16")]; tensor x_139_transpose_x_0 = const()[name = tensor("x_139_transpose_x_0"), val = tensor(false)]; tensor x_139_transpose_y_0 = const()[name = tensor("x_139_transpose_y_0"), val = tensor(false)]; tensor transpose_224_perm_0 = const()[name = tensor("transpose_224_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_225_perm_0 = const()[name = tensor("transpose_225_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_225 = transpose(perm = transpose_225_perm_0, x = p_18_cast_fp16)[name = tensor("transpose_414")]; tensor transpose_224 = transpose(perm = transpose_224_perm_0, x = var_1704_cast_fp16)[name = tensor("transpose_415")]; tensor x_139_cast_fp16 = matmul(transpose_x = x_139_transpose_x_0, transpose_y = x_139_transpose_y_0, x = transpose_224, y = transpose_225)[name = tensor("x_139_cast_fp16")]; tensor var_1708_shape_cast_fp16 = shape(x = x_139_cast_fp16)[name = tensor("op_1708_shape_cast_fp16")]; tensor gather_118_axis_0 = const()[name = tensor("gather_118_axis_0"), val = tensor(0)]; tensor gather_118_batch_dims_0 = const()[name = tensor("gather_118_batch_dims_0"), val = tensor(0)]; tensor gather_118_validate_indices_0 = const()[name = tensor("gather_118_validate_indices_0"), val = tensor(false)]; tensor var_1708_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1708_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_118_to_uint16 = const()[name = tensor("select_118_to_uint16"), val = tensor(0)]; tensor var_1708_shape_cast_fp16_to_uint16 = cast(dtype = var_1708_shape_cast_fp16_to_uint16_dtype_0, x = var_1708_shape_cast_fp16)[name = tensor("cast_157")]; tensor gather_118_cast_uint16 = gather(axis = gather_118_axis_0, batch_dims = gather_118_batch_dims_0, indices = select_118_to_uint16, validate_indices = gather_118_validate_indices_0, x = var_1708_shape_cast_fp16_to_uint16)[name = tensor("gather_118_cast_uint16")]; tensor gather_118_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_118_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_119 = const()[name = tensor("gather_119"), val = tensor(8)]; tensor gather_120_axis_0 = const()[name = tensor("gather_120_axis_0"), val = tensor(0)]; tensor gather_120_batch_dims_0 = const()[name = tensor("gather_120_batch_dims_0"), val = tensor(0)]; tensor gather_120_validate_indices_0 = const()[name = tensor("gather_120_validate_indices_0"), val = tensor(false)]; tensor select_120_to_uint16 = const()[name = tensor("select_120_to_uint16"), val = tensor(2)]; tensor gather_120_cast_uint16 = gather(axis = gather_120_axis_0, batch_dims = gather_120_batch_dims_0, indices = select_120_to_uint16, validate_indices = gather_120_validate_indices_0, x = var_1708_shape_cast_fp16_to_uint16)[name = tensor("gather_120_cast_uint16")]; tensor gather_120_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_120_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_121_axis_0 = const()[name = tensor("gather_121_axis_0"), val = tensor(0)]; tensor gather_121_batch_dims_0 = const()[name = tensor("gather_121_batch_dims_0"), val = tensor(0)]; tensor gather_121_validate_indices_0 = const()[name = tensor("gather_121_validate_indices_0"), val = tensor(false)]; tensor select_121_to_uint16 = const()[name = tensor("select_121_to_uint16"), val = tensor(3)]; tensor gather_121_cast_uint16 = gather(axis = gather_121_axis_0, batch_dims = gather_121_batch_dims_0, indices = select_121_to_uint16, validate_indices = gather_121_validate_indices_0, x = var_1708_shape_cast_fp16_to_uint16)[name = tensor("gather_121_cast_uint16")]; tensor gather_121_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_121_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_20_pad_0 = const()[name = tensor("x0_20_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_20_mode_0 = const()[name = tensor("x0_20_mode_0"), val = tensor("constant")]; tensor const_27_to_fp16 = const()[name = tensor("const_27_to_fp16"), val = tensor(0x0p+0)]; tensor x0_20_cast_fp16 = pad(constant_val = const_27_to_fp16, mode = x0_20_mode_0, pad = x0_20_pad_0, x = x_139_cast_fp16)[name = tensor("x0_20_cast_fp16")]; tensor concat_83_axis_0 = const()[name = tensor("concat_83_axis_0"), val = tensor(0)]; tensor concat_83_interleave_0 = const()[name = tensor("concat_83_interleave_0"), val = tensor(false)]; tensor gather_118_cast_uint16_to_int32 = cast(dtype = gather_118_cast_uint16_to_int32_dtype_0, x = gather_118_cast_uint16)[name = tensor("cast_155")]; tensor gather_120_cast_uint16_to_int32 = cast(dtype = gather_120_cast_uint16_to_int32_dtype_0, x = gather_120_cast_uint16)[name = tensor("cast_156")]; tensor concat_83 = concat(axis = concat_83_axis_0, interleave = concat_83_interleave_0, values = (gather_118_cast_uint16_to_int32, gather_119, var_21, gather_120_cast_uint16_to_int32))[name = tensor("concat_83")]; tensor x1_18_cast_fp16 = reshape(shape = concat_83, x = x0_20_cast_fp16)[name = tensor("x1_18_cast_fp16")]; tensor var_1718_begin_0 = const()[name = tensor("op_1718_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1718_end_0 = const()[name = tensor("op_1718_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_1718_end_mask_0 = const()[name = tensor("op_1718_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1718_cast_fp16 = slice_by_index(begin = var_1718_begin_0, end = var_1718_end_0, end_mask = var_1718_end_mask_0, x = x1_18_cast_fp16)[name = tensor("op_1718_cast_fp16")]; tensor concat_84_axis_0 = const()[name = tensor("concat_84_axis_0"), val = tensor(0)]; tensor concat_84_interleave_0 = const()[name = tensor("concat_84_interleave_0"), val = tensor(false)]; tensor gather_121_cast_uint16_to_int32 = cast(dtype = gather_121_cast_uint16_to_int32_dtype_0, x = gather_121_cast_uint16)[name = tensor("cast_154")]; tensor concat_84 = concat(axis = concat_84_axis_0, interleave = concat_84_interleave_0, values = (gather_118_cast_uint16_to_int32, gather_119, gather_120_cast_uint16_to_int32, gather_121_cast_uint16_to_int32))[name = tensor("concat_84")]; tensor matrix_bd_18_cast_fp16 = reshape(shape = concat_84, x = var_1718_cast_fp16)[name = tensor("matrix_bd_18_cast_fp16")]; tensor matrix_ac_18_transpose_x_0 = const()[name = tensor("matrix_ac_18_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_18_transpose_y_0 = const()[name = tensor("matrix_ac_18_transpose_y_0"), val = tensor(false)]; tensor transpose_226_perm_0 = const()[name = tensor("transpose_226_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_227_perm_0 = const()[name = tensor("transpose_227_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_227 = transpose(perm = transpose_227_perm_0, x = k_18_cast_fp16)[name = tensor("transpose_412")]; tensor transpose_226 = transpose(perm = transpose_226_perm_0, x = var_1702_cast_fp16)[name = tensor("transpose_413")]; tensor matrix_ac_18_cast_fp16 = matmul(transpose_x = matrix_ac_18_transpose_x_0, transpose_y = matrix_ac_18_transpose_y_0, x = transpose_226, y = transpose_227)[name = tensor("matrix_ac_18_cast_fp16")]; tensor var_1723_shape_cast_fp16 = shape(x = matrix_ac_18_cast_fp16)[name = tensor("op_1723_shape_cast_fp16")]; tensor gather_122_axis_0 = const()[name = tensor("gather_122_axis_0"), val = tensor(0)]; tensor gather_122_batch_dims_0 = const()[name = tensor("gather_122_batch_dims_0"), val = tensor(0)]; tensor gather_122_validate_indices_0 = const()[name = tensor("gather_122_validate_indices_0"), val = tensor(false)]; tensor var_1723_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1723_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_122_to_uint16 = const()[name = tensor("select_122_to_uint16"), val = tensor(3)]; tensor var_1723_shape_cast_fp16_to_uint16 = cast(dtype = var_1723_shape_cast_fp16_to_uint16_dtype_0, x = var_1723_shape_cast_fp16)[name = tensor("cast_153")]; tensor gather_122_cast_uint16 = gather(axis = gather_122_axis_0, batch_dims = gather_122_batch_dims_0, indices = select_122_to_uint16, validate_indices = gather_122_validate_indices_0, x = var_1723_shape_cast_fp16_to_uint16)[name = tensor("gather_122_cast_uint16")]; tensor gather_122_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_122_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_85_values0_0 = const()[name = tensor("concat_85_values0_0"), val = tensor(0)]; tensor concat_85_values1_0 = const()[name = tensor("concat_85_values1_0"), val = tensor(8)]; tensor concat_85_values2_0 = const()[name = tensor("concat_85_values2_0"), val = tensor(0)]; tensor concat_85_axis_0 = const()[name = tensor("concat_85_axis_0"), val = tensor(0)]; tensor concat_85_interleave_0 = const()[name = tensor("concat_85_interleave_0"), val = tensor(false)]; tensor gather_122_cast_uint16_to_int32 = cast(dtype = gather_122_cast_uint16_to_int32_dtype_0, x = gather_122_cast_uint16)[name = tensor("cast_152")]; tensor concat_85 = concat(axis = concat_85_axis_0, interleave = concat_85_interleave_0, values = (concat_85_values0_0, concat_85_values1_0, concat_85_values2_0, gather_122_cast_uint16_to_int32))[name = tensor("concat_85")]; tensor matrix_bd0_18_begin_0 = const()[name = tensor("matrix_bd0_18_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_18_end_mask_0 = const()[name = tensor("matrix_bd0_18_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_18_cast_fp16 = slice_by_index(begin = matrix_bd0_18_begin_0, end = concat_85, end_mask = matrix_bd0_18_end_mask_0, x = matrix_bd_18_cast_fp16)[name = tensor("matrix_bd0_18_cast_fp16")]; tensor var_1728_cast_fp16 = add(x = matrix_ac_18_cast_fp16, y = matrix_bd0_18_cast_fp16)[name = tensor("op_1728_cast_fp16")]; tensor _inversed_scores_18_y_0_to_fp16 = const()[name = tensor("_inversed_scores_18_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_18_cast_fp16 = mul(x = var_1728_cast_fp16, y = _inversed_scores_18_y_0_to_fp16)[name = tensor("_inversed_scores_18_cast_fp16")]; tensor value_18_cast_fp16 = transpose(perm = value_18_perm_0, x = v_18_cast_fp16)[name = tensor("transpose_411")]; tensor var_1731_shape_cast_fp16 = shape(x = value_18_cast_fp16)[name = tensor("op_1731_shape_cast_fp16")]; tensor gather_123_axis_0 = const()[name = tensor("gather_123_axis_0"), val = tensor(0)]; tensor gather_123_batch_dims_0 = const()[name = tensor("gather_123_batch_dims_0"), val = tensor(0)]; tensor gather_123_validate_indices_0 = const()[name = tensor("gather_123_validate_indices_0"), val = tensor(false)]; tensor var_1731_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1731_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_123_to_uint16 = const()[name = tensor("select_123_to_uint16"), val = tensor(0)]; tensor var_1731_shape_cast_fp16_to_uint16 = cast(dtype = var_1731_shape_cast_fp16_to_uint16_dtype_0, x = var_1731_shape_cast_fp16)[name = tensor("cast_151")]; tensor gather_123_cast_uint16 = gather(axis = gather_123_axis_0, batch_dims = gather_123_batch_dims_0, indices = select_123_to_uint16, validate_indices = gather_123_validate_indices_0, x = var_1731_shape_cast_fp16_to_uint16)[name = tensor("gather_123_cast_uint16")]; tensor gather_123_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_123_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_18_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_18_cast_fp16, cond = mask0_4)[name = tensor("scores0_18_cast_fp16")]; tensor var_1734_cast_fp16 = softmax(axis = var_21, x = scores0_18_cast_fp16)[name = tensor("op_1734_cast_fp16")]; tensor input_127_cast_fp16 = select(a = var_8_to_fp16, b = var_1734_cast_fp16, cond = mask0_4)[name = tensor("input_127_cast_fp16")]; tensor x2_18_transpose_x_0 = const()[name = tensor("x2_18_transpose_x_0"), val = tensor(false)]; tensor x2_18_transpose_y_0 = const()[name = tensor("x2_18_transpose_y_0"), val = tensor(false)]; tensor x2_18_cast_fp16 = matmul(transpose_x = x2_18_transpose_x_0, transpose_y = x2_18_transpose_y_0, x = input_127_cast_fp16, y = value_18_cast_fp16)[name = tensor("x2_18_cast_fp16")]; tensor var_1738_perm_0 = const()[name = tensor("op_1738_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_86_axis_0 = const()[name = tensor("concat_86_axis_0"), val = tensor(0)]; tensor concat_86_interleave_0 = const()[name = tensor("concat_86_interleave_0"), val = tensor(false)]; tensor gather_123_cast_uint16_to_int32 = cast(dtype = gather_123_cast_uint16_to_int32_dtype_0, x = gather_123_cast_uint16)[name = tensor("cast_150")]; tensor concat_86 = concat(axis = concat_86_axis_0, interleave = concat_86_interleave_0, values = (gather_123_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_86")]; tensor var_1738_cast_fp16 = transpose(perm = var_1738_perm_0, x = x2_18_cast_fp16)[name = tensor("transpose_410")]; tensor input0_117_cast_fp16 = reshape(shape = concat_86, x = var_1738_cast_fp16)[name = tensor("input0_117_cast_fp16")]; tensor encoder_layers_8_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(114545920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115070272))), name = tensor("encoder_layers_8_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_79_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_self_attn_linear_out_weight_to_fp16_palettized, x = input0_117_cast_fp16)[name = tensor("linear_79_cast_fp16")]; tensor input0_119_cast_fp16 = add(x = input_125_cast_fp16, y = linear_79_cast_fp16)[name = tensor("input0_119_cast_fp16")]; tensor x_143_axes_0 = const()[name = tensor("x_143_axes_0"), val = tensor([-1])]; tensor encoder_layers_8_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_8_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115070400)))]; tensor encoder_layers_8_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_8_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115072512)))]; tensor x_143_cast_fp16 = layer_norm(axes = x_143_axes_0, beta = encoder_layers_8_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_8_norm_conv_weight_to_fp16, x = input0_119_cast_fp16)[name = tensor("x_143_cast_fp16")]; tensor input_129_perm_0 = const()[name = tensor("input_129_perm_0"), val = tensor([0, 2, 1])]; tensor input0_121_pad_type_0 = const()[name = tensor("input0_121_pad_type_0"), val = tensor("valid")]; tensor input0_121_strides_0 = const()[name = tensor("input0_121_strides_0"), val = tensor([1])]; tensor input0_121_pad_0 = const()[name = tensor("input0_121_pad_0"), val = tensor([0, 0])]; tensor input0_121_dilations_0 = const()[name = tensor("input0_121_dilations_0"), val = tensor([1])]; tensor input0_121_groups_0 = const()[name = tensor("input0_121_groups_0"), val = tensor(1)]; tensor encoder_layers_8_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(115074624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116123264))), name = tensor("encoder_layers_8_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_129_cast_fp16 = transpose(perm = input_129_perm_0, x = x_143_cast_fp16)[name = tensor("transpose_409")]; tensor input0_121_cast_fp16 = conv(dilations = input0_121_dilations_0, groups = input0_121_groups_0, pad = input0_121_pad_0, pad_type = input0_121_pad_type_0, strides = input0_121_strides_0, weight = encoder_layers_8_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_129_cast_fp16)[name = tensor("input0_121_cast_fp16")]; tensor x_145_split_num_splits_0 = const()[name = tensor("x_145_split_num_splits_0"), val = tensor(2)]; tensor x_145_split_axis_0 = const()[name = tensor("x_145_split_axis_0"), val = tensor(1)]; tensor x_145_split_cast_fp16_0, tensor x_145_split_cast_fp16_1 = split(axis = x_145_split_axis_0, num_splits = x_145_split_num_splits_0, x = input0_121_cast_fp16)[name = tensor("x_145_split_cast_fp16")]; tensor x_145_split_1_sigmoid_cast_fp16 = sigmoid(x = x_145_split_cast_fp16_1)[name = tensor("x_145_split_1_sigmoid_cast_fp16")]; tensor x_145_cast_fp16 = mul(x = x_145_split_cast_fp16_0, y = x_145_split_1_sigmoid_cast_fp16)[name = tensor("x_145_cast_fp16")]; tensor input0_123_cast_fp16 = select(a = var_8_to_fp16, b = x_145_cast_fp16, cond = var_457)[name = tensor("input0_123_cast_fp16")]; tensor input0_125_pad_0 = const()[name = tensor("input0_125_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_125_mode_0 = const()[name = tensor("input0_125_mode_0"), val = tensor("constant")]; tensor const_28_to_fp16 = const()[name = tensor("const_28_to_fp16"), val = tensor(0x0p+0)]; tensor input0_125_cast_fp16 = pad(constant_val = const_28_to_fp16, mode = input0_125_mode_0, pad = input0_125_pad_0, x = input0_123_cast_fp16)[name = tensor("input0_125_cast_fp16")]; tensor input1_38_pad_type_0 = const()[name = tensor("input1_38_pad_type_0"), val = tensor("valid")]; tensor input1_38_groups_0 = const()[name = tensor("input1_38_groups_0"), val = tensor(1024)]; tensor input1_38_strides_0 = const()[name = tensor("input1_38_strides_0"), val = tensor([1])]; tensor input1_38_pad_0 = const()[name = tensor("input1_38_pad_0"), val = tensor([0, 0])]; tensor input1_38_dilations_0 = const()[name = tensor("input1_38_dilations_0"), val = tensor([1])]; tensor const_75_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116123392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116128064))), name = tensor("const_75_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_76_to_fp16 = const()[name = tensor("const_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116128192)))]; tensor input_131_cast_fp16 = conv(bias = const_76_to_fp16, dilations = input1_38_dilations_0, groups = input1_38_groups_0, pad = input1_38_pad_0, pad_type = input1_38_pad_type_0, strides = input1_38_strides_0, weight = const_75_to_fp16_palettized, x = input0_125_cast_fp16)[name = tensor("input_131_cast_fp16")]; tensor var_1776_cast_fp16 = silu(x = input_131_cast_fp16)[name = tensor("op_1776_cast_fp16")]; tensor x_147_pad_type_0 = const()[name = tensor("x_147_pad_type_0"), val = tensor("valid")]; tensor x_147_strides_0 = const()[name = tensor("x_147_strides_0"), val = tensor([1])]; tensor x_147_pad_0 = const()[name = tensor("x_147_pad_0"), val = tensor([0, 0])]; tensor x_147_dilations_0 = const()[name = tensor("x_147_dilations_0"), val = tensor([1])]; tensor x_147_groups_0 = const()[name = tensor("x_147_groups_0"), val = tensor(1)]; tensor encoder_layers_8_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116130304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116654656))), name = tensor("encoder_layers_8_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_147_cast_fp16 = conv(dilations = x_147_dilations_0, groups = x_147_groups_0, pad = x_147_pad_0, pad_type = x_147_pad_type_0, strides = x_147_strides_0, weight = encoder_layers_8_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1776_cast_fp16)[name = tensor("x_147_cast_fp16")]; tensor var_1783_perm_0 = const()[name = tensor("op_1783_perm_0"), val = tensor([0, 2, 1])]; tensor var_1783_cast_fp16 = transpose(perm = var_1783_perm_0, x = x_147_cast_fp16)[name = tensor("transpose_408")]; tensor input1_40_cast_fp16 = add(x = input0_119_cast_fp16, y = var_1783_cast_fp16)[name = tensor("input1_40_cast_fp16")]; tensor input0_127_axes_0 = const()[name = tensor("input0_127_axes_0"), val = tensor([-1])]; tensor encoder_layers_8_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_8_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116654784)))]; tensor encoder_layers_8_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_8_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116656896)))]; tensor input0_127_cast_fp16 = layer_norm(axes = input0_127_axes_0, beta = encoder_layers_8_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_8_norm_feed_forward2_weight_to_fp16, x = input1_40_cast_fp16)[name = tensor("input0_127_cast_fp16")]; tensor encoder_layers_8_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(116659008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118756224))), name = tensor("encoder_layers_8_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_80_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_8_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_127_cast_fp16)[name = tensor("linear_80_cast_fp16")]; tensor var_1794_cast_fp16 = silu(x = linear_80_cast_fp16)[name = tensor("op_1794_cast_fp16")]; tensor encoder_layers_8_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(118756352))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120853568))), name = tensor("encoder_layers_8_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_81_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_8_feed_forward2_linear2_weight_to_fp16_palettized, x = var_1794_cast_fp16)[name = tensor("linear_81_cast_fp16")]; tensor var_1799_to_fp16 = const()[name = tensor("op_1799_to_fp16"), val = tensor(0x1p-1)]; tensor var_1800_cast_fp16 = mul(x = linear_81_cast_fp16, y = var_1799_to_fp16)[name = tensor("op_1800_cast_fp16")]; tensor input2_20_cast_fp16 = add(x = input1_40_cast_fp16, y = var_1800_cast_fp16)[name = tensor("input2_20_cast_fp16")]; tensor input0_129_axes_0 = const()[name = tensor("input0_129_axes_0"), val = tensor([-1])]; tensor encoder_layers_8_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_8_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120853696)))]; tensor encoder_layers_8_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_8_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120855808)))]; tensor input0_129_cast_fp16 = layer_norm(axes = input0_129_axes_0, beta = encoder_layers_8_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_8_norm_out_weight_to_fp16, x = input2_20_cast_fp16)[name = tensor("input0_129_cast_fp16")]; tensor input_135_axes_0 = const()[name = tensor("input_135_axes_0"), val = tensor([-1])]; tensor encoder_layers_9_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_9_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120857920)))]; tensor encoder_layers_9_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_9_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120860032)))]; tensor input_135_cast_fp16 = layer_norm(axes = input_135_axes_0, beta = encoder_layers_9_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_9_norm_feed_forward1_weight_to_fp16, x = input0_129_cast_fp16)[name = tensor("input_135_cast_fp16")]; tensor encoder_layers_9_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(120862144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122959360))), name = tensor("encoder_layers_9_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_82_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_9_feed_forward1_linear1_weight_to_fp16_palettized, x = input_135_cast_fp16)[name = tensor("linear_82_cast_fp16")]; tensor var_1823_cast_fp16 = silu(x = linear_82_cast_fp16)[name = tensor("op_1823_cast_fp16")]; tensor encoder_layers_9_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(122959488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125056704))), name = tensor("encoder_layers_9_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_83_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1823_cast_fp16)[name = tensor("linear_83_cast_fp16")]; tensor var_1828_to_fp16 = const()[name = tensor("op_1828_to_fp16"), val = tensor(0x1p-1)]; tensor var_1829_cast_fp16 = mul(x = linear_83_cast_fp16, y = var_1828_to_fp16)[name = tensor("op_1829_cast_fp16")]; tensor input_139_cast_fp16 = add(x = input0_129_cast_fp16, y = var_1829_cast_fp16)[name = tensor("input_139_cast_fp16")]; tensor query_20_axes_0 = const()[name = tensor("query_20_axes_0"), val = tensor([-1])]; tensor encoder_layers_9_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_9_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125056832)))]; tensor encoder_layers_9_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_9_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125058944)))]; tensor query_20_cast_fp16 = layer_norm(axes = query_20_axes_0, beta = encoder_layers_9_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_9_norm_self_att_weight_to_fp16, x = input_139_cast_fp16)[name = tensor("query_20_cast_fp16")]; tensor var_1842_shape_cast_fp16 = shape(x = query_20_cast_fp16)[name = tensor("op_1842_shape_cast_fp16")]; tensor gather_124_axis_0 = const()[name = tensor("gather_124_axis_0"), val = tensor(0)]; tensor gather_124_batch_dims_0 = const()[name = tensor("gather_124_batch_dims_0"), val = tensor(0)]; tensor gather_124_validate_indices_0 = const()[name = tensor("gather_124_validate_indices_0"), val = tensor(false)]; tensor var_1842_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1842_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_124_to_uint16 = const()[name = tensor("select_124_to_uint16"), val = tensor(0)]; tensor var_1842_shape_cast_fp16_to_uint16 = cast(dtype = var_1842_shape_cast_fp16_to_uint16_dtype_0, x = var_1842_shape_cast_fp16)[name = tensor("cast_149")]; tensor gather_124_cast_uint16 = gather(axis = gather_124_axis_0, batch_dims = gather_124_batch_dims_0, indices = select_124_to_uint16, validate_indices = gather_124_validate_indices_0, x = var_1842_shape_cast_fp16_to_uint16)[name = tensor("gather_124_cast_uint16")]; tensor gather_124_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_124_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_9_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125061056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125585408))), name = tensor("encoder_layers_9_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_84_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_self_attn_linear_q_weight_to_fp16_palettized, x = query_20_cast_fp16)[name = tensor("linear_84_cast_fp16")]; tensor concat_87_axis_0 = const()[name = tensor("concat_87_axis_0"), val = tensor(0)]; tensor concat_87_interleave_0 = const()[name = tensor("concat_87_interleave_0"), val = tensor(false)]; tensor gather_124_cast_uint16_to_int32 = cast(dtype = gather_124_cast_uint16_to_int32_dtype_0, x = gather_124_cast_uint16)[name = tensor("cast_148")]; tensor concat_87 = concat(axis = concat_87_axis_0, interleave = concat_87_interleave_0, values = (gather_124_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_87")]; tensor q_20_cast_fp16 = reshape(shape = concat_87, x = linear_84_cast_fp16)[name = tensor("q_20_cast_fp16")]; tensor encoder_layers_9_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(125585536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126109888))), name = tensor("encoder_layers_9_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_85_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_self_attn_linear_k_weight_to_fp16_palettized, x = query_20_cast_fp16)[name = tensor("linear_85_cast_fp16")]; tensor k_20_cast_fp16 = reshape(shape = concat_87, x = linear_85_cast_fp16)[name = tensor("k_20_cast_fp16")]; tensor encoder_layers_9_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126110016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126634368))), name = tensor("encoder_layers_9_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_86_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_self_attn_linear_v_weight_to_fp16_palettized, x = query_20_cast_fp16)[name = tensor("linear_86_cast_fp16")]; tensor v_20_cast_fp16 = reshape(shape = concat_87, x = linear_86_cast_fp16)[name = tensor("v_20_cast_fp16")]; tensor value_20_perm_0 = const()[name = tensor("value_20_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_9_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(126634496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127158848))), name = tensor("encoder_layers_9_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_87_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_87_cast_fp16")]; tensor var_1862 = const()[name = tensor("op_1862"), val = tensor([1, -1, 8, 128])]; tensor p_20_cast_fp16 = reshape(shape = var_1862, x = linear_87_cast_fp16)[name = tensor("p_20_cast_fp16")]; tensor encoder_layers_9_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_9_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127158976)))]; tensor var_1865_cast_fp16 = add(x = q_20_cast_fp16, y = encoder_layers_9_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1865_cast_fp16")]; tensor encoder_layers_9_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_9_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127161088)))]; tensor var_1867_cast_fp16 = add(x = q_20_cast_fp16, y = encoder_layers_9_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1867_cast_fp16")]; tensor x_155_transpose_x_0 = const()[name = tensor("x_155_transpose_x_0"), val = tensor(false)]; tensor x_155_transpose_y_0 = const()[name = tensor("x_155_transpose_y_0"), val = tensor(false)]; tensor transpose_228_perm_0 = const()[name = tensor("transpose_228_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_229_perm_0 = const()[name = tensor("transpose_229_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_229 = transpose(perm = transpose_229_perm_0, x = p_20_cast_fp16)[name = tensor("transpose_406")]; tensor transpose_228 = transpose(perm = transpose_228_perm_0, x = var_1867_cast_fp16)[name = tensor("transpose_407")]; tensor x_155_cast_fp16 = matmul(transpose_x = x_155_transpose_x_0, transpose_y = x_155_transpose_y_0, x = transpose_228, y = transpose_229)[name = tensor("x_155_cast_fp16")]; tensor var_1871_shape_cast_fp16 = shape(x = x_155_cast_fp16)[name = tensor("op_1871_shape_cast_fp16")]; tensor gather_126_axis_0 = const()[name = tensor("gather_126_axis_0"), val = tensor(0)]; tensor gather_126_batch_dims_0 = const()[name = tensor("gather_126_batch_dims_0"), val = tensor(0)]; tensor gather_126_validate_indices_0 = const()[name = tensor("gather_126_validate_indices_0"), val = tensor(false)]; tensor var_1871_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1871_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_126_to_uint16 = const()[name = tensor("select_126_to_uint16"), val = tensor(0)]; tensor var_1871_shape_cast_fp16_to_uint16 = cast(dtype = var_1871_shape_cast_fp16_to_uint16_dtype_0, x = var_1871_shape_cast_fp16)[name = tensor("cast_147")]; tensor gather_126_cast_uint16 = gather(axis = gather_126_axis_0, batch_dims = gather_126_batch_dims_0, indices = select_126_to_uint16, validate_indices = gather_126_validate_indices_0, x = var_1871_shape_cast_fp16_to_uint16)[name = tensor("gather_126_cast_uint16")]; tensor gather_126_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_126_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_127 = const()[name = tensor("gather_127"), val = tensor(8)]; tensor gather_128_axis_0 = const()[name = tensor("gather_128_axis_0"), val = tensor(0)]; tensor gather_128_batch_dims_0 = const()[name = tensor("gather_128_batch_dims_0"), val = tensor(0)]; tensor gather_128_validate_indices_0 = const()[name = tensor("gather_128_validate_indices_0"), val = tensor(false)]; tensor select_128_to_uint16 = const()[name = tensor("select_128_to_uint16"), val = tensor(2)]; tensor gather_128_cast_uint16 = gather(axis = gather_128_axis_0, batch_dims = gather_128_batch_dims_0, indices = select_128_to_uint16, validate_indices = gather_128_validate_indices_0, x = var_1871_shape_cast_fp16_to_uint16)[name = tensor("gather_128_cast_uint16")]; tensor gather_128_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_128_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_129_axis_0 = const()[name = tensor("gather_129_axis_0"), val = tensor(0)]; tensor gather_129_batch_dims_0 = const()[name = tensor("gather_129_batch_dims_0"), val = tensor(0)]; tensor gather_129_validate_indices_0 = const()[name = tensor("gather_129_validate_indices_0"), val = tensor(false)]; tensor select_129_to_uint16 = const()[name = tensor("select_129_to_uint16"), val = tensor(3)]; tensor gather_129_cast_uint16 = gather(axis = gather_129_axis_0, batch_dims = gather_129_batch_dims_0, indices = select_129_to_uint16, validate_indices = gather_129_validate_indices_0, x = var_1871_shape_cast_fp16_to_uint16)[name = tensor("gather_129_cast_uint16")]; tensor gather_129_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_129_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_22_pad_0 = const()[name = tensor("x0_22_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_22_mode_0 = const()[name = tensor("x0_22_mode_0"), val = tensor("constant")]; tensor const_29_to_fp16 = const()[name = tensor("const_29_to_fp16"), val = tensor(0x0p+0)]; tensor x0_22_cast_fp16 = pad(constant_val = const_29_to_fp16, mode = x0_22_mode_0, pad = x0_22_pad_0, x = x_155_cast_fp16)[name = tensor("x0_22_cast_fp16")]; tensor concat_90_axis_0 = const()[name = tensor("concat_90_axis_0"), val = tensor(0)]; tensor concat_90_interleave_0 = const()[name = tensor("concat_90_interleave_0"), val = tensor(false)]; tensor gather_126_cast_uint16_to_int32 = cast(dtype = gather_126_cast_uint16_to_int32_dtype_0, x = gather_126_cast_uint16)[name = tensor("cast_145")]; tensor gather_128_cast_uint16_to_int32 = cast(dtype = gather_128_cast_uint16_to_int32_dtype_0, x = gather_128_cast_uint16)[name = tensor("cast_146")]; tensor concat_90 = concat(axis = concat_90_axis_0, interleave = concat_90_interleave_0, values = (gather_126_cast_uint16_to_int32, gather_127, var_21, gather_128_cast_uint16_to_int32))[name = tensor("concat_90")]; tensor x1_20_cast_fp16 = reshape(shape = concat_90, x = x0_22_cast_fp16)[name = tensor("x1_20_cast_fp16")]; tensor var_1881_begin_0 = const()[name = tensor("op_1881_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1881_end_0 = const()[name = tensor("op_1881_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_1881_end_mask_0 = const()[name = tensor("op_1881_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1881_cast_fp16 = slice_by_index(begin = var_1881_begin_0, end = var_1881_end_0, end_mask = var_1881_end_mask_0, x = x1_20_cast_fp16)[name = tensor("op_1881_cast_fp16")]; tensor concat_91_axis_0 = const()[name = tensor("concat_91_axis_0"), val = tensor(0)]; tensor concat_91_interleave_0 = const()[name = tensor("concat_91_interleave_0"), val = tensor(false)]; tensor gather_129_cast_uint16_to_int32 = cast(dtype = gather_129_cast_uint16_to_int32_dtype_0, x = gather_129_cast_uint16)[name = tensor("cast_144")]; tensor concat_91 = concat(axis = concat_91_axis_0, interleave = concat_91_interleave_0, values = (gather_126_cast_uint16_to_int32, gather_127, gather_128_cast_uint16_to_int32, gather_129_cast_uint16_to_int32))[name = tensor("concat_91")]; tensor matrix_bd_20_cast_fp16 = reshape(shape = concat_91, x = var_1881_cast_fp16)[name = tensor("matrix_bd_20_cast_fp16")]; tensor matrix_ac_20_transpose_x_0 = const()[name = tensor("matrix_ac_20_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_20_transpose_y_0 = const()[name = tensor("matrix_ac_20_transpose_y_0"), val = tensor(false)]; tensor transpose_230_perm_0 = const()[name = tensor("transpose_230_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_231_perm_0 = const()[name = tensor("transpose_231_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_231 = transpose(perm = transpose_231_perm_0, x = k_20_cast_fp16)[name = tensor("transpose_404")]; tensor transpose_230 = transpose(perm = transpose_230_perm_0, x = var_1865_cast_fp16)[name = tensor("transpose_405")]; tensor matrix_ac_20_cast_fp16 = matmul(transpose_x = matrix_ac_20_transpose_x_0, transpose_y = matrix_ac_20_transpose_y_0, x = transpose_230, y = transpose_231)[name = tensor("matrix_ac_20_cast_fp16")]; tensor var_1886_shape_cast_fp16 = shape(x = matrix_ac_20_cast_fp16)[name = tensor("op_1886_shape_cast_fp16")]; tensor gather_130_axis_0 = const()[name = tensor("gather_130_axis_0"), val = tensor(0)]; tensor gather_130_batch_dims_0 = const()[name = tensor("gather_130_batch_dims_0"), val = tensor(0)]; tensor gather_130_validate_indices_0 = const()[name = tensor("gather_130_validate_indices_0"), val = tensor(false)]; tensor var_1886_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1886_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_130_to_uint16 = const()[name = tensor("select_130_to_uint16"), val = tensor(3)]; tensor var_1886_shape_cast_fp16_to_uint16 = cast(dtype = var_1886_shape_cast_fp16_to_uint16_dtype_0, x = var_1886_shape_cast_fp16)[name = tensor("cast_143")]; tensor gather_130_cast_uint16 = gather(axis = gather_130_axis_0, batch_dims = gather_130_batch_dims_0, indices = select_130_to_uint16, validate_indices = gather_130_validate_indices_0, x = var_1886_shape_cast_fp16_to_uint16)[name = tensor("gather_130_cast_uint16")]; tensor gather_130_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_130_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_92_values0_0 = const()[name = tensor("concat_92_values0_0"), val = tensor(0)]; tensor concat_92_values1_0 = const()[name = tensor("concat_92_values1_0"), val = tensor(8)]; tensor concat_92_values2_0 = const()[name = tensor("concat_92_values2_0"), val = tensor(0)]; tensor concat_92_axis_0 = const()[name = tensor("concat_92_axis_0"), val = tensor(0)]; tensor concat_92_interleave_0 = const()[name = tensor("concat_92_interleave_0"), val = tensor(false)]; tensor gather_130_cast_uint16_to_int32 = cast(dtype = gather_130_cast_uint16_to_int32_dtype_0, x = gather_130_cast_uint16)[name = tensor("cast_142")]; tensor concat_92 = concat(axis = concat_92_axis_0, interleave = concat_92_interleave_0, values = (concat_92_values0_0, concat_92_values1_0, concat_92_values2_0, gather_130_cast_uint16_to_int32))[name = tensor("concat_92")]; tensor matrix_bd0_20_begin_0 = const()[name = tensor("matrix_bd0_20_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_20_end_mask_0 = const()[name = tensor("matrix_bd0_20_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_20_cast_fp16 = slice_by_index(begin = matrix_bd0_20_begin_0, end = concat_92, end_mask = matrix_bd0_20_end_mask_0, x = matrix_bd_20_cast_fp16)[name = tensor("matrix_bd0_20_cast_fp16")]; tensor var_1891_cast_fp16 = add(x = matrix_ac_20_cast_fp16, y = matrix_bd0_20_cast_fp16)[name = tensor("op_1891_cast_fp16")]; tensor _inversed_scores_20_y_0_to_fp16 = const()[name = tensor("_inversed_scores_20_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_20_cast_fp16 = mul(x = var_1891_cast_fp16, y = _inversed_scores_20_y_0_to_fp16)[name = tensor("_inversed_scores_20_cast_fp16")]; tensor value_20_cast_fp16 = transpose(perm = value_20_perm_0, x = v_20_cast_fp16)[name = tensor("transpose_403")]; tensor var_1894_shape_cast_fp16 = shape(x = value_20_cast_fp16)[name = tensor("op_1894_shape_cast_fp16")]; tensor gather_131_axis_0 = const()[name = tensor("gather_131_axis_0"), val = tensor(0)]; tensor gather_131_batch_dims_0 = const()[name = tensor("gather_131_batch_dims_0"), val = tensor(0)]; tensor gather_131_validate_indices_0 = const()[name = tensor("gather_131_validate_indices_0"), val = tensor(false)]; tensor var_1894_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_1894_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_131_to_uint16 = const()[name = tensor("select_131_to_uint16"), val = tensor(0)]; tensor var_1894_shape_cast_fp16_to_uint16 = cast(dtype = var_1894_shape_cast_fp16_to_uint16_dtype_0, x = var_1894_shape_cast_fp16)[name = tensor("cast_141")]; tensor gather_131_cast_uint16 = gather(axis = gather_131_axis_0, batch_dims = gather_131_batch_dims_0, indices = select_131_to_uint16, validate_indices = gather_131_validate_indices_0, x = var_1894_shape_cast_fp16_to_uint16)[name = tensor("gather_131_cast_uint16")]; tensor gather_131_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_131_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_20_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_20_cast_fp16, cond = mask0_4)[name = tensor("scores0_20_cast_fp16")]; tensor var_1897_cast_fp16 = softmax(axis = var_21, x = scores0_20_cast_fp16)[name = tensor("op_1897_cast_fp16")]; tensor input_141_cast_fp16 = select(a = var_8_to_fp16, b = var_1897_cast_fp16, cond = mask0_4)[name = tensor("input_141_cast_fp16")]; tensor x2_20_transpose_x_0 = const()[name = tensor("x2_20_transpose_x_0"), val = tensor(false)]; tensor x2_20_transpose_y_0 = const()[name = tensor("x2_20_transpose_y_0"), val = tensor(false)]; tensor x2_20_cast_fp16 = matmul(transpose_x = x2_20_transpose_x_0, transpose_y = x2_20_transpose_y_0, x = input_141_cast_fp16, y = value_20_cast_fp16)[name = tensor("x2_20_cast_fp16")]; tensor var_1901_perm_0 = const()[name = tensor("op_1901_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_93_axis_0 = const()[name = tensor("concat_93_axis_0"), val = tensor(0)]; tensor concat_93_interleave_0 = const()[name = tensor("concat_93_interleave_0"), val = tensor(false)]; tensor gather_131_cast_uint16_to_int32 = cast(dtype = gather_131_cast_uint16_to_int32_dtype_0, x = gather_131_cast_uint16)[name = tensor("cast_140")]; tensor concat_93 = concat(axis = concat_93_axis_0, interleave = concat_93_interleave_0, values = (gather_131_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_93")]; tensor var_1901_cast_fp16 = transpose(perm = var_1901_perm_0, x = x2_20_cast_fp16)[name = tensor("transpose_402")]; tensor input0_131_cast_fp16 = reshape(shape = concat_93, x = var_1901_cast_fp16)[name = tensor("input0_131_cast_fp16")]; tensor encoder_layers_9_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127163200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127687552))), name = tensor("encoder_layers_9_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_88_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_self_attn_linear_out_weight_to_fp16_palettized, x = input0_131_cast_fp16)[name = tensor("linear_88_cast_fp16")]; tensor input0_133_cast_fp16 = add(x = input_139_cast_fp16, y = linear_88_cast_fp16)[name = tensor("input0_133_cast_fp16")]; tensor x_159_axes_0 = const()[name = tensor("x_159_axes_0"), val = tensor([-1])]; tensor encoder_layers_9_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_9_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127687680)))]; tensor encoder_layers_9_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_9_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127689792)))]; tensor x_159_cast_fp16 = layer_norm(axes = x_159_axes_0, beta = encoder_layers_9_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_9_norm_conv_weight_to_fp16, x = input0_133_cast_fp16)[name = tensor("x_159_cast_fp16")]; tensor input_143_perm_0 = const()[name = tensor("input_143_perm_0"), val = tensor([0, 2, 1])]; tensor input0_135_pad_type_0 = const()[name = tensor("input0_135_pad_type_0"), val = tensor("valid")]; tensor input0_135_strides_0 = const()[name = tensor("input0_135_strides_0"), val = tensor([1])]; tensor input0_135_pad_0 = const()[name = tensor("input0_135_pad_0"), val = tensor([0, 0])]; tensor input0_135_dilations_0 = const()[name = tensor("input0_135_dilations_0"), val = tensor([1])]; tensor input0_135_groups_0 = const()[name = tensor("input0_135_groups_0"), val = tensor(1)]; tensor encoder_layers_9_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(127691904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128740544))), name = tensor("encoder_layers_9_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_143_cast_fp16 = transpose(perm = input_143_perm_0, x = x_159_cast_fp16)[name = tensor("transpose_401")]; tensor input0_135_cast_fp16 = conv(dilations = input0_135_dilations_0, groups = input0_135_groups_0, pad = input0_135_pad_0, pad_type = input0_135_pad_type_0, strides = input0_135_strides_0, weight = encoder_layers_9_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_143_cast_fp16)[name = tensor("input0_135_cast_fp16")]; tensor x_161_split_num_splits_0 = const()[name = tensor("x_161_split_num_splits_0"), val = tensor(2)]; tensor x_161_split_axis_0 = const()[name = tensor("x_161_split_axis_0"), val = tensor(1)]; tensor x_161_split_cast_fp16_0, tensor x_161_split_cast_fp16_1 = split(axis = x_161_split_axis_0, num_splits = x_161_split_num_splits_0, x = input0_135_cast_fp16)[name = tensor("x_161_split_cast_fp16")]; tensor x_161_split_1_sigmoid_cast_fp16 = sigmoid(x = x_161_split_cast_fp16_1)[name = tensor("x_161_split_1_sigmoid_cast_fp16")]; tensor x_161_cast_fp16 = mul(x = x_161_split_cast_fp16_0, y = x_161_split_1_sigmoid_cast_fp16)[name = tensor("x_161_cast_fp16")]; tensor input0_137_cast_fp16 = select(a = var_8_to_fp16, b = x_161_cast_fp16, cond = var_457)[name = tensor("input0_137_cast_fp16")]; tensor input0_139_pad_0 = const()[name = tensor("input0_139_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_139_mode_0 = const()[name = tensor("input0_139_mode_0"), val = tensor("constant")]; tensor const_30_to_fp16 = const()[name = tensor("const_30_to_fp16"), val = tensor(0x0p+0)]; tensor input0_139_cast_fp16 = pad(constant_val = const_30_to_fp16, mode = input0_139_mode_0, pad = input0_139_pad_0, x = input0_137_cast_fp16)[name = tensor("input0_139_cast_fp16")]; tensor input1_42_pad_type_0 = const()[name = tensor("input1_42_pad_type_0"), val = tensor("valid")]; tensor input1_42_groups_0 = const()[name = tensor("input1_42_groups_0"), val = tensor(1024)]; tensor input1_42_strides_0 = const()[name = tensor("input1_42_strides_0"), val = tensor([1])]; tensor input1_42_pad_0 = const()[name = tensor("input1_42_pad_0"), val = tensor([0, 0])]; tensor input1_42_dilations_0 = const()[name = tensor("input1_42_dilations_0"), val = tensor([1])]; tensor const_77_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128740672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128745344))), name = tensor("const_77_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_78_to_fp16 = const()[name = tensor("const_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128745472)))]; tensor input_145_cast_fp16 = conv(bias = const_78_to_fp16, dilations = input1_42_dilations_0, groups = input1_42_groups_0, pad = input1_42_pad_0, pad_type = input1_42_pad_type_0, strides = input1_42_strides_0, weight = const_77_to_fp16_palettized, x = input0_139_cast_fp16)[name = tensor("input_145_cast_fp16")]; tensor var_1939_cast_fp16 = silu(x = input_145_cast_fp16)[name = tensor("op_1939_cast_fp16")]; tensor x_163_pad_type_0 = const()[name = tensor("x_163_pad_type_0"), val = tensor("valid")]; tensor x_163_strides_0 = const()[name = tensor("x_163_strides_0"), val = tensor([1])]; tensor x_163_pad_0 = const()[name = tensor("x_163_pad_0"), val = tensor([0, 0])]; tensor x_163_dilations_0 = const()[name = tensor("x_163_dilations_0"), val = tensor([1])]; tensor x_163_groups_0 = const()[name = tensor("x_163_groups_0"), val = tensor(1)]; tensor encoder_layers_9_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(128747584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129271936))), name = tensor("encoder_layers_9_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_163_cast_fp16 = conv(dilations = x_163_dilations_0, groups = x_163_groups_0, pad = x_163_pad_0, pad_type = x_163_pad_type_0, strides = x_163_strides_0, weight = encoder_layers_9_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1939_cast_fp16)[name = tensor("x_163_cast_fp16")]; tensor var_1946_perm_0 = const()[name = tensor("op_1946_perm_0"), val = tensor([0, 2, 1])]; tensor var_1946_cast_fp16 = transpose(perm = var_1946_perm_0, x = x_163_cast_fp16)[name = tensor("transpose_400")]; tensor input1_44_cast_fp16 = add(x = input0_133_cast_fp16, y = var_1946_cast_fp16)[name = tensor("input1_44_cast_fp16")]; tensor input0_141_axes_0 = const()[name = tensor("input0_141_axes_0"), val = tensor([-1])]; tensor encoder_layers_9_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_9_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129272064)))]; tensor encoder_layers_9_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_9_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129274176)))]; tensor input0_141_cast_fp16 = layer_norm(axes = input0_141_axes_0, beta = encoder_layers_9_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_9_norm_feed_forward2_weight_to_fp16, x = input1_44_cast_fp16)[name = tensor("input0_141_cast_fp16")]; tensor encoder_layers_9_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(129276288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131373504))), name = tensor("encoder_layers_9_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_89_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_9_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_141_cast_fp16)[name = tensor("linear_89_cast_fp16")]; tensor var_1957_cast_fp16 = silu(x = linear_89_cast_fp16)[name = tensor("op_1957_cast_fp16")]; tensor encoder_layers_9_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(131373632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133470848))), name = tensor("encoder_layers_9_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_90_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_9_feed_forward2_linear2_weight_to_fp16_palettized, x = var_1957_cast_fp16)[name = tensor("linear_90_cast_fp16")]; tensor var_1962_to_fp16 = const()[name = tensor("op_1962_to_fp16"), val = tensor(0x1p-1)]; tensor var_1963_cast_fp16 = mul(x = linear_90_cast_fp16, y = var_1962_to_fp16)[name = tensor("op_1963_cast_fp16")]; tensor input2_22_cast_fp16 = add(x = input1_44_cast_fp16, y = var_1963_cast_fp16)[name = tensor("input2_22_cast_fp16")]; tensor input0_143_axes_0 = const()[name = tensor("input0_143_axes_0"), val = tensor([-1])]; tensor encoder_layers_9_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_9_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133470976)))]; tensor encoder_layers_9_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_9_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133473088)))]; tensor input0_143_cast_fp16 = layer_norm(axes = input0_143_axes_0, beta = encoder_layers_9_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_9_norm_out_weight_to_fp16, x = input2_22_cast_fp16)[name = tensor("input0_143_cast_fp16")]; tensor input_149_axes_0 = const()[name = tensor("input_149_axes_0"), val = tensor([-1])]; tensor encoder_layers_10_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_10_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133475200)))]; tensor encoder_layers_10_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_10_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133477312)))]; tensor input_149_cast_fp16 = layer_norm(axes = input_149_axes_0, beta = encoder_layers_10_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_10_norm_feed_forward1_weight_to_fp16, x = input0_143_cast_fp16)[name = tensor("input_149_cast_fp16")]; tensor encoder_layers_10_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(133479424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135576640))), name = tensor("encoder_layers_10_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_91_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_10_feed_forward1_linear1_weight_to_fp16_palettized, x = input_149_cast_fp16)[name = tensor("linear_91_cast_fp16")]; tensor var_1986_cast_fp16 = silu(x = linear_91_cast_fp16)[name = tensor("op_1986_cast_fp16")]; tensor encoder_layers_10_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(135576768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137673984))), name = tensor("encoder_layers_10_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_92_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_feed_forward1_linear2_weight_to_fp16_palettized, x = var_1986_cast_fp16)[name = tensor("linear_92_cast_fp16")]; tensor var_1991_to_fp16 = const()[name = tensor("op_1991_to_fp16"), val = tensor(0x1p-1)]; tensor var_1992_cast_fp16 = mul(x = linear_92_cast_fp16, y = var_1991_to_fp16)[name = tensor("op_1992_cast_fp16")]; tensor input_153_cast_fp16 = add(x = input0_143_cast_fp16, y = var_1992_cast_fp16)[name = tensor("input_153_cast_fp16")]; tensor query_22_axes_0 = const()[name = tensor("query_22_axes_0"), val = tensor([-1])]; tensor encoder_layers_10_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_10_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137674112)))]; tensor encoder_layers_10_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_10_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137676224)))]; tensor query_22_cast_fp16 = layer_norm(axes = query_22_axes_0, beta = encoder_layers_10_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_10_norm_self_att_weight_to_fp16, x = input_153_cast_fp16)[name = tensor("query_22_cast_fp16")]; tensor var_2005_shape_cast_fp16 = shape(x = query_22_cast_fp16)[name = tensor("op_2005_shape_cast_fp16")]; tensor gather_132_axis_0 = const()[name = tensor("gather_132_axis_0"), val = tensor(0)]; tensor gather_132_batch_dims_0 = const()[name = tensor("gather_132_batch_dims_0"), val = tensor(0)]; tensor gather_132_validate_indices_0 = const()[name = tensor("gather_132_validate_indices_0"), val = tensor(false)]; tensor var_2005_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2005_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_132_to_uint16 = const()[name = tensor("select_132_to_uint16"), val = tensor(0)]; tensor var_2005_shape_cast_fp16_to_uint16 = cast(dtype = var_2005_shape_cast_fp16_to_uint16_dtype_0, x = var_2005_shape_cast_fp16)[name = tensor("cast_139")]; tensor gather_132_cast_uint16 = gather(axis = gather_132_axis_0, batch_dims = gather_132_batch_dims_0, indices = select_132_to_uint16, validate_indices = gather_132_validate_indices_0, x = var_2005_shape_cast_fp16_to_uint16)[name = tensor("gather_132_cast_uint16")]; tensor gather_132_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_132_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_10_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(137678336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138202688))), name = tensor("encoder_layers_10_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_93_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_self_attn_linear_q_weight_to_fp16_palettized, x = query_22_cast_fp16)[name = tensor("linear_93_cast_fp16")]; tensor concat_94_axis_0 = const()[name = tensor("concat_94_axis_0"), val = tensor(0)]; tensor concat_94_interleave_0 = const()[name = tensor("concat_94_interleave_0"), val = tensor(false)]; tensor gather_132_cast_uint16_to_int32 = cast(dtype = gather_132_cast_uint16_to_int32_dtype_0, x = gather_132_cast_uint16)[name = tensor("cast_138")]; tensor concat_94 = concat(axis = concat_94_axis_0, interleave = concat_94_interleave_0, values = (gather_132_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_94")]; tensor q_22_cast_fp16 = reshape(shape = concat_94, x = linear_93_cast_fp16)[name = tensor("q_22_cast_fp16")]; tensor encoder_layers_10_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138202816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138727168))), name = tensor("encoder_layers_10_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_94_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_self_attn_linear_k_weight_to_fp16_palettized, x = query_22_cast_fp16)[name = tensor("linear_94_cast_fp16")]; tensor k_22_cast_fp16 = reshape(shape = concat_94, x = linear_94_cast_fp16)[name = tensor("k_22_cast_fp16")]; tensor encoder_layers_10_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(138727296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139251648))), name = tensor("encoder_layers_10_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_95_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_self_attn_linear_v_weight_to_fp16_palettized, x = query_22_cast_fp16)[name = tensor("linear_95_cast_fp16")]; tensor v_22_cast_fp16 = reshape(shape = concat_94, x = linear_95_cast_fp16)[name = tensor("v_22_cast_fp16")]; tensor value_22_perm_0 = const()[name = tensor("value_22_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_10_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139251776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139776128))), name = tensor("encoder_layers_10_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_96_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_96_cast_fp16")]; tensor var_2025 = const()[name = tensor("op_2025"), val = tensor([1, -1, 8, 128])]; tensor p_22_cast_fp16 = reshape(shape = var_2025, x = linear_96_cast_fp16)[name = tensor("p_22_cast_fp16")]; tensor encoder_layers_10_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_10_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139776256)))]; tensor var_2028_cast_fp16 = add(x = q_22_cast_fp16, y = encoder_layers_10_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2028_cast_fp16")]; tensor encoder_layers_10_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_10_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139778368)))]; tensor var_2030_cast_fp16 = add(x = q_22_cast_fp16, y = encoder_layers_10_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2030_cast_fp16")]; tensor x_171_transpose_x_0 = const()[name = tensor("x_171_transpose_x_0"), val = tensor(false)]; tensor x_171_transpose_y_0 = const()[name = tensor("x_171_transpose_y_0"), val = tensor(false)]; tensor transpose_232_perm_0 = const()[name = tensor("transpose_232_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_233_perm_0 = const()[name = tensor("transpose_233_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_233 = transpose(perm = transpose_233_perm_0, x = p_22_cast_fp16)[name = tensor("transpose_398")]; tensor transpose_232 = transpose(perm = transpose_232_perm_0, x = var_2030_cast_fp16)[name = tensor("transpose_399")]; tensor x_171_cast_fp16 = matmul(transpose_x = x_171_transpose_x_0, transpose_y = x_171_transpose_y_0, x = transpose_232, y = transpose_233)[name = tensor("x_171_cast_fp16")]; tensor var_2034_shape_cast_fp16 = shape(x = x_171_cast_fp16)[name = tensor("op_2034_shape_cast_fp16")]; tensor gather_134_axis_0 = const()[name = tensor("gather_134_axis_0"), val = tensor(0)]; tensor gather_134_batch_dims_0 = const()[name = tensor("gather_134_batch_dims_0"), val = tensor(0)]; tensor gather_134_validate_indices_0 = const()[name = tensor("gather_134_validate_indices_0"), val = tensor(false)]; tensor var_2034_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2034_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_134_to_uint16 = const()[name = tensor("select_134_to_uint16"), val = tensor(0)]; tensor var_2034_shape_cast_fp16_to_uint16 = cast(dtype = var_2034_shape_cast_fp16_to_uint16_dtype_0, x = var_2034_shape_cast_fp16)[name = tensor("cast_137")]; tensor gather_134_cast_uint16 = gather(axis = gather_134_axis_0, batch_dims = gather_134_batch_dims_0, indices = select_134_to_uint16, validate_indices = gather_134_validate_indices_0, x = var_2034_shape_cast_fp16_to_uint16)[name = tensor("gather_134_cast_uint16")]; tensor gather_134_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_134_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_135 = const()[name = tensor("gather_135"), val = tensor(8)]; tensor gather_136_axis_0 = const()[name = tensor("gather_136_axis_0"), val = tensor(0)]; tensor gather_136_batch_dims_0 = const()[name = tensor("gather_136_batch_dims_0"), val = tensor(0)]; tensor gather_136_validate_indices_0 = const()[name = tensor("gather_136_validate_indices_0"), val = tensor(false)]; tensor select_136_to_uint16 = const()[name = tensor("select_136_to_uint16"), val = tensor(2)]; tensor gather_136_cast_uint16 = gather(axis = gather_136_axis_0, batch_dims = gather_136_batch_dims_0, indices = select_136_to_uint16, validate_indices = gather_136_validate_indices_0, x = var_2034_shape_cast_fp16_to_uint16)[name = tensor("gather_136_cast_uint16")]; tensor gather_136_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_136_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_137_axis_0 = const()[name = tensor("gather_137_axis_0"), val = tensor(0)]; tensor gather_137_batch_dims_0 = const()[name = tensor("gather_137_batch_dims_0"), val = tensor(0)]; tensor gather_137_validate_indices_0 = const()[name = tensor("gather_137_validate_indices_0"), val = tensor(false)]; tensor select_137_to_uint16 = const()[name = tensor("select_137_to_uint16"), val = tensor(3)]; tensor gather_137_cast_uint16 = gather(axis = gather_137_axis_0, batch_dims = gather_137_batch_dims_0, indices = select_137_to_uint16, validate_indices = gather_137_validate_indices_0, x = var_2034_shape_cast_fp16_to_uint16)[name = tensor("gather_137_cast_uint16")]; tensor gather_137_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_137_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_24_pad_0 = const()[name = tensor("x0_24_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_24_mode_0 = const()[name = tensor("x0_24_mode_0"), val = tensor("constant")]; tensor const_31_to_fp16 = const()[name = tensor("const_31_to_fp16"), val = tensor(0x0p+0)]; tensor x0_24_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = x0_24_mode_0, pad = x0_24_pad_0, x = x_171_cast_fp16)[name = tensor("x0_24_cast_fp16")]; tensor concat_97_axis_0 = const()[name = tensor("concat_97_axis_0"), val = tensor(0)]; tensor concat_97_interleave_0 = const()[name = tensor("concat_97_interleave_0"), val = tensor(false)]; tensor gather_134_cast_uint16_to_int32 = cast(dtype = gather_134_cast_uint16_to_int32_dtype_0, x = gather_134_cast_uint16)[name = tensor("cast_135")]; tensor gather_136_cast_uint16_to_int32 = cast(dtype = gather_136_cast_uint16_to_int32_dtype_0, x = gather_136_cast_uint16)[name = tensor("cast_136")]; tensor concat_97 = concat(axis = concat_97_axis_0, interleave = concat_97_interleave_0, values = (gather_134_cast_uint16_to_int32, gather_135, var_21, gather_136_cast_uint16_to_int32))[name = tensor("concat_97")]; tensor x1_22_cast_fp16 = reshape(shape = concat_97, x = x0_24_cast_fp16)[name = tensor("x1_22_cast_fp16")]; tensor var_2044_begin_0 = const()[name = tensor("op_2044_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2044_end_0 = const()[name = tensor("op_2044_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_2044_end_mask_0 = const()[name = tensor("op_2044_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2044_cast_fp16 = slice_by_index(begin = var_2044_begin_0, end = var_2044_end_0, end_mask = var_2044_end_mask_0, x = x1_22_cast_fp16)[name = tensor("op_2044_cast_fp16")]; tensor concat_98_axis_0 = const()[name = tensor("concat_98_axis_0"), val = tensor(0)]; tensor concat_98_interleave_0 = const()[name = tensor("concat_98_interleave_0"), val = tensor(false)]; tensor gather_137_cast_uint16_to_int32 = cast(dtype = gather_137_cast_uint16_to_int32_dtype_0, x = gather_137_cast_uint16)[name = tensor("cast_134")]; tensor concat_98 = concat(axis = concat_98_axis_0, interleave = concat_98_interleave_0, values = (gather_134_cast_uint16_to_int32, gather_135, gather_136_cast_uint16_to_int32, gather_137_cast_uint16_to_int32))[name = tensor("concat_98")]; tensor matrix_bd_22_cast_fp16 = reshape(shape = concat_98, x = var_2044_cast_fp16)[name = tensor("matrix_bd_22_cast_fp16")]; tensor matrix_ac_22_transpose_x_0 = const()[name = tensor("matrix_ac_22_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_22_transpose_y_0 = const()[name = tensor("matrix_ac_22_transpose_y_0"), val = tensor(false)]; tensor transpose_234_perm_0 = const()[name = tensor("transpose_234_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_235_perm_0 = const()[name = tensor("transpose_235_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_235 = transpose(perm = transpose_235_perm_0, x = k_22_cast_fp16)[name = tensor("transpose_396")]; tensor transpose_234 = transpose(perm = transpose_234_perm_0, x = var_2028_cast_fp16)[name = tensor("transpose_397")]; tensor matrix_ac_22_cast_fp16 = matmul(transpose_x = matrix_ac_22_transpose_x_0, transpose_y = matrix_ac_22_transpose_y_0, x = transpose_234, y = transpose_235)[name = tensor("matrix_ac_22_cast_fp16")]; tensor var_2049_shape_cast_fp16 = shape(x = matrix_ac_22_cast_fp16)[name = tensor("op_2049_shape_cast_fp16")]; tensor gather_138_axis_0 = const()[name = tensor("gather_138_axis_0"), val = tensor(0)]; tensor gather_138_batch_dims_0 = const()[name = tensor("gather_138_batch_dims_0"), val = tensor(0)]; tensor gather_138_validate_indices_0 = const()[name = tensor("gather_138_validate_indices_0"), val = tensor(false)]; tensor var_2049_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2049_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_138_to_uint16 = const()[name = tensor("select_138_to_uint16"), val = tensor(3)]; tensor var_2049_shape_cast_fp16_to_uint16 = cast(dtype = var_2049_shape_cast_fp16_to_uint16_dtype_0, x = var_2049_shape_cast_fp16)[name = tensor("cast_133")]; tensor gather_138_cast_uint16 = gather(axis = gather_138_axis_0, batch_dims = gather_138_batch_dims_0, indices = select_138_to_uint16, validate_indices = gather_138_validate_indices_0, x = var_2049_shape_cast_fp16_to_uint16)[name = tensor("gather_138_cast_uint16")]; tensor gather_138_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_138_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_99_values0_0 = const()[name = tensor("concat_99_values0_0"), val = tensor(0)]; tensor concat_99_values1_0 = const()[name = tensor("concat_99_values1_0"), val = tensor(8)]; tensor concat_99_values2_0 = const()[name = tensor("concat_99_values2_0"), val = tensor(0)]; tensor concat_99_axis_0 = const()[name = tensor("concat_99_axis_0"), val = tensor(0)]; tensor concat_99_interleave_0 = const()[name = tensor("concat_99_interleave_0"), val = tensor(false)]; tensor gather_138_cast_uint16_to_int32 = cast(dtype = gather_138_cast_uint16_to_int32_dtype_0, x = gather_138_cast_uint16)[name = tensor("cast_132")]; tensor concat_99 = concat(axis = concat_99_axis_0, interleave = concat_99_interleave_0, values = (concat_99_values0_0, concat_99_values1_0, concat_99_values2_0, gather_138_cast_uint16_to_int32))[name = tensor("concat_99")]; tensor matrix_bd0_22_begin_0 = const()[name = tensor("matrix_bd0_22_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_22_end_mask_0 = const()[name = tensor("matrix_bd0_22_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_22_cast_fp16 = slice_by_index(begin = matrix_bd0_22_begin_0, end = concat_99, end_mask = matrix_bd0_22_end_mask_0, x = matrix_bd_22_cast_fp16)[name = tensor("matrix_bd0_22_cast_fp16")]; tensor var_2054_cast_fp16 = add(x = matrix_ac_22_cast_fp16, y = matrix_bd0_22_cast_fp16)[name = tensor("op_2054_cast_fp16")]; tensor _inversed_scores_22_y_0_to_fp16 = const()[name = tensor("_inversed_scores_22_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_22_cast_fp16 = mul(x = var_2054_cast_fp16, y = _inversed_scores_22_y_0_to_fp16)[name = tensor("_inversed_scores_22_cast_fp16")]; tensor value_22_cast_fp16 = transpose(perm = value_22_perm_0, x = v_22_cast_fp16)[name = tensor("transpose_395")]; tensor var_2057_shape_cast_fp16 = shape(x = value_22_cast_fp16)[name = tensor("op_2057_shape_cast_fp16")]; tensor gather_139_axis_0 = const()[name = tensor("gather_139_axis_0"), val = tensor(0)]; tensor gather_139_batch_dims_0 = const()[name = tensor("gather_139_batch_dims_0"), val = tensor(0)]; tensor gather_139_validate_indices_0 = const()[name = tensor("gather_139_validate_indices_0"), val = tensor(false)]; tensor var_2057_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2057_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_139_to_uint16 = const()[name = tensor("select_139_to_uint16"), val = tensor(0)]; tensor var_2057_shape_cast_fp16_to_uint16 = cast(dtype = var_2057_shape_cast_fp16_to_uint16_dtype_0, x = var_2057_shape_cast_fp16)[name = tensor("cast_131")]; tensor gather_139_cast_uint16 = gather(axis = gather_139_axis_0, batch_dims = gather_139_batch_dims_0, indices = select_139_to_uint16, validate_indices = gather_139_validate_indices_0, x = var_2057_shape_cast_fp16_to_uint16)[name = tensor("gather_139_cast_uint16")]; tensor gather_139_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_139_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_22_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_22_cast_fp16, cond = mask0_4)[name = tensor("scores0_22_cast_fp16")]; tensor var_2060_cast_fp16 = softmax(axis = var_21, x = scores0_22_cast_fp16)[name = tensor("op_2060_cast_fp16")]; tensor input_155_cast_fp16 = select(a = var_8_to_fp16, b = var_2060_cast_fp16, cond = mask0_4)[name = tensor("input_155_cast_fp16")]; tensor x2_22_transpose_x_0 = const()[name = tensor("x2_22_transpose_x_0"), val = tensor(false)]; tensor x2_22_transpose_y_0 = const()[name = tensor("x2_22_transpose_y_0"), val = tensor(false)]; tensor x2_22_cast_fp16 = matmul(transpose_x = x2_22_transpose_x_0, transpose_y = x2_22_transpose_y_0, x = input_155_cast_fp16, y = value_22_cast_fp16)[name = tensor("x2_22_cast_fp16")]; tensor var_2064_perm_0 = const()[name = tensor("op_2064_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_100_axis_0 = const()[name = tensor("concat_100_axis_0"), val = tensor(0)]; tensor concat_100_interleave_0 = const()[name = tensor("concat_100_interleave_0"), val = tensor(false)]; tensor gather_139_cast_uint16_to_int32 = cast(dtype = gather_139_cast_uint16_to_int32_dtype_0, x = gather_139_cast_uint16)[name = tensor("cast_130")]; tensor concat_100 = concat(axis = concat_100_axis_0, interleave = concat_100_interleave_0, values = (gather_139_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_100")]; tensor var_2064_cast_fp16 = transpose(perm = var_2064_perm_0, x = x2_22_cast_fp16)[name = tensor("transpose_394")]; tensor input0_145_cast_fp16 = reshape(shape = concat_100, x = var_2064_cast_fp16)[name = tensor("input0_145_cast_fp16")]; tensor encoder_layers_10_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(139780480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140304832))), name = tensor("encoder_layers_10_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_97_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_self_attn_linear_out_weight_to_fp16_palettized, x = input0_145_cast_fp16)[name = tensor("linear_97_cast_fp16")]; tensor input0_147_cast_fp16 = add(x = input_153_cast_fp16, y = linear_97_cast_fp16)[name = tensor("input0_147_cast_fp16")]; tensor x_175_axes_0 = const()[name = tensor("x_175_axes_0"), val = tensor([-1])]; tensor encoder_layers_10_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_10_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140304960)))]; tensor encoder_layers_10_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_10_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140307072)))]; tensor x_175_cast_fp16 = layer_norm(axes = x_175_axes_0, beta = encoder_layers_10_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_10_norm_conv_weight_to_fp16, x = input0_147_cast_fp16)[name = tensor("x_175_cast_fp16")]; tensor input_157_perm_0 = const()[name = tensor("input_157_perm_0"), val = tensor([0, 2, 1])]; tensor input0_149_pad_type_0 = const()[name = tensor("input0_149_pad_type_0"), val = tensor("valid")]; tensor input0_149_strides_0 = const()[name = tensor("input0_149_strides_0"), val = tensor([1])]; tensor input0_149_pad_0 = const()[name = tensor("input0_149_pad_0"), val = tensor([0, 0])]; tensor input0_149_dilations_0 = const()[name = tensor("input0_149_dilations_0"), val = tensor([1])]; tensor input0_149_groups_0 = const()[name = tensor("input0_149_groups_0"), val = tensor(1)]; tensor encoder_layers_10_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(140309184))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141357824))), name = tensor("encoder_layers_10_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_157_cast_fp16 = transpose(perm = input_157_perm_0, x = x_175_cast_fp16)[name = tensor("transpose_393")]; tensor input0_149_cast_fp16 = conv(dilations = input0_149_dilations_0, groups = input0_149_groups_0, pad = input0_149_pad_0, pad_type = input0_149_pad_type_0, strides = input0_149_strides_0, weight = encoder_layers_10_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_157_cast_fp16)[name = tensor("input0_149_cast_fp16")]; tensor x_177_split_num_splits_0 = const()[name = tensor("x_177_split_num_splits_0"), val = tensor(2)]; tensor x_177_split_axis_0 = const()[name = tensor("x_177_split_axis_0"), val = tensor(1)]; tensor x_177_split_cast_fp16_0, tensor x_177_split_cast_fp16_1 = split(axis = x_177_split_axis_0, num_splits = x_177_split_num_splits_0, x = input0_149_cast_fp16)[name = tensor("x_177_split_cast_fp16")]; tensor x_177_split_1_sigmoid_cast_fp16 = sigmoid(x = x_177_split_cast_fp16_1)[name = tensor("x_177_split_1_sigmoid_cast_fp16")]; tensor x_177_cast_fp16 = mul(x = x_177_split_cast_fp16_0, y = x_177_split_1_sigmoid_cast_fp16)[name = tensor("x_177_cast_fp16")]; tensor input0_151_cast_fp16 = select(a = var_8_to_fp16, b = x_177_cast_fp16, cond = var_457)[name = tensor("input0_151_cast_fp16")]; tensor input0_153_pad_0 = const()[name = tensor("input0_153_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_153_mode_0 = const()[name = tensor("input0_153_mode_0"), val = tensor("constant")]; tensor const_32_to_fp16 = const()[name = tensor("const_32_to_fp16"), val = tensor(0x0p+0)]; tensor input0_153_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input0_153_mode_0, pad = input0_153_pad_0, x = input0_151_cast_fp16)[name = tensor("input0_153_cast_fp16")]; tensor input1_46_pad_type_0 = const()[name = tensor("input1_46_pad_type_0"), val = tensor("valid")]; tensor input1_46_groups_0 = const()[name = tensor("input1_46_groups_0"), val = tensor(1024)]; tensor input1_46_strides_0 = const()[name = tensor("input1_46_strides_0"), val = tensor([1])]; tensor input1_46_pad_0 = const()[name = tensor("input1_46_pad_0"), val = tensor([0, 0])]; tensor input1_46_dilations_0 = const()[name = tensor("input1_46_dilations_0"), val = tensor([1])]; tensor const_79_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141357952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141362624))), name = tensor("const_79_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_80_to_fp16 = const()[name = tensor("const_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141362752)))]; tensor input_159_cast_fp16 = conv(bias = const_80_to_fp16, dilations = input1_46_dilations_0, groups = input1_46_groups_0, pad = input1_46_pad_0, pad_type = input1_46_pad_type_0, strides = input1_46_strides_0, weight = const_79_to_fp16_palettized, x = input0_153_cast_fp16)[name = tensor("input_159_cast_fp16")]; tensor var_2102_cast_fp16 = silu(x = input_159_cast_fp16)[name = tensor("op_2102_cast_fp16")]; tensor x_179_pad_type_0 = const()[name = tensor("x_179_pad_type_0"), val = tensor("valid")]; tensor x_179_strides_0 = const()[name = tensor("x_179_strides_0"), val = tensor([1])]; tensor x_179_pad_0 = const()[name = tensor("x_179_pad_0"), val = tensor([0, 0])]; tensor x_179_dilations_0 = const()[name = tensor("x_179_dilations_0"), val = tensor([1])]; tensor x_179_groups_0 = const()[name = tensor("x_179_groups_0"), val = tensor(1)]; tensor encoder_layers_10_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141364864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141889216))), name = tensor("encoder_layers_10_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_179_cast_fp16 = conv(dilations = x_179_dilations_0, groups = x_179_groups_0, pad = x_179_pad_0, pad_type = x_179_pad_type_0, strides = x_179_strides_0, weight = encoder_layers_10_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2102_cast_fp16)[name = tensor("x_179_cast_fp16")]; tensor var_2109_perm_0 = const()[name = tensor("op_2109_perm_0"), val = tensor([0, 2, 1])]; tensor var_2109_cast_fp16 = transpose(perm = var_2109_perm_0, x = x_179_cast_fp16)[name = tensor("transpose_392")]; tensor input1_48_cast_fp16 = add(x = input0_147_cast_fp16, y = var_2109_cast_fp16)[name = tensor("input1_48_cast_fp16")]; tensor input0_155_axes_0 = const()[name = tensor("input0_155_axes_0"), val = tensor([-1])]; tensor encoder_layers_10_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_10_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141889344)))]; tensor encoder_layers_10_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_10_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141891456)))]; tensor input0_155_cast_fp16 = layer_norm(axes = input0_155_axes_0, beta = encoder_layers_10_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_10_norm_feed_forward2_weight_to_fp16, x = input1_48_cast_fp16)[name = tensor("input0_155_cast_fp16")]; tensor encoder_layers_10_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(141893568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143990784))), name = tensor("encoder_layers_10_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_98_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_10_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_155_cast_fp16)[name = tensor("linear_98_cast_fp16")]; tensor var_2120_cast_fp16 = silu(x = linear_98_cast_fp16)[name = tensor("op_2120_cast_fp16")]; tensor encoder_layers_10_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(143990912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146088128))), name = tensor("encoder_layers_10_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_99_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_10_feed_forward2_linear2_weight_to_fp16_palettized, x = var_2120_cast_fp16)[name = tensor("linear_99_cast_fp16")]; tensor var_2125_to_fp16 = const()[name = tensor("op_2125_to_fp16"), val = tensor(0x1p-1)]; tensor var_2126_cast_fp16 = mul(x = linear_99_cast_fp16, y = var_2125_to_fp16)[name = tensor("op_2126_cast_fp16")]; tensor input2_24_cast_fp16 = add(x = input1_48_cast_fp16, y = var_2126_cast_fp16)[name = tensor("input2_24_cast_fp16")]; tensor input0_157_axes_0 = const()[name = tensor("input0_157_axes_0"), val = tensor([-1])]; tensor encoder_layers_10_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_10_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146088256)))]; tensor encoder_layers_10_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_10_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146090368)))]; tensor input0_157_cast_fp16 = layer_norm(axes = input0_157_axes_0, beta = encoder_layers_10_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_10_norm_out_weight_to_fp16, x = input2_24_cast_fp16)[name = tensor("input0_157_cast_fp16")]; tensor input_163_axes_0 = const()[name = tensor("input_163_axes_0"), val = tensor([-1])]; tensor encoder_layers_11_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_11_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146092480)))]; tensor encoder_layers_11_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_11_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146094592)))]; tensor input_163_cast_fp16 = layer_norm(axes = input_163_axes_0, beta = encoder_layers_11_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_11_norm_feed_forward1_weight_to_fp16, x = input0_157_cast_fp16)[name = tensor("input_163_cast_fp16")]; tensor encoder_layers_11_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(146096704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148193920))), name = tensor("encoder_layers_11_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_100_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_11_feed_forward1_linear1_weight_to_fp16_palettized, x = input_163_cast_fp16)[name = tensor("linear_100_cast_fp16")]; tensor var_2149_cast_fp16 = silu(x = linear_100_cast_fp16)[name = tensor("op_2149_cast_fp16")]; tensor encoder_layers_11_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(148194048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150291264))), name = tensor("encoder_layers_11_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_101_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_feed_forward1_linear2_weight_to_fp16_palettized, x = var_2149_cast_fp16)[name = tensor("linear_101_cast_fp16")]; tensor var_2154_to_fp16 = const()[name = tensor("op_2154_to_fp16"), val = tensor(0x1p-1)]; tensor var_2155_cast_fp16 = mul(x = linear_101_cast_fp16, y = var_2154_to_fp16)[name = tensor("op_2155_cast_fp16")]; tensor input_167_cast_fp16 = add(x = input0_157_cast_fp16, y = var_2155_cast_fp16)[name = tensor("input_167_cast_fp16")]; tensor query_24_axes_0 = const()[name = tensor("query_24_axes_0"), val = tensor([-1])]; tensor encoder_layers_11_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_11_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150291392)))]; tensor encoder_layers_11_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_11_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150293504)))]; tensor query_24_cast_fp16 = layer_norm(axes = query_24_axes_0, beta = encoder_layers_11_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_11_norm_self_att_weight_to_fp16, x = input_167_cast_fp16)[name = tensor("query_24_cast_fp16")]; tensor var_2168_shape_cast_fp16 = shape(x = query_24_cast_fp16)[name = tensor("op_2168_shape_cast_fp16")]; tensor gather_140_axis_0 = const()[name = tensor("gather_140_axis_0"), val = tensor(0)]; tensor gather_140_batch_dims_0 = const()[name = tensor("gather_140_batch_dims_0"), val = tensor(0)]; tensor gather_140_validate_indices_0 = const()[name = tensor("gather_140_validate_indices_0"), val = tensor(false)]; tensor var_2168_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2168_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_140_to_uint16 = const()[name = tensor("select_140_to_uint16"), val = tensor(0)]; tensor var_2168_shape_cast_fp16_to_uint16 = cast(dtype = var_2168_shape_cast_fp16_to_uint16_dtype_0, x = var_2168_shape_cast_fp16)[name = tensor("cast_129")]; tensor gather_140_cast_uint16 = gather(axis = gather_140_axis_0, batch_dims = gather_140_batch_dims_0, indices = select_140_to_uint16, validate_indices = gather_140_validate_indices_0, x = var_2168_shape_cast_fp16_to_uint16)[name = tensor("gather_140_cast_uint16")]; tensor gather_140_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_140_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_11_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150295616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150819968))), name = tensor("encoder_layers_11_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_102_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_self_attn_linear_q_weight_to_fp16_palettized, x = query_24_cast_fp16)[name = tensor("linear_102_cast_fp16")]; tensor concat_101_axis_0 = const()[name = tensor("concat_101_axis_0"), val = tensor(0)]; tensor concat_101_interleave_0 = const()[name = tensor("concat_101_interleave_0"), val = tensor(false)]; tensor gather_140_cast_uint16_to_int32 = cast(dtype = gather_140_cast_uint16_to_int32_dtype_0, x = gather_140_cast_uint16)[name = tensor("cast_128")]; tensor concat_101 = concat(axis = concat_101_axis_0, interleave = concat_101_interleave_0, values = (gather_140_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_101")]; tensor q_24_cast_fp16 = reshape(shape = concat_101, x = linear_102_cast_fp16)[name = tensor("q_24_cast_fp16")]; tensor encoder_layers_11_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(150820096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151344448))), name = tensor("encoder_layers_11_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_103_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_self_attn_linear_k_weight_to_fp16_palettized, x = query_24_cast_fp16)[name = tensor("linear_103_cast_fp16")]; tensor k_24_cast_fp16 = reshape(shape = concat_101, x = linear_103_cast_fp16)[name = tensor("k_24_cast_fp16")]; tensor encoder_layers_11_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151344576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151868928))), name = tensor("encoder_layers_11_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_104_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_self_attn_linear_v_weight_to_fp16_palettized, x = query_24_cast_fp16)[name = tensor("linear_104_cast_fp16")]; tensor v_24_cast_fp16 = reshape(shape = concat_101, x = linear_104_cast_fp16)[name = tensor("v_24_cast_fp16")]; tensor value_24_perm_0 = const()[name = tensor("value_24_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_11_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(151869056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152393408))), name = tensor("encoder_layers_11_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_105_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_105_cast_fp16")]; tensor var_2188 = const()[name = tensor("op_2188"), val = tensor([1, -1, 8, 128])]; tensor p_24_cast_fp16 = reshape(shape = var_2188, x = linear_105_cast_fp16)[name = tensor("p_24_cast_fp16")]; tensor encoder_layers_11_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_11_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152393536)))]; tensor var_2191_cast_fp16 = add(x = q_24_cast_fp16, y = encoder_layers_11_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2191_cast_fp16")]; tensor encoder_layers_11_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_11_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152395648)))]; tensor var_2193_cast_fp16 = add(x = q_24_cast_fp16, y = encoder_layers_11_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2193_cast_fp16")]; tensor x_187_transpose_x_0 = const()[name = tensor("x_187_transpose_x_0"), val = tensor(false)]; tensor x_187_transpose_y_0 = const()[name = tensor("x_187_transpose_y_0"), val = tensor(false)]; tensor transpose_236_perm_0 = const()[name = tensor("transpose_236_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_237_perm_0 = const()[name = tensor("transpose_237_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_237 = transpose(perm = transpose_237_perm_0, x = p_24_cast_fp16)[name = tensor("transpose_390")]; tensor transpose_236 = transpose(perm = transpose_236_perm_0, x = var_2193_cast_fp16)[name = tensor("transpose_391")]; tensor x_187_cast_fp16 = matmul(transpose_x = x_187_transpose_x_0, transpose_y = x_187_transpose_y_0, x = transpose_236, y = transpose_237)[name = tensor("x_187_cast_fp16")]; tensor var_2197_shape_cast_fp16 = shape(x = x_187_cast_fp16)[name = tensor("op_2197_shape_cast_fp16")]; tensor gather_142_axis_0 = const()[name = tensor("gather_142_axis_0"), val = tensor(0)]; tensor gather_142_batch_dims_0 = const()[name = tensor("gather_142_batch_dims_0"), val = tensor(0)]; tensor gather_142_validate_indices_0 = const()[name = tensor("gather_142_validate_indices_0"), val = tensor(false)]; tensor var_2197_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2197_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_142_to_uint16 = const()[name = tensor("select_142_to_uint16"), val = tensor(0)]; tensor var_2197_shape_cast_fp16_to_uint16 = cast(dtype = var_2197_shape_cast_fp16_to_uint16_dtype_0, x = var_2197_shape_cast_fp16)[name = tensor("cast_127")]; tensor gather_142_cast_uint16 = gather(axis = gather_142_axis_0, batch_dims = gather_142_batch_dims_0, indices = select_142_to_uint16, validate_indices = gather_142_validate_indices_0, x = var_2197_shape_cast_fp16_to_uint16)[name = tensor("gather_142_cast_uint16")]; tensor gather_142_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_142_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_143 = const()[name = tensor("gather_143"), val = tensor(8)]; tensor gather_144_axis_0 = const()[name = tensor("gather_144_axis_0"), val = tensor(0)]; tensor gather_144_batch_dims_0 = const()[name = tensor("gather_144_batch_dims_0"), val = tensor(0)]; tensor gather_144_validate_indices_0 = const()[name = tensor("gather_144_validate_indices_0"), val = tensor(false)]; tensor select_144_to_uint16 = const()[name = tensor("select_144_to_uint16"), val = tensor(2)]; tensor gather_144_cast_uint16 = gather(axis = gather_144_axis_0, batch_dims = gather_144_batch_dims_0, indices = select_144_to_uint16, validate_indices = gather_144_validate_indices_0, x = var_2197_shape_cast_fp16_to_uint16)[name = tensor("gather_144_cast_uint16")]; tensor gather_144_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_144_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_145_axis_0 = const()[name = tensor("gather_145_axis_0"), val = tensor(0)]; tensor gather_145_batch_dims_0 = const()[name = tensor("gather_145_batch_dims_0"), val = tensor(0)]; tensor gather_145_validate_indices_0 = const()[name = tensor("gather_145_validate_indices_0"), val = tensor(false)]; tensor select_145_to_uint16 = const()[name = tensor("select_145_to_uint16"), val = tensor(3)]; tensor gather_145_cast_uint16 = gather(axis = gather_145_axis_0, batch_dims = gather_145_batch_dims_0, indices = select_145_to_uint16, validate_indices = gather_145_validate_indices_0, x = var_2197_shape_cast_fp16_to_uint16)[name = tensor("gather_145_cast_uint16")]; tensor gather_145_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_145_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_26_pad_0 = const()[name = tensor("x0_26_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_26_mode_0 = const()[name = tensor("x0_26_mode_0"), val = tensor("constant")]; tensor const_33_to_fp16 = const()[name = tensor("const_33_to_fp16"), val = tensor(0x0p+0)]; tensor x0_26_cast_fp16 = pad(constant_val = const_33_to_fp16, mode = x0_26_mode_0, pad = x0_26_pad_0, x = x_187_cast_fp16)[name = tensor("x0_26_cast_fp16")]; tensor concat_104_axis_0 = const()[name = tensor("concat_104_axis_0"), val = tensor(0)]; tensor concat_104_interleave_0 = const()[name = tensor("concat_104_interleave_0"), val = tensor(false)]; tensor gather_142_cast_uint16_to_int32 = cast(dtype = gather_142_cast_uint16_to_int32_dtype_0, x = gather_142_cast_uint16)[name = tensor("cast_125")]; tensor gather_144_cast_uint16_to_int32 = cast(dtype = gather_144_cast_uint16_to_int32_dtype_0, x = gather_144_cast_uint16)[name = tensor("cast_126")]; tensor concat_104 = concat(axis = concat_104_axis_0, interleave = concat_104_interleave_0, values = (gather_142_cast_uint16_to_int32, gather_143, var_21, gather_144_cast_uint16_to_int32))[name = tensor("concat_104")]; tensor x1_24_cast_fp16 = reshape(shape = concat_104, x = x0_26_cast_fp16)[name = tensor("x1_24_cast_fp16")]; tensor var_2207_begin_0 = const()[name = tensor("op_2207_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2207_end_0 = const()[name = tensor("op_2207_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_2207_end_mask_0 = const()[name = tensor("op_2207_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2207_cast_fp16 = slice_by_index(begin = var_2207_begin_0, end = var_2207_end_0, end_mask = var_2207_end_mask_0, x = x1_24_cast_fp16)[name = tensor("op_2207_cast_fp16")]; tensor concat_105_axis_0 = const()[name = tensor("concat_105_axis_0"), val = tensor(0)]; tensor concat_105_interleave_0 = const()[name = tensor("concat_105_interleave_0"), val = tensor(false)]; tensor gather_145_cast_uint16_to_int32 = cast(dtype = gather_145_cast_uint16_to_int32_dtype_0, x = gather_145_cast_uint16)[name = tensor("cast_124")]; tensor concat_105 = concat(axis = concat_105_axis_0, interleave = concat_105_interleave_0, values = (gather_142_cast_uint16_to_int32, gather_143, gather_144_cast_uint16_to_int32, gather_145_cast_uint16_to_int32))[name = tensor("concat_105")]; tensor matrix_bd_24_cast_fp16 = reshape(shape = concat_105, x = var_2207_cast_fp16)[name = tensor("matrix_bd_24_cast_fp16")]; tensor matrix_ac_24_transpose_x_0 = const()[name = tensor("matrix_ac_24_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_24_transpose_y_0 = const()[name = tensor("matrix_ac_24_transpose_y_0"), val = tensor(false)]; tensor transpose_238_perm_0 = const()[name = tensor("transpose_238_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_239_perm_0 = const()[name = tensor("transpose_239_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_239 = transpose(perm = transpose_239_perm_0, x = k_24_cast_fp16)[name = tensor("transpose_388")]; tensor transpose_238 = transpose(perm = transpose_238_perm_0, x = var_2191_cast_fp16)[name = tensor("transpose_389")]; tensor matrix_ac_24_cast_fp16 = matmul(transpose_x = matrix_ac_24_transpose_x_0, transpose_y = matrix_ac_24_transpose_y_0, x = transpose_238, y = transpose_239)[name = tensor("matrix_ac_24_cast_fp16")]; tensor var_2212_shape_cast_fp16 = shape(x = matrix_ac_24_cast_fp16)[name = tensor("op_2212_shape_cast_fp16")]; tensor gather_146_axis_0 = const()[name = tensor("gather_146_axis_0"), val = tensor(0)]; tensor gather_146_batch_dims_0 = const()[name = tensor("gather_146_batch_dims_0"), val = tensor(0)]; tensor gather_146_validate_indices_0 = const()[name = tensor("gather_146_validate_indices_0"), val = tensor(false)]; tensor var_2212_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2212_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_146_to_uint16 = const()[name = tensor("select_146_to_uint16"), val = tensor(3)]; tensor var_2212_shape_cast_fp16_to_uint16 = cast(dtype = var_2212_shape_cast_fp16_to_uint16_dtype_0, x = var_2212_shape_cast_fp16)[name = tensor("cast_123")]; tensor gather_146_cast_uint16 = gather(axis = gather_146_axis_0, batch_dims = gather_146_batch_dims_0, indices = select_146_to_uint16, validate_indices = gather_146_validate_indices_0, x = var_2212_shape_cast_fp16_to_uint16)[name = tensor("gather_146_cast_uint16")]; tensor gather_146_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_146_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_106_values0_0 = const()[name = tensor("concat_106_values0_0"), val = tensor(0)]; tensor concat_106_values1_0 = const()[name = tensor("concat_106_values1_0"), val = tensor(8)]; tensor concat_106_values2_0 = const()[name = tensor("concat_106_values2_0"), val = tensor(0)]; tensor concat_106_axis_0 = const()[name = tensor("concat_106_axis_0"), val = tensor(0)]; tensor concat_106_interleave_0 = const()[name = tensor("concat_106_interleave_0"), val = tensor(false)]; tensor gather_146_cast_uint16_to_int32 = cast(dtype = gather_146_cast_uint16_to_int32_dtype_0, x = gather_146_cast_uint16)[name = tensor("cast_122")]; tensor concat_106 = concat(axis = concat_106_axis_0, interleave = concat_106_interleave_0, values = (concat_106_values0_0, concat_106_values1_0, concat_106_values2_0, gather_146_cast_uint16_to_int32))[name = tensor("concat_106")]; tensor matrix_bd0_24_begin_0 = const()[name = tensor("matrix_bd0_24_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_24_end_mask_0 = const()[name = tensor("matrix_bd0_24_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_24_cast_fp16 = slice_by_index(begin = matrix_bd0_24_begin_0, end = concat_106, end_mask = matrix_bd0_24_end_mask_0, x = matrix_bd_24_cast_fp16)[name = tensor("matrix_bd0_24_cast_fp16")]; tensor var_2217_cast_fp16 = add(x = matrix_ac_24_cast_fp16, y = matrix_bd0_24_cast_fp16)[name = tensor("op_2217_cast_fp16")]; tensor _inversed_scores_24_y_0_to_fp16 = const()[name = tensor("_inversed_scores_24_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_24_cast_fp16 = mul(x = var_2217_cast_fp16, y = _inversed_scores_24_y_0_to_fp16)[name = tensor("_inversed_scores_24_cast_fp16")]; tensor value_24_cast_fp16 = transpose(perm = value_24_perm_0, x = v_24_cast_fp16)[name = tensor("transpose_387")]; tensor var_2220_shape_cast_fp16 = shape(x = value_24_cast_fp16)[name = tensor("op_2220_shape_cast_fp16")]; tensor gather_147_axis_0 = const()[name = tensor("gather_147_axis_0"), val = tensor(0)]; tensor gather_147_batch_dims_0 = const()[name = tensor("gather_147_batch_dims_0"), val = tensor(0)]; tensor gather_147_validate_indices_0 = const()[name = tensor("gather_147_validate_indices_0"), val = tensor(false)]; tensor var_2220_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2220_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_147_to_uint16 = const()[name = tensor("select_147_to_uint16"), val = tensor(0)]; tensor var_2220_shape_cast_fp16_to_uint16 = cast(dtype = var_2220_shape_cast_fp16_to_uint16_dtype_0, x = var_2220_shape_cast_fp16)[name = tensor("cast_121")]; tensor gather_147_cast_uint16 = gather(axis = gather_147_axis_0, batch_dims = gather_147_batch_dims_0, indices = select_147_to_uint16, validate_indices = gather_147_validate_indices_0, x = var_2220_shape_cast_fp16_to_uint16)[name = tensor("gather_147_cast_uint16")]; tensor gather_147_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_147_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_24_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_24_cast_fp16, cond = mask0_4)[name = tensor("scores0_24_cast_fp16")]; tensor var_2223_cast_fp16 = softmax(axis = var_21, x = scores0_24_cast_fp16)[name = tensor("op_2223_cast_fp16")]; tensor input_169_cast_fp16 = select(a = var_8_to_fp16, b = var_2223_cast_fp16, cond = mask0_4)[name = tensor("input_169_cast_fp16")]; tensor x2_24_transpose_x_0 = const()[name = tensor("x2_24_transpose_x_0"), val = tensor(false)]; tensor x2_24_transpose_y_0 = const()[name = tensor("x2_24_transpose_y_0"), val = tensor(false)]; tensor x2_24_cast_fp16 = matmul(transpose_x = x2_24_transpose_x_0, transpose_y = x2_24_transpose_y_0, x = input_169_cast_fp16, y = value_24_cast_fp16)[name = tensor("x2_24_cast_fp16")]; tensor var_2227_perm_0 = const()[name = tensor("op_2227_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_107_axis_0 = const()[name = tensor("concat_107_axis_0"), val = tensor(0)]; tensor concat_107_interleave_0 = const()[name = tensor("concat_107_interleave_0"), val = tensor(false)]; tensor gather_147_cast_uint16_to_int32 = cast(dtype = gather_147_cast_uint16_to_int32_dtype_0, x = gather_147_cast_uint16)[name = tensor("cast_120")]; tensor concat_107 = concat(axis = concat_107_axis_0, interleave = concat_107_interleave_0, values = (gather_147_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_107")]; tensor var_2227_cast_fp16 = transpose(perm = var_2227_perm_0, x = x2_24_cast_fp16)[name = tensor("transpose_386")]; tensor input0_159_cast_fp16 = reshape(shape = concat_107, x = var_2227_cast_fp16)[name = tensor("input0_159_cast_fp16")]; tensor encoder_layers_11_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152397760))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152922112))), name = tensor("encoder_layers_11_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_106_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_self_attn_linear_out_weight_to_fp16_palettized, x = input0_159_cast_fp16)[name = tensor("linear_106_cast_fp16")]; tensor input0_161_cast_fp16 = add(x = input_167_cast_fp16, y = linear_106_cast_fp16)[name = tensor("input0_161_cast_fp16")]; tensor x_191_axes_0 = const()[name = tensor("x_191_axes_0"), val = tensor([-1])]; tensor encoder_layers_11_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_11_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152922240)))]; tensor encoder_layers_11_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_11_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152924352)))]; tensor x_191_cast_fp16 = layer_norm(axes = x_191_axes_0, beta = encoder_layers_11_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_11_norm_conv_weight_to_fp16, x = input0_161_cast_fp16)[name = tensor("x_191_cast_fp16")]; tensor input_171_perm_0 = const()[name = tensor("input_171_perm_0"), val = tensor([0, 2, 1])]; tensor input0_163_pad_type_0 = const()[name = tensor("input0_163_pad_type_0"), val = tensor("valid")]; tensor input0_163_strides_0 = const()[name = tensor("input0_163_strides_0"), val = tensor([1])]; tensor input0_163_pad_0 = const()[name = tensor("input0_163_pad_0"), val = tensor([0, 0])]; tensor input0_163_dilations_0 = const()[name = tensor("input0_163_dilations_0"), val = tensor([1])]; tensor input0_163_groups_0 = const()[name = tensor("input0_163_groups_0"), val = tensor(1)]; tensor encoder_layers_11_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(152926464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153975104))), name = tensor("encoder_layers_11_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_171_cast_fp16 = transpose(perm = input_171_perm_0, x = x_191_cast_fp16)[name = tensor("transpose_385")]; tensor input0_163_cast_fp16 = conv(dilations = input0_163_dilations_0, groups = input0_163_groups_0, pad = input0_163_pad_0, pad_type = input0_163_pad_type_0, strides = input0_163_strides_0, weight = encoder_layers_11_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_171_cast_fp16)[name = tensor("input0_163_cast_fp16")]; tensor x_193_split_num_splits_0 = const()[name = tensor("x_193_split_num_splits_0"), val = tensor(2)]; tensor x_193_split_axis_0 = const()[name = tensor("x_193_split_axis_0"), val = tensor(1)]; tensor x_193_split_cast_fp16_0, tensor x_193_split_cast_fp16_1 = split(axis = x_193_split_axis_0, num_splits = x_193_split_num_splits_0, x = input0_163_cast_fp16)[name = tensor("x_193_split_cast_fp16")]; tensor x_193_split_1_sigmoid_cast_fp16 = sigmoid(x = x_193_split_cast_fp16_1)[name = tensor("x_193_split_1_sigmoid_cast_fp16")]; tensor x_193_cast_fp16 = mul(x = x_193_split_cast_fp16_0, y = x_193_split_1_sigmoid_cast_fp16)[name = tensor("x_193_cast_fp16")]; tensor input0_165_cast_fp16 = select(a = var_8_to_fp16, b = x_193_cast_fp16, cond = var_457)[name = tensor("input0_165_cast_fp16")]; tensor input0_167_pad_0 = const()[name = tensor("input0_167_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_167_mode_0 = const()[name = tensor("input0_167_mode_0"), val = tensor("constant")]; tensor const_34_to_fp16 = const()[name = tensor("const_34_to_fp16"), val = tensor(0x0p+0)]; tensor input0_167_cast_fp16 = pad(constant_val = const_34_to_fp16, mode = input0_167_mode_0, pad = input0_167_pad_0, x = input0_165_cast_fp16)[name = tensor("input0_167_cast_fp16")]; tensor input1_50_pad_type_0 = const()[name = tensor("input1_50_pad_type_0"), val = tensor("valid")]; tensor input1_50_groups_0 = const()[name = tensor("input1_50_groups_0"), val = tensor(1024)]; tensor input1_50_strides_0 = const()[name = tensor("input1_50_strides_0"), val = tensor([1])]; tensor input1_50_pad_0 = const()[name = tensor("input1_50_pad_0"), val = tensor([0, 0])]; tensor input1_50_dilations_0 = const()[name = tensor("input1_50_dilations_0"), val = tensor([1])]; tensor const_81_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153975232))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153979904))), name = tensor("const_81_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_82_to_fp16 = const()[name = tensor("const_82_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153980032)))]; tensor input_173_cast_fp16 = conv(bias = const_82_to_fp16, dilations = input1_50_dilations_0, groups = input1_50_groups_0, pad = input1_50_pad_0, pad_type = input1_50_pad_type_0, strides = input1_50_strides_0, weight = const_81_to_fp16_palettized, x = input0_167_cast_fp16)[name = tensor("input_173_cast_fp16")]; tensor var_2265_cast_fp16 = silu(x = input_173_cast_fp16)[name = tensor("op_2265_cast_fp16")]; tensor x_195_pad_type_0 = const()[name = tensor("x_195_pad_type_0"), val = tensor("valid")]; tensor x_195_strides_0 = const()[name = tensor("x_195_strides_0"), val = tensor([1])]; tensor x_195_pad_0 = const()[name = tensor("x_195_pad_0"), val = tensor([0, 0])]; tensor x_195_dilations_0 = const()[name = tensor("x_195_dilations_0"), val = tensor([1])]; tensor x_195_groups_0 = const()[name = tensor("x_195_groups_0"), val = tensor(1)]; tensor encoder_layers_11_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(153982144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154506496))), name = tensor("encoder_layers_11_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_195_cast_fp16 = conv(dilations = x_195_dilations_0, groups = x_195_groups_0, pad = x_195_pad_0, pad_type = x_195_pad_type_0, strides = x_195_strides_0, weight = encoder_layers_11_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2265_cast_fp16)[name = tensor("x_195_cast_fp16")]; tensor var_2272_perm_0 = const()[name = tensor("op_2272_perm_0"), val = tensor([0, 2, 1])]; tensor var_2272_cast_fp16 = transpose(perm = var_2272_perm_0, x = x_195_cast_fp16)[name = tensor("transpose_384")]; tensor input1_52_cast_fp16 = add(x = input0_161_cast_fp16, y = var_2272_cast_fp16)[name = tensor("input1_52_cast_fp16")]; tensor input0_169_axes_0 = const()[name = tensor("input0_169_axes_0"), val = tensor([-1])]; tensor encoder_layers_11_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_11_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154506624)))]; tensor encoder_layers_11_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_11_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154508736)))]; tensor input0_169_cast_fp16 = layer_norm(axes = input0_169_axes_0, beta = encoder_layers_11_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_11_norm_feed_forward2_weight_to_fp16, x = input1_52_cast_fp16)[name = tensor("input0_169_cast_fp16")]; tensor encoder_layers_11_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(154510848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156608064))), name = tensor("encoder_layers_11_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_107_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_11_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_169_cast_fp16)[name = tensor("linear_107_cast_fp16")]; tensor var_2283_cast_fp16 = silu(x = linear_107_cast_fp16)[name = tensor("op_2283_cast_fp16")]; tensor encoder_layers_11_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(156608192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158705408))), name = tensor("encoder_layers_11_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_108_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_11_feed_forward2_linear2_weight_to_fp16_palettized, x = var_2283_cast_fp16)[name = tensor("linear_108_cast_fp16")]; tensor var_2288_to_fp16 = const()[name = tensor("op_2288_to_fp16"), val = tensor(0x1p-1)]; tensor var_2289_cast_fp16 = mul(x = linear_108_cast_fp16, y = var_2288_to_fp16)[name = tensor("op_2289_cast_fp16")]; tensor input2_26_cast_fp16 = add(x = input1_52_cast_fp16, y = var_2289_cast_fp16)[name = tensor("input2_26_cast_fp16")]; tensor input0_171_axes_0 = const()[name = tensor("input0_171_axes_0"), val = tensor([-1])]; tensor encoder_layers_11_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_11_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158705536)))]; tensor encoder_layers_11_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_11_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158707648)))]; tensor input0_171_cast_fp16 = layer_norm(axes = input0_171_axes_0, beta = encoder_layers_11_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_11_norm_out_weight_to_fp16, x = input2_26_cast_fp16)[name = tensor("input0_171_cast_fp16")]; tensor input_177_axes_0 = const()[name = tensor("input_177_axes_0"), val = tensor([-1])]; tensor encoder_layers_12_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_12_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158709760)))]; tensor encoder_layers_12_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_12_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158711872)))]; tensor input_177_cast_fp16 = layer_norm(axes = input_177_axes_0, beta = encoder_layers_12_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_12_norm_feed_forward1_weight_to_fp16, x = input0_171_cast_fp16)[name = tensor("input_177_cast_fp16")]; tensor encoder_layers_12_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(158713984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160811200))), name = tensor("encoder_layers_12_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_109_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_12_feed_forward1_linear1_weight_to_fp16_palettized, x = input_177_cast_fp16)[name = tensor("linear_109_cast_fp16")]; tensor var_2312_cast_fp16 = silu(x = linear_109_cast_fp16)[name = tensor("op_2312_cast_fp16")]; tensor encoder_layers_12_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(160811328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162908544))), name = tensor("encoder_layers_12_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_110_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_feed_forward1_linear2_weight_to_fp16_palettized, x = var_2312_cast_fp16)[name = tensor("linear_110_cast_fp16")]; tensor var_2317_to_fp16 = const()[name = tensor("op_2317_to_fp16"), val = tensor(0x1p-1)]; tensor var_2318_cast_fp16 = mul(x = linear_110_cast_fp16, y = var_2317_to_fp16)[name = tensor("op_2318_cast_fp16")]; tensor input_181_cast_fp16 = add(x = input0_171_cast_fp16, y = var_2318_cast_fp16)[name = tensor("input_181_cast_fp16")]; tensor query_26_axes_0 = const()[name = tensor("query_26_axes_0"), val = tensor([-1])]; tensor encoder_layers_12_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_12_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162908672)))]; tensor encoder_layers_12_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_12_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162910784)))]; tensor query_26_cast_fp16 = layer_norm(axes = query_26_axes_0, beta = encoder_layers_12_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_12_norm_self_att_weight_to_fp16, x = input_181_cast_fp16)[name = tensor("query_26_cast_fp16")]; tensor var_2331_shape_cast_fp16 = shape(x = query_26_cast_fp16)[name = tensor("op_2331_shape_cast_fp16")]; tensor gather_148_axis_0 = const()[name = tensor("gather_148_axis_0"), val = tensor(0)]; tensor gather_148_batch_dims_0 = const()[name = tensor("gather_148_batch_dims_0"), val = tensor(0)]; tensor gather_148_validate_indices_0 = const()[name = tensor("gather_148_validate_indices_0"), val = tensor(false)]; tensor var_2331_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2331_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_148_to_uint16 = const()[name = tensor("select_148_to_uint16"), val = tensor(0)]; tensor var_2331_shape_cast_fp16_to_uint16 = cast(dtype = var_2331_shape_cast_fp16_to_uint16_dtype_0, x = var_2331_shape_cast_fp16)[name = tensor("cast_119")]; tensor gather_148_cast_uint16 = gather(axis = gather_148_axis_0, batch_dims = gather_148_batch_dims_0, indices = select_148_to_uint16, validate_indices = gather_148_validate_indices_0, x = var_2331_shape_cast_fp16_to_uint16)[name = tensor("gather_148_cast_uint16")]; tensor gather_148_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_148_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_12_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(162912896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163437248))), name = tensor("encoder_layers_12_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_111_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_self_attn_linear_q_weight_to_fp16_palettized, x = query_26_cast_fp16)[name = tensor("linear_111_cast_fp16")]; tensor concat_108_axis_0 = const()[name = tensor("concat_108_axis_0"), val = tensor(0)]; tensor concat_108_interleave_0 = const()[name = tensor("concat_108_interleave_0"), val = tensor(false)]; tensor gather_148_cast_uint16_to_int32 = cast(dtype = gather_148_cast_uint16_to_int32_dtype_0, x = gather_148_cast_uint16)[name = tensor("cast_118")]; tensor concat_108 = concat(axis = concat_108_axis_0, interleave = concat_108_interleave_0, values = (gather_148_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_108")]; tensor q_26_cast_fp16 = reshape(shape = concat_108, x = linear_111_cast_fp16)[name = tensor("q_26_cast_fp16")]; tensor encoder_layers_12_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163437376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163961728))), name = tensor("encoder_layers_12_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_112_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_self_attn_linear_k_weight_to_fp16_palettized, x = query_26_cast_fp16)[name = tensor("linear_112_cast_fp16")]; tensor k_26_cast_fp16 = reshape(shape = concat_108, x = linear_112_cast_fp16)[name = tensor("k_26_cast_fp16")]; tensor encoder_layers_12_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(163961856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164486208))), name = tensor("encoder_layers_12_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_113_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_self_attn_linear_v_weight_to_fp16_palettized, x = query_26_cast_fp16)[name = tensor("linear_113_cast_fp16")]; tensor v_26_cast_fp16 = reshape(shape = concat_108, x = linear_113_cast_fp16)[name = tensor("v_26_cast_fp16")]; tensor value_26_perm_0 = const()[name = tensor("value_26_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_12_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(164486336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165010688))), name = tensor("encoder_layers_12_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_114_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_114_cast_fp16")]; tensor var_2351 = const()[name = tensor("op_2351"), val = tensor([1, -1, 8, 128])]; tensor p_26_cast_fp16 = reshape(shape = var_2351, x = linear_114_cast_fp16)[name = tensor("p_26_cast_fp16")]; tensor encoder_layers_12_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_12_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165010816)))]; tensor var_2354_cast_fp16 = add(x = q_26_cast_fp16, y = encoder_layers_12_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2354_cast_fp16")]; tensor encoder_layers_12_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_12_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165012928)))]; tensor var_2356_cast_fp16 = add(x = q_26_cast_fp16, y = encoder_layers_12_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2356_cast_fp16")]; tensor x_203_transpose_x_0 = const()[name = tensor("x_203_transpose_x_0"), val = tensor(false)]; tensor x_203_transpose_y_0 = const()[name = tensor("x_203_transpose_y_0"), val = tensor(false)]; tensor transpose_240_perm_0 = const()[name = tensor("transpose_240_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_241_perm_0 = const()[name = tensor("transpose_241_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_241 = transpose(perm = transpose_241_perm_0, x = p_26_cast_fp16)[name = tensor("transpose_382")]; tensor transpose_240 = transpose(perm = transpose_240_perm_0, x = var_2356_cast_fp16)[name = tensor("transpose_383")]; tensor x_203_cast_fp16 = matmul(transpose_x = x_203_transpose_x_0, transpose_y = x_203_transpose_y_0, x = transpose_240, y = transpose_241)[name = tensor("x_203_cast_fp16")]; tensor var_2360_shape_cast_fp16 = shape(x = x_203_cast_fp16)[name = tensor("op_2360_shape_cast_fp16")]; tensor gather_150_axis_0 = const()[name = tensor("gather_150_axis_0"), val = tensor(0)]; tensor gather_150_batch_dims_0 = const()[name = tensor("gather_150_batch_dims_0"), val = tensor(0)]; tensor gather_150_validate_indices_0 = const()[name = tensor("gather_150_validate_indices_0"), val = tensor(false)]; tensor var_2360_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2360_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_150_to_uint16 = const()[name = tensor("select_150_to_uint16"), val = tensor(0)]; tensor var_2360_shape_cast_fp16_to_uint16 = cast(dtype = var_2360_shape_cast_fp16_to_uint16_dtype_0, x = var_2360_shape_cast_fp16)[name = tensor("cast_117")]; tensor gather_150_cast_uint16 = gather(axis = gather_150_axis_0, batch_dims = gather_150_batch_dims_0, indices = select_150_to_uint16, validate_indices = gather_150_validate_indices_0, x = var_2360_shape_cast_fp16_to_uint16)[name = tensor("gather_150_cast_uint16")]; tensor gather_150_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_150_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_151 = const()[name = tensor("gather_151"), val = tensor(8)]; tensor gather_152_axis_0 = const()[name = tensor("gather_152_axis_0"), val = tensor(0)]; tensor gather_152_batch_dims_0 = const()[name = tensor("gather_152_batch_dims_0"), val = tensor(0)]; tensor gather_152_validate_indices_0 = const()[name = tensor("gather_152_validate_indices_0"), val = tensor(false)]; tensor select_152_to_uint16 = const()[name = tensor("select_152_to_uint16"), val = tensor(2)]; tensor gather_152_cast_uint16 = gather(axis = gather_152_axis_0, batch_dims = gather_152_batch_dims_0, indices = select_152_to_uint16, validate_indices = gather_152_validate_indices_0, x = var_2360_shape_cast_fp16_to_uint16)[name = tensor("gather_152_cast_uint16")]; tensor gather_152_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_152_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_153_axis_0 = const()[name = tensor("gather_153_axis_0"), val = tensor(0)]; tensor gather_153_batch_dims_0 = const()[name = tensor("gather_153_batch_dims_0"), val = tensor(0)]; tensor gather_153_validate_indices_0 = const()[name = tensor("gather_153_validate_indices_0"), val = tensor(false)]; tensor select_153_to_uint16 = const()[name = tensor("select_153_to_uint16"), val = tensor(3)]; tensor gather_153_cast_uint16 = gather(axis = gather_153_axis_0, batch_dims = gather_153_batch_dims_0, indices = select_153_to_uint16, validate_indices = gather_153_validate_indices_0, x = var_2360_shape_cast_fp16_to_uint16)[name = tensor("gather_153_cast_uint16")]; tensor gather_153_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_153_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_28_pad_0 = const()[name = tensor("x0_28_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_28_mode_0 = const()[name = tensor("x0_28_mode_0"), val = tensor("constant")]; tensor const_35_to_fp16 = const()[name = tensor("const_35_to_fp16"), val = tensor(0x0p+0)]; tensor x0_28_cast_fp16 = pad(constant_val = const_35_to_fp16, mode = x0_28_mode_0, pad = x0_28_pad_0, x = x_203_cast_fp16)[name = tensor("x0_28_cast_fp16")]; tensor concat_111_axis_0 = const()[name = tensor("concat_111_axis_0"), val = tensor(0)]; tensor concat_111_interleave_0 = const()[name = tensor("concat_111_interleave_0"), val = tensor(false)]; tensor gather_150_cast_uint16_to_int32 = cast(dtype = gather_150_cast_uint16_to_int32_dtype_0, x = gather_150_cast_uint16)[name = tensor("cast_115")]; tensor gather_152_cast_uint16_to_int32 = cast(dtype = gather_152_cast_uint16_to_int32_dtype_0, x = gather_152_cast_uint16)[name = tensor("cast_116")]; tensor concat_111 = concat(axis = concat_111_axis_0, interleave = concat_111_interleave_0, values = (gather_150_cast_uint16_to_int32, gather_151, var_21, gather_152_cast_uint16_to_int32))[name = tensor("concat_111")]; tensor x1_26_cast_fp16 = reshape(shape = concat_111, x = x0_28_cast_fp16)[name = tensor("x1_26_cast_fp16")]; tensor var_2370_begin_0 = const()[name = tensor("op_2370_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2370_end_0 = const()[name = tensor("op_2370_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_2370_end_mask_0 = const()[name = tensor("op_2370_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2370_cast_fp16 = slice_by_index(begin = var_2370_begin_0, end = var_2370_end_0, end_mask = var_2370_end_mask_0, x = x1_26_cast_fp16)[name = tensor("op_2370_cast_fp16")]; tensor concat_112_axis_0 = const()[name = tensor("concat_112_axis_0"), val = tensor(0)]; tensor concat_112_interleave_0 = const()[name = tensor("concat_112_interleave_0"), val = tensor(false)]; tensor gather_153_cast_uint16_to_int32 = cast(dtype = gather_153_cast_uint16_to_int32_dtype_0, x = gather_153_cast_uint16)[name = tensor("cast_114")]; tensor concat_112 = concat(axis = concat_112_axis_0, interleave = concat_112_interleave_0, values = (gather_150_cast_uint16_to_int32, gather_151, gather_152_cast_uint16_to_int32, gather_153_cast_uint16_to_int32))[name = tensor("concat_112")]; tensor matrix_bd_26_cast_fp16 = reshape(shape = concat_112, x = var_2370_cast_fp16)[name = tensor("matrix_bd_26_cast_fp16")]; tensor matrix_ac_26_transpose_x_0 = const()[name = tensor("matrix_ac_26_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_26_transpose_y_0 = const()[name = tensor("matrix_ac_26_transpose_y_0"), val = tensor(false)]; tensor transpose_242_perm_0 = const()[name = tensor("transpose_242_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_243_perm_0 = const()[name = tensor("transpose_243_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_243 = transpose(perm = transpose_243_perm_0, x = k_26_cast_fp16)[name = tensor("transpose_380")]; tensor transpose_242 = transpose(perm = transpose_242_perm_0, x = var_2354_cast_fp16)[name = tensor("transpose_381")]; tensor matrix_ac_26_cast_fp16 = matmul(transpose_x = matrix_ac_26_transpose_x_0, transpose_y = matrix_ac_26_transpose_y_0, x = transpose_242, y = transpose_243)[name = tensor("matrix_ac_26_cast_fp16")]; tensor var_2375_shape_cast_fp16 = shape(x = matrix_ac_26_cast_fp16)[name = tensor("op_2375_shape_cast_fp16")]; tensor gather_154_axis_0 = const()[name = tensor("gather_154_axis_0"), val = tensor(0)]; tensor gather_154_batch_dims_0 = const()[name = tensor("gather_154_batch_dims_0"), val = tensor(0)]; tensor gather_154_validate_indices_0 = const()[name = tensor("gather_154_validate_indices_0"), val = tensor(false)]; tensor var_2375_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2375_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_154_to_uint16 = const()[name = tensor("select_154_to_uint16"), val = tensor(3)]; tensor var_2375_shape_cast_fp16_to_uint16 = cast(dtype = var_2375_shape_cast_fp16_to_uint16_dtype_0, x = var_2375_shape_cast_fp16)[name = tensor("cast_113")]; tensor gather_154_cast_uint16 = gather(axis = gather_154_axis_0, batch_dims = gather_154_batch_dims_0, indices = select_154_to_uint16, validate_indices = gather_154_validate_indices_0, x = var_2375_shape_cast_fp16_to_uint16)[name = tensor("gather_154_cast_uint16")]; tensor gather_154_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_154_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_113_values0_0 = const()[name = tensor("concat_113_values0_0"), val = tensor(0)]; tensor concat_113_values1_0 = const()[name = tensor("concat_113_values1_0"), val = tensor(8)]; tensor concat_113_values2_0 = const()[name = tensor("concat_113_values2_0"), val = tensor(0)]; tensor concat_113_axis_0 = const()[name = tensor("concat_113_axis_0"), val = tensor(0)]; tensor concat_113_interleave_0 = const()[name = tensor("concat_113_interleave_0"), val = tensor(false)]; tensor gather_154_cast_uint16_to_int32 = cast(dtype = gather_154_cast_uint16_to_int32_dtype_0, x = gather_154_cast_uint16)[name = tensor("cast_112")]; tensor concat_113 = concat(axis = concat_113_axis_0, interleave = concat_113_interleave_0, values = (concat_113_values0_0, concat_113_values1_0, concat_113_values2_0, gather_154_cast_uint16_to_int32))[name = tensor("concat_113")]; tensor matrix_bd0_26_begin_0 = const()[name = tensor("matrix_bd0_26_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_26_end_mask_0 = const()[name = tensor("matrix_bd0_26_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_26_cast_fp16 = slice_by_index(begin = matrix_bd0_26_begin_0, end = concat_113, end_mask = matrix_bd0_26_end_mask_0, x = matrix_bd_26_cast_fp16)[name = tensor("matrix_bd0_26_cast_fp16")]; tensor var_2380_cast_fp16 = add(x = matrix_ac_26_cast_fp16, y = matrix_bd0_26_cast_fp16)[name = tensor("op_2380_cast_fp16")]; tensor _inversed_scores_26_y_0_to_fp16 = const()[name = tensor("_inversed_scores_26_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_26_cast_fp16 = mul(x = var_2380_cast_fp16, y = _inversed_scores_26_y_0_to_fp16)[name = tensor("_inversed_scores_26_cast_fp16")]; tensor value_26_cast_fp16 = transpose(perm = value_26_perm_0, x = v_26_cast_fp16)[name = tensor("transpose_379")]; tensor var_2383_shape_cast_fp16 = shape(x = value_26_cast_fp16)[name = tensor("op_2383_shape_cast_fp16")]; tensor gather_155_axis_0 = const()[name = tensor("gather_155_axis_0"), val = tensor(0)]; tensor gather_155_batch_dims_0 = const()[name = tensor("gather_155_batch_dims_0"), val = tensor(0)]; tensor gather_155_validate_indices_0 = const()[name = tensor("gather_155_validate_indices_0"), val = tensor(false)]; tensor var_2383_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2383_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_155_to_uint16 = const()[name = tensor("select_155_to_uint16"), val = tensor(0)]; tensor var_2383_shape_cast_fp16_to_uint16 = cast(dtype = var_2383_shape_cast_fp16_to_uint16_dtype_0, x = var_2383_shape_cast_fp16)[name = tensor("cast_111")]; tensor gather_155_cast_uint16 = gather(axis = gather_155_axis_0, batch_dims = gather_155_batch_dims_0, indices = select_155_to_uint16, validate_indices = gather_155_validate_indices_0, x = var_2383_shape_cast_fp16_to_uint16)[name = tensor("gather_155_cast_uint16")]; tensor gather_155_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_155_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_26_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_26_cast_fp16, cond = mask0_4)[name = tensor("scores0_26_cast_fp16")]; tensor var_2386_cast_fp16 = softmax(axis = var_21, x = scores0_26_cast_fp16)[name = tensor("op_2386_cast_fp16")]; tensor input_183_cast_fp16 = select(a = var_8_to_fp16, b = var_2386_cast_fp16, cond = mask0_4)[name = tensor("input_183_cast_fp16")]; tensor x2_26_transpose_x_0 = const()[name = tensor("x2_26_transpose_x_0"), val = tensor(false)]; tensor x2_26_transpose_y_0 = const()[name = tensor("x2_26_transpose_y_0"), val = tensor(false)]; tensor x2_26_cast_fp16 = matmul(transpose_x = x2_26_transpose_x_0, transpose_y = x2_26_transpose_y_0, x = input_183_cast_fp16, y = value_26_cast_fp16)[name = tensor("x2_26_cast_fp16")]; tensor var_2390_perm_0 = const()[name = tensor("op_2390_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_114_axis_0 = const()[name = tensor("concat_114_axis_0"), val = tensor(0)]; tensor concat_114_interleave_0 = const()[name = tensor("concat_114_interleave_0"), val = tensor(false)]; tensor gather_155_cast_uint16_to_int32 = cast(dtype = gather_155_cast_uint16_to_int32_dtype_0, x = gather_155_cast_uint16)[name = tensor("cast_110")]; tensor concat_114 = concat(axis = concat_114_axis_0, interleave = concat_114_interleave_0, values = (gather_155_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_114")]; tensor var_2390_cast_fp16 = transpose(perm = var_2390_perm_0, x = x2_26_cast_fp16)[name = tensor("transpose_378")]; tensor input0_173_cast_fp16 = reshape(shape = concat_114, x = var_2390_cast_fp16)[name = tensor("input0_173_cast_fp16")]; tensor encoder_layers_12_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165015040))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165539392))), name = tensor("encoder_layers_12_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_115_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_self_attn_linear_out_weight_to_fp16_palettized, x = input0_173_cast_fp16)[name = tensor("linear_115_cast_fp16")]; tensor input0_175_cast_fp16 = add(x = input_181_cast_fp16, y = linear_115_cast_fp16)[name = tensor("input0_175_cast_fp16")]; tensor x_207_axes_0 = const()[name = tensor("x_207_axes_0"), val = tensor([-1])]; tensor encoder_layers_12_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_12_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165539520)))]; tensor encoder_layers_12_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_12_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165541632)))]; tensor x_207_cast_fp16 = layer_norm(axes = x_207_axes_0, beta = encoder_layers_12_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_12_norm_conv_weight_to_fp16, x = input0_175_cast_fp16)[name = tensor("x_207_cast_fp16")]; tensor input_185_perm_0 = const()[name = tensor("input_185_perm_0"), val = tensor([0, 2, 1])]; tensor input0_177_pad_type_0 = const()[name = tensor("input0_177_pad_type_0"), val = tensor("valid")]; tensor input0_177_strides_0 = const()[name = tensor("input0_177_strides_0"), val = tensor([1])]; tensor input0_177_pad_0 = const()[name = tensor("input0_177_pad_0"), val = tensor([0, 0])]; tensor input0_177_dilations_0 = const()[name = tensor("input0_177_dilations_0"), val = tensor([1])]; tensor input0_177_groups_0 = const()[name = tensor("input0_177_groups_0"), val = tensor(1)]; tensor encoder_layers_12_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(165543744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166592384))), name = tensor("encoder_layers_12_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_185_cast_fp16 = transpose(perm = input_185_perm_0, x = x_207_cast_fp16)[name = tensor("transpose_377")]; tensor input0_177_cast_fp16 = conv(dilations = input0_177_dilations_0, groups = input0_177_groups_0, pad = input0_177_pad_0, pad_type = input0_177_pad_type_0, strides = input0_177_strides_0, weight = encoder_layers_12_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_185_cast_fp16)[name = tensor("input0_177_cast_fp16")]; tensor x_209_split_num_splits_0 = const()[name = tensor("x_209_split_num_splits_0"), val = tensor(2)]; tensor x_209_split_axis_0 = const()[name = tensor("x_209_split_axis_0"), val = tensor(1)]; tensor x_209_split_cast_fp16_0, tensor x_209_split_cast_fp16_1 = split(axis = x_209_split_axis_0, num_splits = x_209_split_num_splits_0, x = input0_177_cast_fp16)[name = tensor("x_209_split_cast_fp16")]; tensor x_209_split_1_sigmoid_cast_fp16 = sigmoid(x = x_209_split_cast_fp16_1)[name = tensor("x_209_split_1_sigmoid_cast_fp16")]; tensor x_209_cast_fp16 = mul(x = x_209_split_cast_fp16_0, y = x_209_split_1_sigmoid_cast_fp16)[name = tensor("x_209_cast_fp16")]; tensor input0_179_cast_fp16 = select(a = var_8_to_fp16, b = x_209_cast_fp16, cond = var_457)[name = tensor("input0_179_cast_fp16")]; tensor input0_181_pad_0 = const()[name = tensor("input0_181_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_181_mode_0 = const()[name = tensor("input0_181_mode_0"), val = tensor("constant")]; tensor const_36_to_fp16 = const()[name = tensor("const_36_to_fp16"), val = tensor(0x0p+0)]; tensor input0_181_cast_fp16 = pad(constant_val = const_36_to_fp16, mode = input0_181_mode_0, pad = input0_181_pad_0, x = input0_179_cast_fp16)[name = tensor("input0_181_cast_fp16")]; tensor input1_54_pad_type_0 = const()[name = tensor("input1_54_pad_type_0"), val = tensor("valid")]; tensor input1_54_groups_0 = const()[name = tensor("input1_54_groups_0"), val = tensor(1024)]; tensor input1_54_strides_0 = const()[name = tensor("input1_54_strides_0"), val = tensor([1])]; tensor input1_54_pad_0 = const()[name = tensor("input1_54_pad_0"), val = tensor([0, 0])]; tensor input1_54_dilations_0 = const()[name = tensor("input1_54_dilations_0"), val = tensor([1])]; tensor const_83_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166592512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166597184))), name = tensor("const_83_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_84_to_fp16 = const()[name = tensor("const_84_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166597312)))]; tensor input_187_cast_fp16 = conv(bias = const_84_to_fp16, dilations = input1_54_dilations_0, groups = input1_54_groups_0, pad = input1_54_pad_0, pad_type = input1_54_pad_type_0, strides = input1_54_strides_0, weight = const_83_to_fp16_palettized, x = input0_181_cast_fp16)[name = tensor("input_187_cast_fp16")]; tensor var_2428_cast_fp16 = silu(x = input_187_cast_fp16)[name = tensor("op_2428_cast_fp16")]; tensor x_211_pad_type_0 = const()[name = tensor("x_211_pad_type_0"), val = tensor("valid")]; tensor x_211_strides_0 = const()[name = tensor("x_211_strides_0"), val = tensor([1])]; tensor x_211_pad_0 = const()[name = tensor("x_211_pad_0"), val = tensor([0, 0])]; tensor x_211_dilations_0 = const()[name = tensor("x_211_dilations_0"), val = tensor([1])]; tensor x_211_groups_0 = const()[name = tensor("x_211_groups_0"), val = tensor(1)]; tensor encoder_layers_12_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(166599424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167123776))), name = tensor("encoder_layers_12_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_211_cast_fp16 = conv(dilations = x_211_dilations_0, groups = x_211_groups_0, pad = x_211_pad_0, pad_type = x_211_pad_type_0, strides = x_211_strides_0, weight = encoder_layers_12_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2428_cast_fp16)[name = tensor("x_211_cast_fp16")]; tensor var_2435_perm_0 = const()[name = tensor("op_2435_perm_0"), val = tensor([0, 2, 1])]; tensor var_2435_cast_fp16 = transpose(perm = var_2435_perm_0, x = x_211_cast_fp16)[name = tensor("transpose_376")]; tensor input1_56_cast_fp16 = add(x = input0_175_cast_fp16, y = var_2435_cast_fp16)[name = tensor("input1_56_cast_fp16")]; tensor input0_183_axes_0 = const()[name = tensor("input0_183_axes_0"), val = tensor([-1])]; tensor encoder_layers_12_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_12_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167123904)))]; tensor encoder_layers_12_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_12_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167126016)))]; tensor input0_183_cast_fp16 = layer_norm(axes = input0_183_axes_0, beta = encoder_layers_12_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_12_norm_feed_forward2_weight_to_fp16, x = input1_56_cast_fp16)[name = tensor("input0_183_cast_fp16")]; tensor encoder_layers_12_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(167128128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169225344))), name = tensor("encoder_layers_12_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_116_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_12_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_183_cast_fp16)[name = tensor("linear_116_cast_fp16")]; tensor var_2446_cast_fp16 = silu(x = linear_116_cast_fp16)[name = tensor("op_2446_cast_fp16")]; tensor encoder_layers_12_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(169225472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171322688))), name = tensor("encoder_layers_12_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_117_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_12_feed_forward2_linear2_weight_to_fp16_palettized, x = var_2446_cast_fp16)[name = tensor("linear_117_cast_fp16")]; tensor var_2451_to_fp16 = const()[name = tensor("op_2451_to_fp16"), val = tensor(0x1p-1)]; tensor var_2452_cast_fp16 = mul(x = linear_117_cast_fp16, y = var_2451_to_fp16)[name = tensor("op_2452_cast_fp16")]; tensor input2_28_cast_fp16 = add(x = input1_56_cast_fp16, y = var_2452_cast_fp16)[name = tensor("input2_28_cast_fp16")]; tensor input0_185_axes_0 = const()[name = tensor("input0_185_axes_0"), val = tensor([-1])]; tensor encoder_layers_12_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_12_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171322816)))]; tensor encoder_layers_12_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_12_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171324928)))]; tensor input0_185_cast_fp16 = layer_norm(axes = input0_185_axes_0, beta = encoder_layers_12_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_12_norm_out_weight_to_fp16, x = input2_28_cast_fp16)[name = tensor("input0_185_cast_fp16")]; tensor input_191_axes_0 = const()[name = tensor("input_191_axes_0"), val = tensor([-1])]; tensor encoder_layers_13_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_13_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171327040)))]; tensor encoder_layers_13_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_13_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171329152)))]; tensor input_191_cast_fp16 = layer_norm(axes = input_191_axes_0, beta = encoder_layers_13_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_13_norm_feed_forward1_weight_to_fp16, x = input0_185_cast_fp16)[name = tensor("input_191_cast_fp16")]; tensor encoder_layers_13_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(171331264))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173428480))), name = tensor("encoder_layers_13_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_118_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_13_feed_forward1_linear1_weight_to_fp16_palettized, x = input_191_cast_fp16)[name = tensor("linear_118_cast_fp16")]; tensor var_2475_cast_fp16 = silu(x = linear_118_cast_fp16)[name = tensor("op_2475_cast_fp16")]; tensor encoder_layers_13_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(173428608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175525824))), name = tensor("encoder_layers_13_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_119_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_feed_forward1_linear2_weight_to_fp16_palettized, x = var_2475_cast_fp16)[name = tensor("linear_119_cast_fp16")]; tensor var_2480_to_fp16 = const()[name = tensor("op_2480_to_fp16"), val = tensor(0x1p-1)]; tensor var_2481_cast_fp16 = mul(x = linear_119_cast_fp16, y = var_2480_to_fp16)[name = tensor("op_2481_cast_fp16")]; tensor input_195_cast_fp16 = add(x = input0_185_cast_fp16, y = var_2481_cast_fp16)[name = tensor("input_195_cast_fp16")]; tensor query_28_axes_0 = const()[name = tensor("query_28_axes_0"), val = tensor([-1])]; tensor encoder_layers_13_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_13_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175525952)))]; tensor encoder_layers_13_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_13_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175528064)))]; tensor query_28_cast_fp16 = layer_norm(axes = query_28_axes_0, beta = encoder_layers_13_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_13_norm_self_att_weight_to_fp16, x = input_195_cast_fp16)[name = tensor("query_28_cast_fp16")]; tensor var_2494_shape_cast_fp16 = shape(x = query_28_cast_fp16)[name = tensor("op_2494_shape_cast_fp16")]; tensor gather_156_axis_0 = const()[name = tensor("gather_156_axis_0"), val = tensor(0)]; tensor gather_156_batch_dims_0 = const()[name = tensor("gather_156_batch_dims_0"), val = tensor(0)]; tensor gather_156_validate_indices_0 = const()[name = tensor("gather_156_validate_indices_0"), val = tensor(false)]; tensor var_2494_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2494_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_156_to_uint16 = const()[name = tensor("select_156_to_uint16"), val = tensor(0)]; tensor var_2494_shape_cast_fp16_to_uint16 = cast(dtype = var_2494_shape_cast_fp16_to_uint16_dtype_0, x = var_2494_shape_cast_fp16)[name = tensor("cast_109")]; tensor gather_156_cast_uint16 = gather(axis = gather_156_axis_0, batch_dims = gather_156_batch_dims_0, indices = select_156_to_uint16, validate_indices = gather_156_validate_indices_0, x = var_2494_shape_cast_fp16_to_uint16)[name = tensor("gather_156_cast_uint16")]; tensor gather_156_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_156_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_13_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(175530176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176054528))), name = tensor("encoder_layers_13_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_120_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_self_attn_linear_q_weight_to_fp16_palettized, x = query_28_cast_fp16)[name = tensor("linear_120_cast_fp16")]; tensor concat_115_axis_0 = const()[name = tensor("concat_115_axis_0"), val = tensor(0)]; tensor concat_115_interleave_0 = const()[name = tensor("concat_115_interleave_0"), val = tensor(false)]; tensor gather_156_cast_uint16_to_int32 = cast(dtype = gather_156_cast_uint16_to_int32_dtype_0, x = gather_156_cast_uint16)[name = tensor("cast_108")]; tensor concat_115 = concat(axis = concat_115_axis_0, interleave = concat_115_interleave_0, values = (gather_156_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_115")]; tensor q_28_cast_fp16 = reshape(shape = concat_115, x = linear_120_cast_fp16)[name = tensor("q_28_cast_fp16")]; tensor encoder_layers_13_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176054656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176579008))), name = tensor("encoder_layers_13_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_121_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_self_attn_linear_k_weight_to_fp16_palettized, x = query_28_cast_fp16)[name = tensor("linear_121_cast_fp16")]; tensor k_28_cast_fp16 = reshape(shape = concat_115, x = linear_121_cast_fp16)[name = tensor("k_28_cast_fp16")]; tensor encoder_layers_13_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(176579136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177103488))), name = tensor("encoder_layers_13_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_122_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_self_attn_linear_v_weight_to_fp16_palettized, x = query_28_cast_fp16)[name = tensor("linear_122_cast_fp16")]; tensor v_28_cast_fp16 = reshape(shape = concat_115, x = linear_122_cast_fp16)[name = tensor("v_28_cast_fp16")]; tensor value_28_perm_0 = const()[name = tensor("value_28_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_13_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177103616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177627968))), name = tensor("encoder_layers_13_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_123_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_123_cast_fp16")]; tensor var_2514 = const()[name = tensor("op_2514"), val = tensor([1, -1, 8, 128])]; tensor p_28_cast_fp16 = reshape(shape = var_2514, x = linear_123_cast_fp16)[name = tensor("p_28_cast_fp16")]; tensor encoder_layers_13_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_13_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177628096)))]; tensor var_2517_cast_fp16 = add(x = q_28_cast_fp16, y = encoder_layers_13_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2517_cast_fp16")]; tensor encoder_layers_13_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_13_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177630208)))]; tensor var_2519_cast_fp16 = add(x = q_28_cast_fp16, y = encoder_layers_13_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2519_cast_fp16")]; tensor x_219_transpose_x_0 = const()[name = tensor("x_219_transpose_x_0"), val = tensor(false)]; tensor x_219_transpose_y_0 = const()[name = tensor("x_219_transpose_y_0"), val = tensor(false)]; tensor transpose_244_perm_0 = const()[name = tensor("transpose_244_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_245_perm_0 = const()[name = tensor("transpose_245_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_245 = transpose(perm = transpose_245_perm_0, x = p_28_cast_fp16)[name = tensor("transpose_374")]; tensor transpose_244 = transpose(perm = transpose_244_perm_0, x = var_2519_cast_fp16)[name = tensor("transpose_375")]; tensor x_219_cast_fp16 = matmul(transpose_x = x_219_transpose_x_0, transpose_y = x_219_transpose_y_0, x = transpose_244, y = transpose_245)[name = tensor("x_219_cast_fp16")]; tensor var_2523_shape_cast_fp16 = shape(x = x_219_cast_fp16)[name = tensor("op_2523_shape_cast_fp16")]; tensor gather_158_axis_0 = const()[name = tensor("gather_158_axis_0"), val = tensor(0)]; tensor gather_158_batch_dims_0 = const()[name = tensor("gather_158_batch_dims_0"), val = tensor(0)]; tensor gather_158_validate_indices_0 = const()[name = tensor("gather_158_validate_indices_0"), val = tensor(false)]; tensor var_2523_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2523_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_158_to_uint16 = const()[name = tensor("select_158_to_uint16"), val = tensor(0)]; tensor var_2523_shape_cast_fp16_to_uint16 = cast(dtype = var_2523_shape_cast_fp16_to_uint16_dtype_0, x = var_2523_shape_cast_fp16)[name = tensor("cast_107")]; tensor gather_158_cast_uint16 = gather(axis = gather_158_axis_0, batch_dims = gather_158_batch_dims_0, indices = select_158_to_uint16, validate_indices = gather_158_validate_indices_0, x = var_2523_shape_cast_fp16_to_uint16)[name = tensor("gather_158_cast_uint16")]; tensor gather_158_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_158_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_159 = const()[name = tensor("gather_159"), val = tensor(8)]; tensor gather_160_axis_0 = const()[name = tensor("gather_160_axis_0"), val = tensor(0)]; tensor gather_160_batch_dims_0 = const()[name = tensor("gather_160_batch_dims_0"), val = tensor(0)]; tensor gather_160_validate_indices_0 = const()[name = tensor("gather_160_validate_indices_0"), val = tensor(false)]; tensor select_160_to_uint16 = const()[name = tensor("select_160_to_uint16"), val = tensor(2)]; tensor gather_160_cast_uint16 = gather(axis = gather_160_axis_0, batch_dims = gather_160_batch_dims_0, indices = select_160_to_uint16, validate_indices = gather_160_validate_indices_0, x = var_2523_shape_cast_fp16_to_uint16)[name = tensor("gather_160_cast_uint16")]; tensor gather_160_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_160_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_161_axis_0 = const()[name = tensor("gather_161_axis_0"), val = tensor(0)]; tensor gather_161_batch_dims_0 = const()[name = tensor("gather_161_batch_dims_0"), val = tensor(0)]; tensor gather_161_validate_indices_0 = const()[name = tensor("gather_161_validate_indices_0"), val = tensor(false)]; tensor select_161_to_uint16 = const()[name = tensor("select_161_to_uint16"), val = tensor(3)]; tensor gather_161_cast_uint16 = gather(axis = gather_161_axis_0, batch_dims = gather_161_batch_dims_0, indices = select_161_to_uint16, validate_indices = gather_161_validate_indices_0, x = var_2523_shape_cast_fp16_to_uint16)[name = tensor("gather_161_cast_uint16")]; tensor gather_161_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_161_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_30_pad_0 = const()[name = tensor("x0_30_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_30_mode_0 = const()[name = tensor("x0_30_mode_0"), val = tensor("constant")]; tensor const_37_to_fp16 = const()[name = tensor("const_37_to_fp16"), val = tensor(0x0p+0)]; tensor x0_30_cast_fp16 = pad(constant_val = const_37_to_fp16, mode = x0_30_mode_0, pad = x0_30_pad_0, x = x_219_cast_fp16)[name = tensor("x0_30_cast_fp16")]; tensor concat_118_axis_0 = const()[name = tensor("concat_118_axis_0"), val = tensor(0)]; tensor concat_118_interleave_0 = const()[name = tensor("concat_118_interleave_0"), val = tensor(false)]; tensor gather_158_cast_uint16_to_int32 = cast(dtype = gather_158_cast_uint16_to_int32_dtype_0, x = gather_158_cast_uint16)[name = tensor("cast_105")]; tensor gather_160_cast_uint16_to_int32 = cast(dtype = gather_160_cast_uint16_to_int32_dtype_0, x = gather_160_cast_uint16)[name = tensor("cast_106")]; tensor concat_118 = concat(axis = concat_118_axis_0, interleave = concat_118_interleave_0, values = (gather_158_cast_uint16_to_int32, gather_159, var_21, gather_160_cast_uint16_to_int32))[name = tensor("concat_118")]; tensor x1_28_cast_fp16 = reshape(shape = concat_118, x = x0_30_cast_fp16)[name = tensor("x1_28_cast_fp16")]; tensor var_2533_begin_0 = const()[name = tensor("op_2533_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2533_end_0 = const()[name = tensor("op_2533_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_2533_end_mask_0 = const()[name = tensor("op_2533_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2533_cast_fp16 = slice_by_index(begin = var_2533_begin_0, end = var_2533_end_0, end_mask = var_2533_end_mask_0, x = x1_28_cast_fp16)[name = tensor("op_2533_cast_fp16")]; tensor concat_119_axis_0 = const()[name = tensor("concat_119_axis_0"), val = tensor(0)]; tensor concat_119_interleave_0 = const()[name = tensor("concat_119_interleave_0"), val = tensor(false)]; tensor gather_161_cast_uint16_to_int32 = cast(dtype = gather_161_cast_uint16_to_int32_dtype_0, x = gather_161_cast_uint16)[name = tensor("cast_104")]; tensor concat_119 = concat(axis = concat_119_axis_0, interleave = concat_119_interleave_0, values = (gather_158_cast_uint16_to_int32, gather_159, gather_160_cast_uint16_to_int32, gather_161_cast_uint16_to_int32))[name = tensor("concat_119")]; tensor matrix_bd_28_cast_fp16 = reshape(shape = concat_119, x = var_2533_cast_fp16)[name = tensor("matrix_bd_28_cast_fp16")]; tensor matrix_ac_28_transpose_x_0 = const()[name = tensor("matrix_ac_28_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_28_transpose_y_0 = const()[name = tensor("matrix_ac_28_transpose_y_0"), val = tensor(false)]; tensor transpose_246_perm_0 = const()[name = tensor("transpose_246_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_247_perm_0 = const()[name = tensor("transpose_247_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_247 = transpose(perm = transpose_247_perm_0, x = k_28_cast_fp16)[name = tensor("transpose_372")]; tensor transpose_246 = transpose(perm = transpose_246_perm_0, x = var_2517_cast_fp16)[name = tensor("transpose_373")]; tensor matrix_ac_28_cast_fp16 = matmul(transpose_x = matrix_ac_28_transpose_x_0, transpose_y = matrix_ac_28_transpose_y_0, x = transpose_246, y = transpose_247)[name = tensor("matrix_ac_28_cast_fp16")]; tensor var_2538_shape_cast_fp16 = shape(x = matrix_ac_28_cast_fp16)[name = tensor("op_2538_shape_cast_fp16")]; tensor gather_162_axis_0 = const()[name = tensor("gather_162_axis_0"), val = tensor(0)]; tensor gather_162_batch_dims_0 = const()[name = tensor("gather_162_batch_dims_0"), val = tensor(0)]; tensor gather_162_validate_indices_0 = const()[name = tensor("gather_162_validate_indices_0"), val = tensor(false)]; tensor var_2538_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2538_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_162_to_uint16 = const()[name = tensor("select_162_to_uint16"), val = tensor(3)]; tensor var_2538_shape_cast_fp16_to_uint16 = cast(dtype = var_2538_shape_cast_fp16_to_uint16_dtype_0, x = var_2538_shape_cast_fp16)[name = tensor("cast_103")]; tensor gather_162_cast_uint16 = gather(axis = gather_162_axis_0, batch_dims = gather_162_batch_dims_0, indices = select_162_to_uint16, validate_indices = gather_162_validate_indices_0, x = var_2538_shape_cast_fp16_to_uint16)[name = tensor("gather_162_cast_uint16")]; tensor gather_162_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_162_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_120_values0_0 = const()[name = tensor("concat_120_values0_0"), val = tensor(0)]; tensor concat_120_values1_0 = const()[name = tensor("concat_120_values1_0"), val = tensor(8)]; tensor concat_120_values2_0 = const()[name = tensor("concat_120_values2_0"), val = tensor(0)]; tensor concat_120_axis_0 = const()[name = tensor("concat_120_axis_0"), val = tensor(0)]; tensor concat_120_interleave_0 = const()[name = tensor("concat_120_interleave_0"), val = tensor(false)]; tensor gather_162_cast_uint16_to_int32 = cast(dtype = gather_162_cast_uint16_to_int32_dtype_0, x = gather_162_cast_uint16)[name = tensor("cast_102")]; tensor concat_120 = concat(axis = concat_120_axis_0, interleave = concat_120_interleave_0, values = (concat_120_values0_0, concat_120_values1_0, concat_120_values2_0, gather_162_cast_uint16_to_int32))[name = tensor("concat_120")]; tensor matrix_bd0_28_begin_0 = const()[name = tensor("matrix_bd0_28_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_28_end_mask_0 = const()[name = tensor("matrix_bd0_28_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_28_cast_fp16 = slice_by_index(begin = matrix_bd0_28_begin_0, end = concat_120, end_mask = matrix_bd0_28_end_mask_0, x = matrix_bd_28_cast_fp16)[name = tensor("matrix_bd0_28_cast_fp16")]; tensor var_2543_cast_fp16 = add(x = matrix_ac_28_cast_fp16, y = matrix_bd0_28_cast_fp16)[name = tensor("op_2543_cast_fp16")]; tensor _inversed_scores_28_y_0_to_fp16 = const()[name = tensor("_inversed_scores_28_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_28_cast_fp16 = mul(x = var_2543_cast_fp16, y = _inversed_scores_28_y_0_to_fp16)[name = tensor("_inversed_scores_28_cast_fp16")]; tensor value_28_cast_fp16 = transpose(perm = value_28_perm_0, x = v_28_cast_fp16)[name = tensor("transpose_371")]; tensor var_2546_shape_cast_fp16 = shape(x = value_28_cast_fp16)[name = tensor("op_2546_shape_cast_fp16")]; tensor gather_163_axis_0 = const()[name = tensor("gather_163_axis_0"), val = tensor(0)]; tensor gather_163_batch_dims_0 = const()[name = tensor("gather_163_batch_dims_0"), val = tensor(0)]; tensor gather_163_validate_indices_0 = const()[name = tensor("gather_163_validate_indices_0"), val = tensor(false)]; tensor var_2546_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2546_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_163_to_uint16 = const()[name = tensor("select_163_to_uint16"), val = tensor(0)]; tensor var_2546_shape_cast_fp16_to_uint16 = cast(dtype = var_2546_shape_cast_fp16_to_uint16_dtype_0, x = var_2546_shape_cast_fp16)[name = tensor("cast_101")]; tensor gather_163_cast_uint16 = gather(axis = gather_163_axis_0, batch_dims = gather_163_batch_dims_0, indices = select_163_to_uint16, validate_indices = gather_163_validate_indices_0, x = var_2546_shape_cast_fp16_to_uint16)[name = tensor("gather_163_cast_uint16")]; tensor gather_163_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_163_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_28_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_28_cast_fp16, cond = mask0_4)[name = tensor("scores0_28_cast_fp16")]; tensor var_2549_cast_fp16 = softmax(axis = var_21, x = scores0_28_cast_fp16)[name = tensor("op_2549_cast_fp16")]; tensor input_197_cast_fp16 = select(a = var_8_to_fp16, b = var_2549_cast_fp16, cond = mask0_4)[name = tensor("input_197_cast_fp16")]; tensor x2_28_transpose_x_0 = const()[name = tensor("x2_28_transpose_x_0"), val = tensor(false)]; tensor x2_28_transpose_y_0 = const()[name = tensor("x2_28_transpose_y_0"), val = tensor(false)]; tensor x2_28_cast_fp16 = matmul(transpose_x = x2_28_transpose_x_0, transpose_y = x2_28_transpose_y_0, x = input_197_cast_fp16, y = value_28_cast_fp16)[name = tensor("x2_28_cast_fp16")]; tensor var_2553_perm_0 = const()[name = tensor("op_2553_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_121_axis_0 = const()[name = tensor("concat_121_axis_0"), val = tensor(0)]; tensor concat_121_interleave_0 = const()[name = tensor("concat_121_interleave_0"), val = tensor(false)]; tensor gather_163_cast_uint16_to_int32 = cast(dtype = gather_163_cast_uint16_to_int32_dtype_0, x = gather_163_cast_uint16)[name = tensor("cast_100")]; tensor concat_121 = concat(axis = concat_121_axis_0, interleave = concat_121_interleave_0, values = (gather_163_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_121")]; tensor var_2553_cast_fp16 = transpose(perm = var_2553_perm_0, x = x2_28_cast_fp16)[name = tensor("transpose_370")]; tensor input0_187_cast_fp16 = reshape(shape = concat_121, x = var_2553_cast_fp16)[name = tensor("input0_187_cast_fp16")]; tensor encoder_layers_13_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(177632320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178156672))), name = tensor("encoder_layers_13_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_124_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_self_attn_linear_out_weight_to_fp16_palettized, x = input0_187_cast_fp16)[name = tensor("linear_124_cast_fp16")]; tensor input0_189_cast_fp16 = add(x = input_195_cast_fp16, y = linear_124_cast_fp16)[name = tensor("input0_189_cast_fp16")]; tensor x_223_axes_0 = const()[name = tensor("x_223_axes_0"), val = tensor([-1])]; tensor encoder_layers_13_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_13_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178156800)))]; tensor encoder_layers_13_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_13_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178158912)))]; tensor x_223_cast_fp16 = layer_norm(axes = x_223_axes_0, beta = encoder_layers_13_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_13_norm_conv_weight_to_fp16, x = input0_189_cast_fp16)[name = tensor("x_223_cast_fp16")]; tensor input_199_perm_0 = const()[name = tensor("input_199_perm_0"), val = tensor([0, 2, 1])]; tensor input0_191_pad_type_0 = const()[name = tensor("input0_191_pad_type_0"), val = tensor("valid")]; tensor input0_191_strides_0 = const()[name = tensor("input0_191_strides_0"), val = tensor([1])]; tensor input0_191_pad_0 = const()[name = tensor("input0_191_pad_0"), val = tensor([0, 0])]; tensor input0_191_dilations_0 = const()[name = tensor("input0_191_dilations_0"), val = tensor([1])]; tensor input0_191_groups_0 = const()[name = tensor("input0_191_groups_0"), val = tensor(1)]; tensor encoder_layers_13_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(178161024))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179209664))), name = tensor("encoder_layers_13_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_199_cast_fp16 = transpose(perm = input_199_perm_0, x = x_223_cast_fp16)[name = tensor("transpose_369")]; tensor input0_191_cast_fp16 = conv(dilations = input0_191_dilations_0, groups = input0_191_groups_0, pad = input0_191_pad_0, pad_type = input0_191_pad_type_0, strides = input0_191_strides_0, weight = encoder_layers_13_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_199_cast_fp16)[name = tensor("input0_191_cast_fp16")]; tensor x_225_split_num_splits_0 = const()[name = tensor("x_225_split_num_splits_0"), val = tensor(2)]; tensor x_225_split_axis_0 = const()[name = tensor("x_225_split_axis_0"), val = tensor(1)]; tensor x_225_split_cast_fp16_0, tensor x_225_split_cast_fp16_1 = split(axis = x_225_split_axis_0, num_splits = x_225_split_num_splits_0, x = input0_191_cast_fp16)[name = tensor("x_225_split_cast_fp16")]; tensor x_225_split_1_sigmoid_cast_fp16 = sigmoid(x = x_225_split_cast_fp16_1)[name = tensor("x_225_split_1_sigmoid_cast_fp16")]; tensor x_225_cast_fp16 = mul(x = x_225_split_cast_fp16_0, y = x_225_split_1_sigmoid_cast_fp16)[name = tensor("x_225_cast_fp16")]; tensor input0_193_cast_fp16 = select(a = var_8_to_fp16, b = x_225_cast_fp16, cond = var_457)[name = tensor("input0_193_cast_fp16")]; tensor input0_195_pad_0 = const()[name = tensor("input0_195_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_195_mode_0 = const()[name = tensor("input0_195_mode_0"), val = tensor("constant")]; tensor const_38_to_fp16 = const()[name = tensor("const_38_to_fp16"), val = tensor(0x0p+0)]; tensor input0_195_cast_fp16 = pad(constant_val = const_38_to_fp16, mode = input0_195_mode_0, pad = input0_195_pad_0, x = input0_193_cast_fp16)[name = tensor("input0_195_cast_fp16")]; tensor input1_58_pad_type_0 = const()[name = tensor("input1_58_pad_type_0"), val = tensor("valid")]; tensor input1_58_groups_0 = const()[name = tensor("input1_58_groups_0"), val = tensor(1024)]; tensor input1_58_strides_0 = const()[name = tensor("input1_58_strides_0"), val = tensor([1])]; tensor input1_58_pad_0 = const()[name = tensor("input1_58_pad_0"), val = tensor([0, 0])]; tensor input1_58_dilations_0 = const()[name = tensor("input1_58_dilations_0"), val = tensor([1])]; tensor const_85_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179209792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179214464))), name = tensor("const_85_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_86_to_fp16 = const()[name = tensor("const_86_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179214592)))]; tensor input_201_cast_fp16 = conv(bias = const_86_to_fp16, dilations = input1_58_dilations_0, groups = input1_58_groups_0, pad = input1_58_pad_0, pad_type = input1_58_pad_type_0, strides = input1_58_strides_0, weight = const_85_to_fp16_palettized, x = input0_195_cast_fp16)[name = tensor("input_201_cast_fp16")]; tensor var_2591_cast_fp16 = silu(x = input_201_cast_fp16)[name = tensor("op_2591_cast_fp16")]; tensor x_227_pad_type_0 = const()[name = tensor("x_227_pad_type_0"), val = tensor("valid")]; tensor x_227_strides_0 = const()[name = tensor("x_227_strides_0"), val = tensor([1])]; tensor x_227_pad_0 = const()[name = tensor("x_227_pad_0"), val = tensor([0, 0])]; tensor x_227_dilations_0 = const()[name = tensor("x_227_dilations_0"), val = tensor([1])]; tensor x_227_groups_0 = const()[name = tensor("x_227_groups_0"), val = tensor(1)]; tensor encoder_layers_13_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179216704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179741056))), name = tensor("encoder_layers_13_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_227_cast_fp16 = conv(dilations = x_227_dilations_0, groups = x_227_groups_0, pad = x_227_pad_0, pad_type = x_227_pad_type_0, strides = x_227_strides_0, weight = encoder_layers_13_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2591_cast_fp16)[name = tensor("x_227_cast_fp16")]; tensor var_2598_perm_0 = const()[name = tensor("op_2598_perm_0"), val = tensor([0, 2, 1])]; tensor var_2598_cast_fp16 = transpose(perm = var_2598_perm_0, x = x_227_cast_fp16)[name = tensor("transpose_368")]; tensor input1_60_cast_fp16 = add(x = input0_189_cast_fp16, y = var_2598_cast_fp16)[name = tensor("input1_60_cast_fp16")]; tensor input0_197_axes_0 = const()[name = tensor("input0_197_axes_0"), val = tensor([-1])]; tensor encoder_layers_13_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_13_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179741184)))]; tensor encoder_layers_13_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_13_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179743296)))]; tensor input0_197_cast_fp16 = layer_norm(axes = input0_197_axes_0, beta = encoder_layers_13_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_13_norm_feed_forward2_weight_to_fp16, x = input1_60_cast_fp16)[name = tensor("input0_197_cast_fp16")]; tensor encoder_layers_13_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(179745408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181842624))), name = tensor("encoder_layers_13_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_125_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_13_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_197_cast_fp16)[name = tensor("linear_125_cast_fp16")]; tensor var_2609_cast_fp16 = silu(x = linear_125_cast_fp16)[name = tensor("op_2609_cast_fp16")]; tensor encoder_layers_13_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(181842752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183939968))), name = tensor("encoder_layers_13_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_126_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_13_feed_forward2_linear2_weight_to_fp16_palettized, x = var_2609_cast_fp16)[name = tensor("linear_126_cast_fp16")]; tensor var_2614_to_fp16 = const()[name = tensor("op_2614_to_fp16"), val = tensor(0x1p-1)]; tensor var_2615_cast_fp16 = mul(x = linear_126_cast_fp16, y = var_2614_to_fp16)[name = tensor("op_2615_cast_fp16")]; tensor input2_30_cast_fp16 = add(x = input1_60_cast_fp16, y = var_2615_cast_fp16)[name = tensor("input2_30_cast_fp16")]; tensor input0_199_axes_0 = const()[name = tensor("input0_199_axes_0"), val = tensor([-1])]; tensor encoder_layers_13_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_13_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183940096)))]; tensor encoder_layers_13_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_13_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183942208)))]; tensor input0_199_cast_fp16 = layer_norm(axes = input0_199_axes_0, beta = encoder_layers_13_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_13_norm_out_weight_to_fp16, x = input2_30_cast_fp16)[name = tensor("input0_199_cast_fp16")]; tensor input_205_axes_0 = const()[name = tensor("input_205_axes_0"), val = tensor([-1])]; tensor encoder_layers_14_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_14_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183944320)))]; tensor encoder_layers_14_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_14_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183946432)))]; tensor input_205_cast_fp16 = layer_norm(axes = input_205_axes_0, beta = encoder_layers_14_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_14_norm_feed_forward1_weight_to_fp16, x = input0_199_cast_fp16)[name = tensor("input_205_cast_fp16")]; tensor encoder_layers_14_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(183948544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186045760))), name = tensor("encoder_layers_14_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_127_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_14_feed_forward1_linear1_weight_to_fp16_palettized, x = input_205_cast_fp16)[name = tensor("linear_127_cast_fp16")]; tensor var_2638_cast_fp16 = silu(x = linear_127_cast_fp16)[name = tensor("op_2638_cast_fp16")]; tensor encoder_layers_14_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(186045888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188143104))), name = tensor("encoder_layers_14_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_128_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_feed_forward1_linear2_weight_to_fp16_palettized, x = var_2638_cast_fp16)[name = tensor("linear_128_cast_fp16")]; tensor var_2643_to_fp16 = const()[name = tensor("op_2643_to_fp16"), val = tensor(0x1p-1)]; tensor var_2644_cast_fp16 = mul(x = linear_128_cast_fp16, y = var_2643_to_fp16)[name = tensor("op_2644_cast_fp16")]; tensor input_209_cast_fp16 = add(x = input0_199_cast_fp16, y = var_2644_cast_fp16)[name = tensor("input_209_cast_fp16")]; tensor query_30_axes_0 = const()[name = tensor("query_30_axes_0"), val = tensor([-1])]; tensor encoder_layers_14_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_14_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188143232)))]; tensor encoder_layers_14_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_14_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188145344)))]; tensor query_30_cast_fp16 = layer_norm(axes = query_30_axes_0, beta = encoder_layers_14_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_14_norm_self_att_weight_to_fp16, x = input_209_cast_fp16)[name = tensor("query_30_cast_fp16")]; tensor var_2657_shape_cast_fp16 = shape(x = query_30_cast_fp16)[name = tensor("op_2657_shape_cast_fp16")]; tensor gather_164_axis_0 = const()[name = tensor("gather_164_axis_0"), val = tensor(0)]; tensor gather_164_batch_dims_0 = const()[name = tensor("gather_164_batch_dims_0"), val = tensor(0)]; tensor gather_164_validate_indices_0 = const()[name = tensor("gather_164_validate_indices_0"), val = tensor(false)]; tensor var_2657_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2657_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_164_to_uint16 = const()[name = tensor("select_164_to_uint16"), val = tensor(0)]; tensor var_2657_shape_cast_fp16_to_uint16 = cast(dtype = var_2657_shape_cast_fp16_to_uint16_dtype_0, x = var_2657_shape_cast_fp16)[name = tensor("cast_99")]; tensor gather_164_cast_uint16 = gather(axis = gather_164_axis_0, batch_dims = gather_164_batch_dims_0, indices = select_164_to_uint16, validate_indices = gather_164_validate_indices_0, x = var_2657_shape_cast_fp16_to_uint16)[name = tensor("gather_164_cast_uint16")]; tensor gather_164_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_164_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_14_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188147456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188671808))), name = tensor("encoder_layers_14_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_129_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_self_attn_linear_q_weight_to_fp16_palettized, x = query_30_cast_fp16)[name = tensor("linear_129_cast_fp16")]; tensor concat_122_axis_0 = const()[name = tensor("concat_122_axis_0"), val = tensor(0)]; tensor concat_122_interleave_0 = const()[name = tensor("concat_122_interleave_0"), val = tensor(false)]; tensor gather_164_cast_uint16_to_int32 = cast(dtype = gather_164_cast_uint16_to_int32_dtype_0, x = gather_164_cast_uint16)[name = tensor("cast_98")]; tensor concat_122 = concat(axis = concat_122_axis_0, interleave = concat_122_interleave_0, values = (gather_164_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_122")]; tensor q_30_cast_fp16 = reshape(shape = concat_122, x = linear_129_cast_fp16)[name = tensor("q_30_cast_fp16")]; tensor encoder_layers_14_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(188671936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189196288))), name = tensor("encoder_layers_14_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_130_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_self_attn_linear_k_weight_to_fp16_palettized, x = query_30_cast_fp16)[name = tensor("linear_130_cast_fp16")]; tensor k_30_cast_fp16 = reshape(shape = concat_122, x = linear_130_cast_fp16)[name = tensor("k_30_cast_fp16")]; tensor encoder_layers_14_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189196416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189720768))), name = tensor("encoder_layers_14_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_131_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_self_attn_linear_v_weight_to_fp16_palettized, x = query_30_cast_fp16)[name = tensor("linear_131_cast_fp16")]; tensor v_30_cast_fp16 = reshape(shape = concat_122, x = linear_131_cast_fp16)[name = tensor("v_30_cast_fp16")]; tensor value_30_perm_0 = const()[name = tensor("value_30_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_14_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(189720896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190245248))), name = tensor("encoder_layers_14_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_132_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_132_cast_fp16")]; tensor var_2677 = const()[name = tensor("op_2677"), val = tensor([1, -1, 8, 128])]; tensor p_30_cast_fp16 = reshape(shape = var_2677, x = linear_132_cast_fp16)[name = tensor("p_30_cast_fp16")]; tensor encoder_layers_14_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_14_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190245376)))]; tensor var_2680_cast_fp16 = add(x = q_30_cast_fp16, y = encoder_layers_14_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2680_cast_fp16")]; tensor encoder_layers_14_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_14_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190247488)))]; tensor var_2682_cast_fp16 = add(x = q_30_cast_fp16, y = encoder_layers_14_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2682_cast_fp16")]; tensor x_235_transpose_x_0 = const()[name = tensor("x_235_transpose_x_0"), val = tensor(false)]; tensor x_235_transpose_y_0 = const()[name = tensor("x_235_transpose_y_0"), val = tensor(false)]; tensor transpose_248_perm_0 = const()[name = tensor("transpose_248_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_249_perm_0 = const()[name = tensor("transpose_249_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_249 = transpose(perm = transpose_249_perm_0, x = p_30_cast_fp16)[name = tensor("transpose_366")]; tensor transpose_248 = transpose(perm = transpose_248_perm_0, x = var_2682_cast_fp16)[name = tensor("transpose_367")]; tensor x_235_cast_fp16 = matmul(transpose_x = x_235_transpose_x_0, transpose_y = x_235_transpose_y_0, x = transpose_248, y = transpose_249)[name = tensor("x_235_cast_fp16")]; tensor var_2686_shape_cast_fp16 = shape(x = x_235_cast_fp16)[name = tensor("op_2686_shape_cast_fp16")]; tensor gather_166_axis_0 = const()[name = tensor("gather_166_axis_0"), val = tensor(0)]; tensor gather_166_batch_dims_0 = const()[name = tensor("gather_166_batch_dims_0"), val = tensor(0)]; tensor gather_166_validate_indices_0 = const()[name = tensor("gather_166_validate_indices_0"), val = tensor(false)]; tensor var_2686_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2686_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_166_to_uint16 = const()[name = tensor("select_166_to_uint16"), val = tensor(0)]; tensor var_2686_shape_cast_fp16_to_uint16 = cast(dtype = var_2686_shape_cast_fp16_to_uint16_dtype_0, x = var_2686_shape_cast_fp16)[name = tensor("cast_97")]; tensor gather_166_cast_uint16 = gather(axis = gather_166_axis_0, batch_dims = gather_166_batch_dims_0, indices = select_166_to_uint16, validate_indices = gather_166_validate_indices_0, x = var_2686_shape_cast_fp16_to_uint16)[name = tensor("gather_166_cast_uint16")]; tensor gather_166_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_166_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_167 = const()[name = tensor("gather_167"), val = tensor(8)]; tensor gather_168_axis_0 = const()[name = tensor("gather_168_axis_0"), val = tensor(0)]; tensor gather_168_batch_dims_0 = const()[name = tensor("gather_168_batch_dims_0"), val = tensor(0)]; tensor gather_168_validate_indices_0 = const()[name = tensor("gather_168_validate_indices_0"), val = tensor(false)]; tensor select_168_to_uint16 = const()[name = tensor("select_168_to_uint16"), val = tensor(2)]; tensor gather_168_cast_uint16 = gather(axis = gather_168_axis_0, batch_dims = gather_168_batch_dims_0, indices = select_168_to_uint16, validate_indices = gather_168_validate_indices_0, x = var_2686_shape_cast_fp16_to_uint16)[name = tensor("gather_168_cast_uint16")]; tensor gather_168_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_168_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_169_axis_0 = const()[name = tensor("gather_169_axis_0"), val = tensor(0)]; tensor gather_169_batch_dims_0 = const()[name = tensor("gather_169_batch_dims_0"), val = tensor(0)]; tensor gather_169_validate_indices_0 = const()[name = tensor("gather_169_validate_indices_0"), val = tensor(false)]; tensor select_169_to_uint16 = const()[name = tensor("select_169_to_uint16"), val = tensor(3)]; tensor gather_169_cast_uint16 = gather(axis = gather_169_axis_0, batch_dims = gather_169_batch_dims_0, indices = select_169_to_uint16, validate_indices = gather_169_validate_indices_0, x = var_2686_shape_cast_fp16_to_uint16)[name = tensor("gather_169_cast_uint16")]; tensor gather_169_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_169_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_32_pad_0 = const()[name = tensor("x0_32_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_32_mode_0 = const()[name = tensor("x0_32_mode_0"), val = tensor("constant")]; tensor const_39_to_fp16 = const()[name = tensor("const_39_to_fp16"), val = tensor(0x0p+0)]; tensor x0_32_cast_fp16 = pad(constant_val = const_39_to_fp16, mode = x0_32_mode_0, pad = x0_32_pad_0, x = x_235_cast_fp16)[name = tensor("x0_32_cast_fp16")]; tensor concat_125_axis_0 = const()[name = tensor("concat_125_axis_0"), val = tensor(0)]; tensor concat_125_interleave_0 = const()[name = tensor("concat_125_interleave_0"), val = tensor(false)]; tensor gather_166_cast_uint16_to_int32 = cast(dtype = gather_166_cast_uint16_to_int32_dtype_0, x = gather_166_cast_uint16)[name = tensor("cast_95")]; tensor gather_168_cast_uint16_to_int32 = cast(dtype = gather_168_cast_uint16_to_int32_dtype_0, x = gather_168_cast_uint16)[name = tensor("cast_96")]; tensor concat_125 = concat(axis = concat_125_axis_0, interleave = concat_125_interleave_0, values = (gather_166_cast_uint16_to_int32, gather_167, var_21, gather_168_cast_uint16_to_int32))[name = tensor("concat_125")]; tensor x1_30_cast_fp16 = reshape(shape = concat_125, x = x0_32_cast_fp16)[name = tensor("x1_30_cast_fp16")]; tensor var_2696_begin_0 = const()[name = tensor("op_2696_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2696_end_0 = const()[name = tensor("op_2696_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_2696_end_mask_0 = const()[name = tensor("op_2696_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2696_cast_fp16 = slice_by_index(begin = var_2696_begin_0, end = var_2696_end_0, end_mask = var_2696_end_mask_0, x = x1_30_cast_fp16)[name = tensor("op_2696_cast_fp16")]; tensor concat_126_axis_0 = const()[name = tensor("concat_126_axis_0"), val = tensor(0)]; tensor concat_126_interleave_0 = const()[name = tensor("concat_126_interleave_0"), val = tensor(false)]; tensor gather_169_cast_uint16_to_int32 = cast(dtype = gather_169_cast_uint16_to_int32_dtype_0, x = gather_169_cast_uint16)[name = tensor("cast_94")]; tensor concat_126 = concat(axis = concat_126_axis_0, interleave = concat_126_interleave_0, values = (gather_166_cast_uint16_to_int32, gather_167, gather_168_cast_uint16_to_int32, gather_169_cast_uint16_to_int32))[name = tensor("concat_126")]; tensor matrix_bd_30_cast_fp16 = reshape(shape = concat_126, x = var_2696_cast_fp16)[name = tensor("matrix_bd_30_cast_fp16")]; tensor matrix_ac_30_transpose_x_0 = const()[name = tensor("matrix_ac_30_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_30_transpose_y_0 = const()[name = tensor("matrix_ac_30_transpose_y_0"), val = tensor(false)]; tensor transpose_250_perm_0 = const()[name = tensor("transpose_250_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_251_perm_0 = const()[name = tensor("transpose_251_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_251 = transpose(perm = transpose_251_perm_0, x = k_30_cast_fp16)[name = tensor("transpose_364")]; tensor transpose_250 = transpose(perm = transpose_250_perm_0, x = var_2680_cast_fp16)[name = tensor("transpose_365")]; tensor matrix_ac_30_cast_fp16 = matmul(transpose_x = matrix_ac_30_transpose_x_0, transpose_y = matrix_ac_30_transpose_y_0, x = transpose_250, y = transpose_251)[name = tensor("matrix_ac_30_cast_fp16")]; tensor var_2701_shape_cast_fp16 = shape(x = matrix_ac_30_cast_fp16)[name = tensor("op_2701_shape_cast_fp16")]; tensor gather_170_axis_0 = const()[name = tensor("gather_170_axis_0"), val = tensor(0)]; tensor gather_170_batch_dims_0 = const()[name = tensor("gather_170_batch_dims_0"), val = tensor(0)]; tensor gather_170_validate_indices_0 = const()[name = tensor("gather_170_validate_indices_0"), val = tensor(false)]; tensor var_2701_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2701_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_170_to_uint16 = const()[name = tensor("select_170_to_uint16"), val = tensor(3)]; tensor var_2701_shape_cast_fp16_to_uint16 = cast(dtype = var_2701_shape_cast_fp16_to_uint16_dtype_0, x = var_2701_shape_cast_fp16)[name = tensor("cast_93")]; tensor gather_170_cast_uint16 = gather(axis = gather_170_axis_0, batch_dims = gather_170_batch_dims_0, indices = select_170_to_uint16, validate_indices = gather_170_validate_indices_0, x = var_2701_shape_cast_fp16_to_uint16)[name = tensor("gather_170_cast_uint16")]; tensor gather_170_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_170_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_127_values0_0 = const()[name = tensor("concat_127_values0_0"), val = tensor(0)]; tensor concat_127_values1_0 = const()[name = tensor("concat_127_values1_0"), val = tensor(8)]; tensor concat_127_values2_0 = const()[name = tensor("concat_127_values2_0"), val = tensor(0)]; tensor concat_127_axis_0 = const()[name = tensor("concat_127_axis_0"), val = tensor(0)]; tensor concat_127_interleave_0 = const()[name = tensor("concat_127_interleave_0"), val = tensor(false)]; tensor gather_170_cast_uint16_to_int32 = cast(dtype = gather_170_cast_uint16_to_int32_dtype_0, x = gather_170_cast_uint16)[name = tensor("cast_92")]; tensor concat_127 = concat(axis = concat_127_axis_0, interleave = concat_127_interleave_0, values = (concat_127_values0_0, concat_127_values1_0, concat_127_values2_0, gather_170_cast_uint16_to_int32))[name = tensor("concat_127")]; tensor matrix_bd0_30_begin_0 = const()[name = tensor("matrix_bd0_30_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_30_end_mask_0 = const()[name = tensor("matrix_bd0_30_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_30_cast_fp16 = slice_by_index(begin = matrix_bd0_30_begin_0, end = concat_127, end_mask = matrix_bd0_30_end_mask_0, x = matrix_bd_30_cast_fp16)[name = tensor("matrix_bd0_30_cast_fp16")]; tensor var_2706_cast_fp16 = add(x = matrix_ac_30_cast_fp16, y = matrix_bd0_30_cast_fp16)[name = tensor("op_2706_cast_fp16")]; tensor _inversed_scores_30_y_0_to_fp16 = const()[name = tensor("_inversed_scores_30_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_30_cast_fp16 = mul(x = var_2706_cast_fp16, y = _inversed_scores_30_y_0_to_fp16)[name = tensor("_inversed_scores_30_cast_fp16")]; tensor value_30_cast_fp16 = transpose(perm = value_30_perm_0, x = v_30_cast_fp16)[name = tensor("transpose_363")]; tensor var_2709_shape_cast_fp16 = shape(x = value_30_cast_fp16)[name = tensor("op_2709_shape_cast_fp16")]; tensor gather_171_axis_0 = const()[name = tensor("gather_171_axis_0"), val = tensor(0)]; tensor gather_171_batch_dims_0 = const()[name = tensor("gather_171_batch_dims_0"), val = tensor(0)]; tensor gather_171_validate_indices_0 = const()[name = tensor("gather_171_validate_indices_0"), val = tensor(false)]; tensor var_2709_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2709_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_171_to_uint16 = const()[name = tensor("select_171_to_uint16"), val = tensor(0)]; tensor var_2709_shape_cast_fp16_to_uint16 = cast(dtype = var_2709_shape_cast_fp16_to_uint16_dtype_0, x = var_2709_shape_cast_fp16)[name = tensor("cast_91")]; tensor gather_171_cast_uint16 = gather(axis = gather_171_axis_0, batch_dims = gather_171_batch_dims_0, indices = select_171_to_uint16, validate_indices = gather_171_validate_indices_0, x = var_2709_shape_cast_fp16_to_uint16)[name = tensor("gather_171_cast_uint16")]; tensor gather_171_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_171_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_30_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_30_cast_fp16, cond = mask0_4)[name = tensor("scores0_30_cast_fp16")]; tensor var_2712_cast_fp16 = softmax(axis = var_21, x = scores0_30_cast_fp16)[name = tensor("op_2712_cast_fp16")]; tensor input_211_cast_fp16 = select(a = var_8_to_fp16, b = var_2712_cast_fp16, cond = mask0_4)[name = tensor("input_211_cast_fp16")]; tensor x2_30_transpose_x_0 = const()[name = tensor("x2_30_transpose_x_0"), val = tensor(false)]; tensor x2_30_transpose_y_0 = const()[name = tensor("x2_30_transpose_y_0"), val = tensor(false)]; tensor x2_30_cast_fp16 = matmul(transpose_x = x2_30_transpose_x_0, transpose_y = x2_30_transpose_y_0, x = input_211_cast_fp16, y = value_30_cast_fp16)[name = tensor("x2_30_cast_fp16")]; tensor var_2716_perm_0 = const()[name = tensor("op_2716_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_128_axis_0 = const()[name = tensor("concat_128_axis_0"), val = tensor(0)]; tensor concat_128_interleave_0 = const()[name = tensor("concat_128_interleave_0"), val = tensor(false)]; tensor gather_171_cast_uint16_to_int32 = cast(dtype = gather_171_cast_uint16_to_int32_dtype_0, x = gather_171_cast_uint16)[name = tensor("cast_90")]; tensor concat_128 = concat(axis = concat_128_axis_0, interleave = concat_128_interleave_0, values = (gather_171_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_128")]; tensor var_2716_cast_fp16 = transpose(perm = var_2716_perm_0, x = x2_30_cast_fp16)[name = tensor("transpose_362")]; tensor input0_201_cast_fp16 = reshape(shape = concat_128, x = var_2716_cast_fp16)[name = tensor("input0_201_cast_fp16")]; tensor encoder_layers_14_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190249600))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190773952))), name = tensor("encoder_layers_14_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_133_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_self_attn_linear_out_weight_to_fp16_palettized, x = input0_201_cast_fp16)[name = tensor("linear_133_cast_fp16")]; tensor input0_203_cast_fp16 = add(x = input_209_cast_fp16, y = linear_133_cast_fp16)[name = tensor("input0_203_cast_fp16")]; tensor x_239_axes_0 = const()[name = tensor("x_239_axes_0"), val = tensor([-1])]; tensor encoder_layers_14_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_14_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190774080)))]; tensor encoder_layers_14_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_14_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190776192)))]; tensor x_239_cast_fp16 = layer_norm(axes = x_239_axes_0, beta = encoder_layers_14_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_14_norm_conv_weight_to_fp16, x = input0_203_cast_fp16)[name = tensor("x_239_cast_fp16")]; tensor input_213_perm_0 = const()[name = tensor("input_213_perm_0"), val = tensor([0, 2, 1])]; tensor input0_205_pad_type_0 = const()[name = tensor("input0_205_pad_type_0"), val = tensor("valid")]; tensor input0_205_strides_0 = const()[name = tensor("input0_205_strides_0"), val = tensor([1])]; tensor input0_205_pad_0 = const()[name = tensor("input0_205_pad_0"), val = tensor([0, 0])]; tensor input0_205_dilations_0 = const()[name = tensor("input0_205_dilations_0"), val = tensor([1])]; tensor input0_205_groups_0 = const()[name = tensor("input0_205_groups_0"), val = tensor(1)]; tensor encoder_layers_14_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(190778304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191826944))), name = tensor("encoder_layers_14_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_213_cast_fp16 = transpose(perm = input_213_perm_0, x = x_239_cast_fp16)[name = tensor("transpose_361")]; tensor input0_205_cast_fp16 = conv(dilations = input0_205_dilations_0, groups = input0_205_groups_0, pad = input0_205_pad_0, pad_type = input0_205_pad_type_0, strides = input0_205_strides_0, weight = encoder_layers_14_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_213_cast_fp16)[name = tensor("input0_205_cast_fp16")]; tensor x_241_split_num_splits_0 = const()[name = tensor("x_241_split_num_splits_0"), val = tensor(2)]; tensor x_241_split_axis_0 = const()[name = tensor("x_241_split_axis_0"), val = tensor(1)]; tensor x_241_split_cast_fp16_0, tensor x_241_split_cast_fp16_1 = split(axis = x_241_split_axis_0, num_splits = x_241_split_num_splits_0, x = input0_205_cast_fp16)[name = tensor("x_241_split_cast_fp16")]; tensor x_241_split_1_sigmoid_cast_fp16 = sigmoid(x = x_241_split_cast_fp16_1)[name = tensor("x_241_split_1_sigmoid_cast_fp16")]; tensor x_241_cast_fp16 = mul(x = x_241_split_cast_fp16_0, y = x_241_split_1_sigmoid_cast_fp16)[name = tensor("x_241_cast_fp16")]; tensor input0_207_cast_fp16 = select(a = var_8_to_fp16, b = x_241_cast_fp16, cond = var_457)[name = tensor("input0_207_cast_fp16")]; tensor input0_209_pad_0 = const()[name = tensor("input0_209_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_209_mode_0 = const()[name = tensor("input0_209_mode_0"), val = tensor("constant")]; tensor const_40_to_fp16 = const()[name = tensor("const_40_to_fp16"), val = tensor(0x0p+0)]; tensor input0_209_cast_fp16 = pad(constant_val = const_40_to_fp16, mode = input0_209_mode_0, pad = input0_209_pad_0, x = input0_207_cast_fp16)[name = tensor("input0_209_cast_fp16")]; tensor input1_62_pad_type_0 = const()[name = tensor("input1_62_pad_type_0"), val = tensor("valid")]; tensor input1_62_groups_0 = const()[name = tensor("input1_62_groups_0"), val = tensor(1024)]; tensor input1_62_strides_0 = const()[name = tensor("input1_62_strides_0"), val = tensor([1])]; tensor input1_62_pad_0 = const()[name = tensor("input1_62_pad_0"), val = tensor([0, 0])]; tensor input1_62_dilations_0 = const()[name = tensor("input1_62_dilations_0"), val = tensor([1])]; tensor const_87_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191827072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191831744))), name = tensor("const_87_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_88_to_fp16 = const()[name = tensor("const_88_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191831872)))]; tensor input_215_cast_fp16 = conv(bias = const_88_to_fp16, dilations = input1_62_dilations_0, groups = input1_62_groups_0, pad = input1_62_pad_0, pad_type = input1_62_pad_type_0, strides = input1_62_strides_0, weight = const_87_to_fp16_palettized, x = input0_209_cast_fp16)[name = tensor("input_215_cast_fp16")]; tensor var_2754_cast_fp16 = silu(x = input_215_cast_fp16)[name = tensor("op_2754_cast_fp16")]; tensor x_243_pad_type_0 = const()[name = tensor("x_243_pad_type_0"), val = tensor("valid")]; tensor x_243_strides_0 = const()[name = tensor("x_243_strides_0"), val = tensor([1])]; tensor x_243_pad_0 = const()[name = tensor("x_243_pad_0"), val = tensor([0, 0])]; tensor x_243_dilations_0 = const()[name = tensor("x_243_dilations_0"), val = tensor([1])]; tensor x_243_groups_0 = const()[name = tensor("x_243_groups_0"), val = tensor(1)]; tensor encoder_layers_14_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(191833984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192358336))), name = tensor("encoder_layers_14_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_243_cast_fp16 = conv(dilations = x_243_dilations_0, groups = x_243_groups_0, pad = x_243_pad_0, pad_type = x_243_pad_type_0, strides = x_243_strides_0, weight = encoder_layers_14_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2754_cast_fp16)[name = tensor("x_243_cast_fp16")]; tensor var_2761_perm_0 = const()[name = tensor("op_2761_perm_0"), val = tensor([0, 2, 1])]; tensor var_2761_cast_fp16 = transpose(perm = var_2761_perm_0, x = x_243_cast_fp16)[name = tensor("transpose_360")]; tensor input1_64_cast_fp16 = add(x = input0_203_cast_fp16, y = var_2761_cast_fp16)[name = tensor("input1_64_cast_fp16")]; tensor input0_211_axes_0 = const()[name = tensor("input0_211_axes_0"), val = tensor([-1])]; tensor encoder_layers_14_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_14_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192358464)))]; tensor encoder_layers_14_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_14_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192360576)))]; tensor input0_211_cast_fp16 = layer_norm(axes = input0_211_axes_0, beta = encoder_layers_14_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_14_norm_feed_forward2_weight_to_fp16, x = input1_64_cast_fp16)[name = tensor("input0_211_cast_fp16")]; tensor encoder_layers_14_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(192362688))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194459904))), name = tensor("encoder_layers_14_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_134_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_14_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_211_cast_fp16)[name = tensor("linear_134_cast_fp16")]; tensor var_2772_cast_fp16 = silu(x = linear_134_cast_fp16)[name = tensor("op_2772_cast_fp16")]; tensor encoder_layers_14_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(194460032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196557248))), name = tensor("encoder_layers_14_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_135_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_14_feed_forward2_linear2_weight_to_fp16_palettized, x = var_2772_cast_fp16)[name = tensor("linear_135_cast_fp16")]; tensor var_2777_to_fp16 = const()[name = tensor("op_2777_to_fp16"), val = tensor(0x1p-1)]; tensor var_2778_cast_fp16 = mul(x = linear_135_cast_fp16, y = var_2777_to_fp16)[name = tensor("op_2778_cast_fp16")]; tensor input2_32_cast_fp16 = add(x = input1_64_cast_fp16, y = var_2778_cast_fp16)[name = tensor("input2_32_cast_fp16")]; tensor input0_213_axes_0 = const()[name = tensor("input0_213_axes_0"), val = tensor([-1])]; tensor encoder_layers_14_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_14_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196557376)))]; tensor encoder_layers_14_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_14_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196559488)))]; tensor input0_213_cast_fp16 = layer_norm(axes = input0_213_axes_0, beta = encoder_layers_14_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_14_norm_out_weight_to_fp16, x = input2_32_cast_fp16)[name = tensor("input0_213_cast_fp16")]; tensor input_219_axes_0 = const()[name = tensor("input_219_axes_0"), val = tensor([-1])]; tensor encoder_layers_15_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_15_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196561600)))]; tensor encoder_layers_15_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_15_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196563712)))]; tensor input_219_cast_fp16 = layer_norm(axes = input_219_axes_0, beta = encoder_layers_15_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_15_norm_feed_forward1_weight_to_fp16, x = input0_213_cast_fp16)[name = tensor("input_219_cast_fp16")]; tensor encoder_layers_15_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(196565824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198663040))), name = tensor("encoder_layers_15_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_136_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_15_feed_forward1_linear1_weight_to_fp16_palettized, x = input_219_cast_fp16)[name = tensor("linear_136_cast_fp16")]; tensor var_2801_cast_fp16 = silu(x = linear_136_cast_fp16)[name = tensor("op_2801_cast_fp16")]; tensor encoder_layers_15_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(198663168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200760384))), name = tensor("encoder_layers_15_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_137_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_feed_forward1_linear2_weight_to_fp16_palettized, x = var_2801_cast_fp16)[name = tensor("linear_137_cast_fp16")]; tensor var_2806_to_fp16 = const()[name = tensor("op_2806_to_fp16"), val = tensor(0x1p-1)]; tensor var_2807_cast_fp16 = mul(x = linear_137_cast_fp16, y = var_2806_to_fp16)[name = tensor("op_2807_cast_fp16")]; tensor input_223_cast_fp16 = add(x = input0_213_cast_fp16, y = var_2807_cast_fp16)[name = tensor("input_223_cast_fp16")]; tensor query_32_axes_0 = const()[name = tensor("query_32_axes_0"), val = tensor([-1])]; tensor encoder_layers_15_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_15_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200760512)))]; tensor encoder_layers_15_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_15_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200762624)))]; tensor query_32_cast_fp16 = layer_norm(axes = query_32_axes_0, beta = encoder_layers_15_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_15_norm_self_att_weight_to_fp16, x = input_223_cast_fp16)[name = tensor("query_32_cast_fp16")]; tensor var_2820_shape_cast_fp16 = shape(x = query_32_cast_fp16)[name = tensor("op_2820_shape_cast_fp16")]; tensor gather_172_axis_0 = const()[name = tensor("gather_172_axis_0"), val = tensor(0)]; tensor gather_172_batch_dims_0 = const()[name = tensor("gather_172_batch_dims_0"), val = tensor(0)]; tensor gather_172_validate_indices_0 = const()[name = tensor("gather_172_validate_indices_0"), val = tensor(false)]; tensor var_2820_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2820_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_172_to_uint16 = const()[name = tensor("select_172_to_uint16"), val = tensor(0)]; tensor var_2820_shape_cast_fp16_to_uint16 = cast(dtype = var_2820_shape_cast_fp16_to_uint16_dtype_0, x = var_2820_shape_cast_fp16)[name = tensor("cast_89")]; tensor gather_172_cast_uint16 = gather(axis = gather_172_axis_0, batch_dims = gather_172_batch_dims_0, indices = select_172_to_uint16, validate_indices = gather_172_validate_indices_0, x = var_2820_shape_cast_fp16_to_uint16)[name = tensor("gather_172_cast_uint16")]; tensor gather_172_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_172_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_15_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(200764736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201289088))), name = tensor("encoder_layers_15_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_138_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_self_attn_linear_q_weight_to_fp16_palettized, x = query_32_cast_fp16)[name = tensor("linear_138_cast_fp16")]; tensor concat_129_axis_0 = const()[name = tensor("concat_129_axis_0"), val = tensor(0)]; tensor concat_129_interleave_0 = const()[name = tensor("concat_129_interleave_0"), val = tensor(false)]; tensor gather_172_cast_uint16_to_int32 = cast(dtype = gather_172_cast_uint16_to_int32_dtype_0, x = gather_172_cast_uint16)[name = tensor("cast_88")]; tensor concat_129 = concat(axis = concat_129_axis_0, interleave = concat_129_interleave_0, values = (gather_172_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_129")]; tensor q_32_cast_fp16 = reshape(shape = concat_129, x = linear_138_cast_fp16)[name = tensor("q_32_cast_fp16")]; tensor encoder_layers_15_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201289216))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201813568))), name = tensor("encoder_layers_15_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_139_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_self_attn_linear_k_weight_to_fp16_palettized, x = query_32_cast_fp16)[name = tensor("linear_139_cast_fp16")]; tensor k_32_cast_fp16 = reshape(shape = concat_129, x = linear_139_cast_fp16)[name = tensor("k_32_cast_fp16")]; tensor encoder_layers_15_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(201813696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202338048))), name = tensor("encoder_layers_15_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_140_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_self_attn_linear_v_weight_to_fp16_palettized, x = query_32_cast_fp16)[name = tensor("linear_140_cast_fp16")]; tensor v_32_cast_fp16 = reshape(shape = concat_129, x = linear_140_cast_fp16)[name = tensor("v_32_cast_fp16")]; tensor value_32_perm_0 = const()[name = tensor("value_32_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_15_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202338176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202862528))), name = tensor("encoder_layers_15_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_141_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_141_cast_fp16")]; tensor var_2840 = const()[name = tensor("op_2840"), val = tensor([1, -1, 8, 128])]; tensor p_32_cast_fp16 = reshape(shape = var_2840, x = linear_141_cast_fp16)[name = tensor("p_32_cast_fp16")]; tensor encoder_layers_15_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_15_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202862656)))]; tensor var_2843_cast_fp16 = add(x = q_32_cast_fp16, y = encoder_layers_15_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2843_cast_fp16")]; tensor encoder_layers_15_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_15_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202864768)))]; tensor var_2845_cast_fp16 = add(x = q_32_cast_fp16, y = encoder_layers_15_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2845_cast_fp16")]; tensor x_251_transpose_x_0 = const()[name = tensor("x_251_transpose_x_0"), val = tensor(false)]; tensor x_251_transpose_y_0 = const()[name = tensor("x_251_transpose_y_0"), val = tensor(false)]; tensor transpose_252_perm_0 = const()[name = tensor("transpose_252_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_253_perm_0 = const()[name = tensor("transpose_253_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_253 = transpose(perm = transpose_253_perm_0, x = p_32_cast_fp16)[name = tensor("transpose_358")]; tensor transpose_252 = transpose(perm = transpose_252_perm_0, x = var_2845_cast_fp16)[name = tensor("transpose_359")]; tensor x_251_cast_fp16 = matmul(transpose_x = x_251_transpose_x_0, transpose_y = x_251_transpose_y_0, x = transpose_252, y = transpose_253)[name = tensor("x_251_cast_fp16")]; tensor var_2849_shape_cast_fp16 = shape(x = x_251_cast_fp16)[name = tensor("op_2849_shape_cast_fp16")]; tensor gather_174_axis_0 = const()[name = tensor("gather_174_axis_0"), val = tensor(0)]; tensor gather_174_batch_dims_0 = const()[name = tensor("gather_174_batch_dims_0"), val = tensor(0)]; tensor gather_174_validate_indices_0 = const()[name = tensor("gather_174_validate_indices_0"), val = tensor(false)]; tensor var_2849_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2849_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_174_to_uint16 = const()[name = tensor("select_174_to_uint16"), val = tensor(0)]; tensor var_2849_shape_cast_fp16_to_uint16 = cast(dtype = var_2849_shape_cast_fp16_to_uint16_dtype_0, x = var_2849_shape_cast_fp16)[name = tensor("cast_87")]; tensor gather_174_cast_uint16 = gather(axis = gather_174_axis_0, batch_dims = gather_174_batch_dims_0, indices = select_174_to_uint16, validate_indices = gather_174_validate_indices_0, x = var_2849_shape_cast_fp16_to_uint16)[name = tensor("gather_174_cast_uint16")]; tensor gather_174_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_174_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_175 = const()[name = tensor("gather_175"), val = tensor(8)]; tensor gather_176_axis_0 = const()[name = tensor("gather_176_axis_0"), val = tensor(0)]; tensor gather_176_batch_dims_0 = const()[name = tensor("gather_176_batch_dims_0"), val = tensor(0)]; tensor gather_176_validate_indices_0 = const()[name = tensor("gather_176_validate_indices_0"), val = tensor(false)]; tensor select_176_to_uint16 = const()[name = tensor("select_176_to_uint16"), val = tensor(2)]; tensor gather_176_cast_uint16 = gather(axis = gather_176_axis_0, batch_dims = gather_176_batch_dims_0, indices = select_176_to_uint16, validate_indices = gather_176_validate_indices_0, x = var_2849_shape_cast_fp16_to_uint16)[name = tensor("gather_176_cast_uint16")]; tensor gather_176_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_176_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_177_axis_0 = const()[name = tensor("gather_177_axis_0"), val = tensor(0)]; tensor gather_177_batch_dims_0 = const()[name = tensor("gather_177_batch_dims_0"), val = tensor(0)]; tensor gather_177_validate_indices_0 = const()[name = tensor("gather_177_validate_indices_0"), val = tensor(false)]; tensor select_177_to_uint16 = const()[name = tensor("select_177_to_uint16"), val = tensor(3)]; tensor gather_177_cast_uint16 = gather(axis = gather_177_axis_0, batch_dims = gather_177_batch_dims_0, indices = select_177_to_uint16, validate_indices = gather_177_validate_indices_0, x = var_2849_shape_cast_fp16_to_uint16)[name = tensor("gather_177_cast_uint16")]; tensor gather_177_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_177_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_34_pad_0 = const()[name = tensor("x0_34_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_34_mode_0 = const()[name = tensor("x0_34_mode_0"), val = tensor("constant")]; tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(0x0p+0)]; tensor x0_34_cast_fp16 = pad(constant_val = const_41_to_fp16, mode = x0_34_mode_0, pad = x0_34_pad_0, x = x_251_cast_fp16)[name = tensor("x0_34_cast_fp16")]; tensor concat_132_axis_0 = const()[name = tensor("concat_132_axis_0"), val = tensor(0)]; tensor concat_132_interleave_0 = const()[name = tensor("concat_132_interleave_0"), val = tensor(false)]; tensor gather_174_cast_uint16_to_int32 = cast(dtype = gather_174_cast_uint16_to_int32_dtype_0, x = gather_174_cast_uint16)[name = tensor("cast_85")]; tensor gather_176_cast_uint16_to_int32 = cast(dtype = gather_176_cast_uint16_to_int32_dtype_0, x = gather_176_cast_uint16)[name = tensor("cast_86")]; tensor concat_132 = concat(axis = concat_132_axis_0, interleave = concat_132_interleave_0, values = (gather_174_cast_uint16_to_int32, gather_175, var_21, gather_176_cast_uint16_to_int32))[name = tensor("concat_132")]; tensor x1_32_cast_fp16 = reshape(shape = concat_132, x = x0_34_cast_fp16)[name = tensor("x1_32_cast_fp16")]; tensor var_2859_begin_0 = const()[name = tensor("op_2859_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2859_end_0 = const()[name = tensor("op_2859_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_2859_end_mask_0 = const()[name = tensor("op_2859_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2859_cast_fp16 = slice_by_index(begin = var_2859_begin_0, end = var_2859_end_0, end_mask = var_2859_end_mask_0, x = x1_32_cast_fp16)[name = tensor("op_2859_cast_fp16")]; tensor concat_133_axis_0 = const()[name = tensor("concat_133_axis_0"), val = tensor(0)]; tensor concat_133_interleave_0 = const()[name = tensor("concat_133_interleave_0"), val = tensor(false)]; tensor gather_177_cast_uint16_to_int32 = cast(dtype = gather_177_cast_uint16_to_int32_dtype_0, x = gather_177_cast_uint16)[name = tensor("cast_84")]; tensor concat_133 = concat(axis = concat_133_axis_0, interleave = concat_133_interleave_0, values = (gather_174_cast_uint16_to_int32, gather_175, gather_176_cast_uint16_to_int32, gather_177_cast_uint16_to_int32))[name = tensor("concat_133")]; tensor matrix_bd_32_cast_fp16 = reshape(shape = concat_133, x = var_2859_cast_fp16)[name = tensor("matrix_bd_32_cast_fp16")]; tensor matrix_ac_32_transpose_x_0 = const()[name = tensor("matrix_ac_32_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_32_transpose_y_0 = const()[name = tensor("matrix_ac_32_transpose_y_0"), val = tensor(false)]; tensor transpose_254_perm_0 = const()[name = tensor("transpose_254_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_255_perm_0 = const()[name = tensor("transpose_255_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_255 = transpose(perm = transpose_255_perm_0, x = k_32_cast_fp16)[name = tensor("transpose_356")]; tensor transpose_254 = transpose(perm = transpose_254_perm_0, x = var_2843_cast_fp16)[name = tensor("transpose_357")]; tensor matrix_ac_32_cast_fp16 = matmul(transpose_x = matrix_ac_32_transpose_x_0, transpose_y = matrix_ac_32_transpose_y_0, x = transpose_254, y = transpose_255)[name = tensor("matrix_ac_32_cast_fp16")]; tensor var_2864_shape_cast_fp16 = shape(x = matrix_ac_32_cast_fp16)[name = tensor("op_2864_shape_cast_fp16")]; tensor gather_178_axis_0 = const()[name = tensor("gather_178_axis_0"), val = tensor(0)]; tensor gather_178_batch_dims_0 = const()[name = tensor("gather_178_batch_dims_0"), val = tensor(0)]; tensor gather_178_validate_indices_0 = const()[name = tensor("gather_178_validate_indices_0"), val = tensor(false)]; tensor var_2864_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2864_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_178_to_uint16 = const()[name = tensor("select_178_to_uint16"), val = tensor(3)]; tensor var_2864_shape_cast_fp16_to_uint16 = cast(dtype = var_2864_shape_cast_fp16_to_uint16_dtype_0, x = var_2864_shape_cast_fp16)[name = tensor("cast_83")]; tensor gather_178_cast_uint16 = gather(axis = gather_178_axis_0, batch_dims = gather_178_batch_dims_0, indices = select_178_to_uint16, validate_indices = gather_178_validate_indices_0, x = var_2864_shape_cast_fp16_to_uint16)[name = tensor("gather_178_cast_uint16")]; tensor gather_178_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_178_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_134_values0_0 = const()[name = tensor("concat_134_values0_0"), val = tensor(0)]; tensor concat_134_values1_0 = const()[name = tensor("concat_134_values1_0"), val = tensor(8)]; tensor concat_134_values2_0 = const()[name = tensor("concat_134_values2_0"), val = tensor(0)]; tensor concat_134_axis_0 = const()[name = tensor("concat_134_axis_0"), val = tensor(0)]; tensor concat_134_interleave_0 = const()[name = tensor("concat_134_interleave_0"), val = tensor(false)]; tensor gather_178_cast_uint16_to_int32 = cast(dtype = gather_178_cast_uint16_to_int32_dtype_0, x = gather_178_cast_uint16)[name = tensor("cast_82")]; tensor concat_134 = concat(axis = concat_134_axis_0, interleave = concat_134_interleave_0, values = (concat_134_values0_0, concat_134_values1_0, concat_134_values2_0, gather_178_cast_uint16_to_int32))[name = tensor("concat_134")]; tensor matrix_bd0_32_begin_0 = const()[name = tensor("matrix_bd0_32_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_32_end_mask_0 = const()[name = tensor("matrix_bd0_32_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_32_cast_fp16 = slice_by_index(begin = matrix_bd0_32_begin_0, end = concat_134, end_mask = matrix_bd0_32_end_mask_0, x = matrix_bd_32_cast_fp16)[name = tensor("matrix_bd0_32_cast_fp16")]; tensor var_2869_cast_fp16 = add(x = matrix_ac_32_cast_fp16, y = matrix_bd0_32_cast_fp16)[name = tensor("op_2869_cast_fp16")]; tensor _inversed_scores_32_y_0_to_fp16 = const()[name = tensor("_inversed_scores_32_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_32_cast_fp16 = mul(x = var_2869_cast_fp16, y = _inversed_scores_32_y_0_to_fp16)[name = tensor("_inversed_scores_32_cast_fp16")]; tensor value_32_cast_fp16 = transpose(perm = value_32_perm_0, x = v_32_cast_fp16)[name = tensor("transpose_355")]; tensor var_2872_shape_cast_fp16 = shape(x = value_32_cast_fp16)[name = tensor("op_2872_shape_cast_fp16")]; tensor gather_179_axis_0 = const()[name = tensor("gather_179_axis_0"), val = tensor(0)]; tensor gather_179_batch_dims_0 = const()[name = tensor("gather_179_batch_dims_0"), val = tensor(0)]; tensor gather_179_validate_indices_0 = const()[name = tensor("gather_179_validate_indices_0"), val = tensor(false)]; tensor var_2872_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2872_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_179_to_uint16 = const()[name = tensor("select_179_to_uint16"), val = tensor(0)]; tensor var_2872_shape_cast_fp16_to_uint16 = cast(dtype = var_2872_shape_cast_fp16_to_uint16_dtype_0, x = var_2872_shape_cast_fp16)[name = tensor("cast_81")]; tensor gather_179_cast_uint16 = gather(axis = gather_179_axis_0, batch_dims = gather_179_batch_dims_0, indices = select_179_to_uint16, validate_indices = gather_179_validate_indices_0, x = var_2872_shape_cast_fp16_to_uint16)[name = tensor("gather_179_cast_uint16")]; tensor gather_179_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_179_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_32_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_32_cast_fp16, cond = mask0_4)[name = tensor("scores0_32_cast_fp16")]; tensor var_2875_cast_fp16 = softmax(axis = var_21, x = scores0_32_cast_fp16)[name = tensor("op_2875_cast_fp16")]; tensor input_225_cast_fp16 = select(a = var_8_to_fp16, b = var_2875_cast_fp16, cond = mask0_4)[name = tensor("input_225_cast_fp16")]; tensor x2_32_transpose_x_0 = const()[name = tensor("x2_32_transpose_x_0"), val = tensor(false)]; tensor x2_32_transpose_y_0 = const()[name = tensor("x2_32_transpose_y_0"), val = tensor(false)]; tensor x2_32_cast_fp16 = matmul(transpose_x = x2_32_transpose_x_0, transpose_y = x2_32_transpose_y_0, x = input_225_cast_fp16, y = value_32_cast_fp16)[name = tensor("x2_32_cast_fp16")]; tensor var_2879_perm_0 = const()[name = tensor("op_2879_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_135_axis_0 = const()[name = tensor("concat_135_axis_0"), val = tensor(0)]; tensor concat_135_interleave_0 = const()[name = tensor("concat_135_interleave_0"), val = tensor(false)]; tensor gather_179_cast_uint16_to_int32 = cast(dtype = gather_179_cast_uint16_to_int32_dtype_0, x = gather_179_cast_uint16)[name = tensor("cast_80")]; tensor concat_135 = concat(axis = concat_135_axis_0, interleave = concat_135_interleave_0, values = (gather_179_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_135")]; tensor var_2879_cast_fp16 = transpose(perm = var_2879_perm_0, x = x2_32_cast_fp16)[name = tensor("transpose_354")]; tensor input0_215_cast_fp16 = reshape(shape = concat_135, x = var_2879_cast_fp16)[name = tensor("input0_215_cast_fp16")]; tensor encoder_layers_15_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(202866880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203391232))), name = tensor("encoder_layers_15_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_142_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_self_attn_linear_out_weight_to_fp16_palettized, x = input0_215_cast_fp16)[name = tensor("linear_142_cast_fp16")]; tensor input0_217_cast_fp16 = add(x = input_223_cast_fp16, y = linear_142_cast_fp16)[name = tensor("input0_217_cast_fp16")]; tensor x_255_axes_0 = const()[name = tensor("x_255_axes_0"), val = tensor([-1])]; tensor encoder_layers_15_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_15_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203391360)))]; tensor encoder_layers_15_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_15_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203393472)))]; tensor x_255_cast_fp16 = layer_norm(axes = x_255_axes_0, beta = encoder_layers_15_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_15_norm_conv_weight_to_fp16, x = input0_217_cast_fp16)[name = tensor("x_255_cast_fp16")]; tensor input_227_perm_0 = const()[name = tensor("input_227_perm_0"), val = tensor([0, 2, 1])]; tensor input0_219_pad_type_0 = const()[name = tensor("input0_219_pad_type_0"), val = tensor("valid")]; tensor input0_219_strides_0 = const()[name = tensor("input0_219_strides_0"), val = tensor([1])]; tensor input0_219_pad_0 = const()[name = tensor("input0_219_pad_0"), val = tensor([0, 0])]; tensor input0_219_dilations_0 = const()[name = tensor("input0_219_dilations_0"), val = tensor([1])]; tensor input0_219_groups_0 = const()[name = tensor("input0_219_groups_0"), val = tensor(1)]; tensor encoder_layers_15_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(203395584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204444224))), name = tensor("encoder_layers_15_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_227_cast_fp16 = transpose(perm = input_227_perm_0, x = x_255_cast_fp16)[name = tensor("transpose_353")]; tensor input0_219_cast_fp16 = conv(dilations = input0_219_dilations_0, groups = input0_219_groups_0, pad = input0_219_pad_0, pad_type = input0_219_pad_type_0, strides = input0_219_strides_0, weight = encoder_layers_15_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_227_cast_fp16)[name = tensor("input0_219_cast_fp16")]; tensor x_257_split_num_splits_0 = const()[name = tensor("x_257_split_num_splits_0"), val = tensor(2)]; tensor x_257_split_axis_0 = const()[name = tensor("x_257_split_axis_0"), val = tensor(1)]; tensor x_257_split_cast_fp16_0, tensor x_257_split_cast_fp16_1 = split(axis = x_257_split_axis_0, num_splits = x_257_split_num_splits_0, x = input0_219_cast_fp16)[name = tensor("x_257_split_cast_fp16")]; tensor x_257_split_1_sigmoid_cast_fp16 = sigmoid(x = x_257_split_cast_fp16_1)[name = tensor("x_257_split_1_sigmoid_cast_fp16")]; tensor x_257_cast_fp16 = mul(x = x_257_split_cast_fp16_0, y = x_257_split_1_sigmoid_cast_fp16)[name = tensor("x_257_cast_fp16")]; tensor input0_221_cast_fp16 = select(a = var_8_to_fp16, b = x_257_cast_fp16, cond = var_457)[name = tensor("input0_221_cast_fp16")]; tensor input0_223_pad_0 = const()[name = tensor("input0_223_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_223_mode_0 = const()[name = tensor("input0_223_mode_0"), val = tensor("constant")]; tensor const_42_to_fp16 = const()[name = tensor("const_42_to_fp16"), val = tensor(0x0p+0)]; tensor input0_223_cast_fp16 = pad(constant_val = const_42_to_fp16, mode = input0_223_mode_0, pad = input0_223_pad_0, x = input0_221_cast_fp16)[name = tensor("input0_223_cast_fp16")]; tensor input1_66_pad_type_0 = const()[name = tensor("input1_66_pad_type_0"), val = tensor("valid")]; tensor input1_66_groups_0 = const()[name = tensor("input1_66_groups_0"), val = tensor(1024)]; tensor input1_66_strides_0 = const()[name = tensor("input1_66_strides_0"), val = tensor([1])]; tensor input1_66_pad_0 = const()[name = tensor("input1_66_pad_0"), val = tensor([0, 0])]; tensor input1_66_dilations_0 = const()[name = tensor("input1_66_dilations_0"), val = tensor([1])]; tensor const_89_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204444352))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204449024))), name = tensor("const_89_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_90_to_fp16 = const()[name = tensor("const_90_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204449152)))]; tensor input_229_cast_fp16 = conv(bias = const_90_to_fp16, dilations = input1_66_dilations_0, groups = input1_66_groups_0, pad = input1_66_pad_0, pad_type = input1_66_pad_type_0, strides = input1_66_strides_0, weight = const_89_to_fp16_palettized, x = input0_223_cast_fp16)[name = tensor("input_229_cast_fp16")]; tensor var_2917_cast_fp16 = silu(x = input_229_cast_fp16)[name = tensor("op_2917_cast_fp16")]; tensor x_259_pad_type_0 = const()[name = tensor("x_259_pad_type_0"), val = tensor("valid")]; tensor x_259_strides_0 = const()[name = tensor("x_259_strides_0"), val = tensor([1])]; tensor x_259_pad_0 = const()[name = tensor("x_259_pad_0"), val = tensor([0, 0])]; tensor x_259_dilations_0 = const()[name = tensor("x_259_dilations_0"), val = tensor([1])]; tensor x_259_groups_0 = const()[name = tensor("x_259_groups_0"), val = tensor(1)]; tensor encoder_layers_15_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204451264))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204975616))), name = tensor("encoder_layers_15_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_259_cast_fp16 = conv(dilations = x_259_dilations_0, groups = x_259_groups_0, pad = x_259_pad_0, pad_type = x_259_pad_type_0, strides = x_259_strides_0, weight = encoder_layers_15_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2917_cast_fp16)[name = tensor("x_259_cast_fp16")]; tensor var_2924_perm_0 = const()[name = tensor("op_2924_perm_0"), val = tensor([0, 2, 1])]; tensor var_2924_cast_fp16 = transpose(perm = var_2924_perm_0, x = x_259_cast_fp16)[name = tensor("transpose_352")]; tensor input1_68_cast_fp16 = add(x = input0_217_cast_fp16, y = var_2924_cast_fp16)[name = tensor("input1_68_cast_fp16")]; tensor input0_225_axes_0 = const()[name = tensor("input0_225_axes_0"), val = tensor([-1])]; tensor encoder_layers_15_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_15_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204975744)))]; tensor encoder_layers_15_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_15_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204977856)))]; tensor input0_225_cast_fp16 = layer_norm(axes = input0_225_axes_0, beta = encoder_layers_15_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_15_norm_feed_forward2_weight_to_fp16, x = input1_68_cast_fp16)[name = tensor("input0_225_cast_fp16")]; tensor encoder_layers_15_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(204979968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207077184))), name = tensor("encoder_layers_15_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_143_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_15_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_225_cast_fp16)[name = tensor("linear_143_cast_fp16")]; tensor var_2935_cast_fp16 = silu(x = linear_143_cast_fp16)[name = tensor("op_2935_cast_fp16")]; tensor encoder_layers_15_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(207077312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(209174528))), name = tensor("encoder_layers_15_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_144_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_15_feed_forward2_linear2_weight_to_fp16_palettized, x = var_2935_cast_fp16)[name = tensor("linear_144_cast_fp16")]; tensor var_2940_to_fp16 = const()[name = tensor("op_2940_to_fp16"), val = tensor(0x1p-1)]; tensor var_2941_cast_fp16 = mul(x = linear_144_cast_fp16, y = var_2940_to_fp16)[name = tensor("op_2941_cast_fp16")]; tensor input2_34_cast_fp16 = add(x = input1_68_cast_fp16, y = var_2941_cast_fp16)[name = tensor("input2_34_cast_fp16")]; tensor input0_227_axes_0 = const()[name = tensor("input0_227_axes_0"), val = tensor([-1])]; tensor encoder_layers_15_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_15_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(209174656)))]; tensor encoder_layers_15_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_15_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(209176768)))]; tensor input0_227_cast_fp16 = layer_norm(axes = input0_227_axes_0, beta = encoder_layers_15_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_15_norm_out_weight_to_fp16, x = input2_34_cast_fp16)[name = tensor("input0_227_cast_fp16")]; tensor input_233_axes_0 = const()[name = tensor("input_233_axes_0"), val = tensor([-1])]; tensor encoder_layers_16_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_16_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(209178880)))]; tensor encoder_layers_16_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_16_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(209180992)))]; tensor input_233_cast_fp16 = layer_norm(axes = input_233_axes_0, beta = encoder_layers_16_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_16_norm_feed_forward1_weight_to_fp16, x = input0_227_cast_fp16)[name = tensor("input_233_cast_fp16")]; tensor encoder_layers_16_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(209183104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211280320))), name = tensor("encoder_layers_16_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_145_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_16_feed_forward1_linear1_weight_to_fp16_palettized, x = input_233_cast_fp16)[name = tensor("linear_145_cast_fp16")]; tensor var_2964_cast_fp16 = silu(x = linear_145_cast_fp16)[name = tensor("op_2964_cast_fp16")]; tensor encoder_layers_16_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(211280448))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213377664))), name = tensor("encoder_layers_16_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_146_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_feed_forward1_linear2_weight_to_fp16_palettized, x = var_2964_cast_fp16)[name = tensor("linear_146_cast_fp16")]; tensor var_2969_to_fp16 = const()[name = tensor("op_2969_to_fp16"), val = tensor(0x1p-1)]; tensor var_2970_cast_fp16 = mul(x = linear_146_cast_fp16, y = var_2969_to_fp16)[name = tensor("op_2970_cast_fp16")]; tensor input_237_cast_fp16 = add(x = input0_227_cast_fp16, y = var_2970_cast_fp16)[name = tensor("input_237_cast_fp16")]; tensor query_34_axes_0 = const()[name = tensor("query_34_axes_0"), val = tensor([-1])]; tensor encoder_layers_16_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_16_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213377792)))]; tensor encoder_layers_16_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_16_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213379904)))]; tensor query_34_cast_fp16 = layer_norm(axes = query_34_axes_0, beta = encoder_layers_16_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_16_norm_self_att_weight_to_fp16, x = input_237_cast_fp16)[name = tensor("query_34_cast_fp16")]; tensor var_2983_shape_cast_fp16 = shape(x = query_34_cast_fp16)[name = tensor("op_2983_shape_cast_fp16")]; tensor gather_180_axis_0 = const()[name = tensor("gather_180_axis_0"), val = tensor(0)]; tensor gather_180_batch_dims_0 = const()[name = tensor("gather_180_batch_dims_0"), val = tensor(0)]; tensor gather_180_validate_indices_0 = const()[name = tensor("gather_180_validate_indices_0"), val = tensor(false)]; tensor var_2983_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_2983_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_180_to_uint16 = const()[name = tensor("select_180_to_uint16"), val = tensor(0)]; tensor var_2983_shape_cast_fp16_to_uint16 = cast(dtype = var_2983_shape_cast_fp16_to_uint16_dtype_0, x = var_2983_shape_cast_fp16)[name = tensor("cast_79")]; tensor gather_180_cast_uint16 = gather(axis = gather_180_axis_0, batch_dims = gather_180_batch_dims_0, indices = select_180_to_uint16, validate_indices = gather_180_validate_indices_0, x = var_2983_shape_cast_fp16_to_uint16)[name = tensor("gather_180_cast_uint16")]; tensor gather_180_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_180_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_16_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213382016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213906368))), name = tensor("encoder_layers_16_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_147_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_self_attn_linear_q_weight_to_fp16_palettized, x = query_34_cast_fp16)[name = tensor("linear_147_cast_fp16")]; tensor concat_136_axis_0 = const()[name = tensor("concat_136_axis_0"), val = tensor(0)]; tensor concat_136_interleave_0 = const()[name = tensor("concat_136_interleave_0"), val = tensor(false)]; tensor gather_180_cast_uint16_to_int32 = cast(dtype = gather_180_cast_uint16_to_int32_dtype_0, x = gather_180_cast_uint16)[name = tensor("cast_78")]; tensor concat_136 = concat(axis = concat_136_axis_0, interleave = concat_136_interleave_0, values = (gather_180_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_136")]; tensor q_34_cast_fp16 = reshape(shape = concat_136, x = linear_147_cast_fp16)[name = tensor("q_34_cast_fp16")]; tensor encoder_layers_16_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(213906496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214430848))), name = tensor("encoder_layers_16_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_148_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_self_attn_linear_k_weight_to_fp16_palettized, x = query_34_cast_fp16)[name = tensor("linear_148_cast_fp16")]; tensor k_34_cast_fp16 = reshape(shape = concat_136, x = linear_148_cast_fp16)[name = tensor("k_34_cast_fp16")]; tensor encoder_layers_16_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214430976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214955328))), name = tensor("encoder_layers_16_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_149_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_self_attn_linear_v_weight_to_fp16_palettized, x = query_34_cast_fp16)[name = tensor("linear_149_cast_fp16")]; tensor v_34_cast_fp16 = reshape(shape = concat_136, x = linear_149_cast_fp16)[name = tensor("v_34_cast_fp16")]; tensor value_34_perm_0 = const()[name = tensor("value_34_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_16_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(214955456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215479808))), name = tensor("encoder_layers_16_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_150_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_150_cast_fp16")]; tensor var_3003 = const()[name = tensor("op_3003"), val = tensor([1, -1, 8, 128])]; tensor p_34_cast_fp16 = reshape(shape = var_3003, x = linear_150_cast_fp16)[name = tensor("p_34_cast_fp16")]; tensor encoder_layers_16_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_16_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215479936)))]; tensor var_3006_cast_fp16 = add(x = q_34_cast_fp16, y = encoder_layers_16_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3006_cast_fp16")]; tensor encoder_layers_16_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_16_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215482048)))]; tensor var_3008_cast_fp16 = add(x = q_34_cast_fp16, y = encoder_layers_16_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3008_cast_fp16")]; tensor x_267_transpose_x_0 = const()[name = tensor("x_267_transpose_x_0"), val = tensor(false)]; tensor x_267_transpose_y_0 = const()[name = tensor("x_267_transpose_y_0"), val = tensor(false)]; tensor transpose_256_perm_0 = const()[name = tensor("transpose_256_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_257_perm_0 = const()[name = tensor("transpose_257_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_257 = transpose(perm = transpose_257_perm_0, x = p_34_cast_fp16)[name = tensor("transpose_350")]; tensor transpose_256 = transpose(perm = transpose_256_perm_0, x = var_3008_cast_fp16)[name = tensor("transpose_351")]; tensor x_267_cast_fp16 = matmul(transpose_x = x_267_transpose_x_0, transpose_y = x_267_transpose_y_0, x = transpose_256, y = transpose_257)[name = tensor("x_267_cast_fp16")]; tensor var_3012_shape_cast_fp16 = shape(x = x_267_cast_fp16)[name = tensor("op_3012_shape_cast_fp16")]; tensor gather_182_axis_0 = const()[name = tensor("gather_182_axis_0"), val = tensor(0)]; tensor gather_182_batch_dims_0 = const()[name = tensor("gather_182_batch_dims_0"), val = tensor(0)]; tensor gather_182_validate_indices_0 = const()[name = tensor("gather_182_validate_indices_0"), val = tensor(false)]; tensor var_3012_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3012_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_182_to_uint16 = const()[name = tensor("select_182_to_uint16"), val = tensor(0)]; tensor var_3012_shape_cast_fp16_to_uint16 = cast(dtype = var_3012_shape_cast_fp16_to_uint16_dtype_0, x = var_3012_shape_cast_fp16)[name = tensor("cast_77")]; tensor gather_182_cast_uint16 = gather(axis = gather_182_axis_0, batch_dims = gather_182_batch_dims_0, indices = select_182_to_uint16, validate_indices = gather_182_validate_indices_0, x = var_3012_shape_cast_fp16_to_uint16)[name = tensor("gather_182_cast_uint16")]; tensor gather_182_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_182_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_183 = const()[name = tensor("gather_183"), val = tensor(8)]; tensor gather_184_axis_0 = const()[name = tensor("gather_184_axis_0"), val = tensor(0)]; tensor gather_184_batch_dims_0 = const()[name = tensor("gather_184_batch_dims_0"), val = tensor(0)]; tensor gather_184_validate_indices_0 = const()[name = tensor("gather_184_validate_indices_0"), val = tensor(false)]; tensor select_184_to_uint16 = const()[name = tensor("select_184_to_uint16"), val = tensor(2)]; tensor gather_184_cast_uint16 = gather(axis = gather_184_axis_0, batch_dims = gather_184_batch_dims_0, indices = select_184_to_uint16, validate_indices = gather_184_validate_indices_0, x = var_3012_shape_cast_fp16_to_uint16)[name = tensor("gather_184_cast_uint16")]; tensor gather_184_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_184_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_185_axis_0 = const()[name = tensor("gather_185_axis_0"), val = tensor(0)]; tensor gather_185_batch_dims_0 = const()[name = tensor("gather_185_batch_dims_0"), val = tensor(0)]; tensor gather_185_validate_indices_0 = const()[name = tensor("gather_185_validate_indices_0"), val = tensor(false)]; tensor select_185_to_uint16 = const()[name = tensor("select_185_to_uint16"), val = tensor(3)]; tensor gather_185_cast_uint16 = gather(axis = gather_185_axis_0, batch_dims = gather_185_batch_dims_0, indices = select_185_to_uint16, validate_indices = gather_185_validate_indices_0, x = var_3012_shape_cast_fp16_to_uint16)[name = tensor("gather_185_cast_uint16")]; tensor gather_185_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_185_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_36_pad_0 = const()[name = tensor("x0_36_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_36_mode_0 = const()[name = tensor("x0_36_mode_0"), val = tensor("constant")]; tensor const_43_to_fp16 = const()[name = tensor("const_43_to_fp16"), val = tensor(0x0p+0)]; tensor x0_36_cast_fp16 = pad(constant_val = const_43_to_fp16, mode = x0_36_mode_0, pad = x0_36_pad_0, x = x_267_cast_fp16)[name = tensor("x0_36_cast_fp16")]; tensor concat_139_axis_0 = const()[name = tensor("concat_139_axis_0"), val = tensor(0)]; tensor concat_139_interleave_0 = const()[name = tensor("concat_139_interleave_0"), val = tensor(false)]; tensor gather_182_cast_uint16_to_int32 = cast(dtype = gather_182_cast_uint16_to_int32_dtype_0, x = gather_182_cast_uint16)[name = tensor("cast_75")]; tensor gather_184_cast_uint16_to_int32 = cast(dtype = gather_184_cast_uint16_to_int32_dtype_0, x = gather_184_cast_uint16)[name = tensor("cast_76")]; tensor concat_139 = concat(axis = concat_139_axis_0, interleave = concat_139_interleave_0, values = (gather_182_cast_uint16_to_int32, gather_183, var_21, gather_184_cast_uint16_to_int32))[name = tensor("concat_139")]; tensor x1_34_cast_fp16 = reshape(shape = concat_139, x = x0_36_cast_fp16)[name = tensor("x1_34_cast_fp16")]; tensor var_3022_begin_0 = const()[name = tensor("op_3022_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3022_end_0 = const()[name = tensor("op_3022_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_3022_end_mask_0 = const()[name = tensor("op_3022_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3022_cast_fp16 = slice_by_index(begin = var_3022_begin_0, end = var_3022_end_0, end_mask = var_3022_end_mask_0, x = x1_34_cast_fp16)[name = tensor("op_3022_cast_fp16")]; tensor concat_140_axis_0 = const()[name = tensor("concat_140_axis_0"), val = tensor(0)]; tensor concat_140_interleave_0 = const()[name = tensor("concat_140_interleave_0"), val = tensor(false)]; tensor gather_185_cast_uint16_to_int32 = cast(dtype = gather_185_cast_uint16_to_int32_dtype_0, x = gather_185_cast_uint16)[name = tensor("cast_74")]; tensor concat_140 = concat(axis = concat_140_axis_0, interleave = concat_140_interleave_0, values = (gather_182_cast_uint16_to_int32, gather_183, gather_184_cast_uint16_to_int32, gather_185_cast_uint16_to_int32))[name = tensor("concat_140")]; tensor matrix_bd_34_cast_fp16 = reshape(shape = concat_140, x = var_3022_cast_fp16)[name = tensor("matrix_bd_34_cast_fp16")]; tensor matrix_ac_34_transpose_x_0 = const()[name = tensor("matrix_ac_34_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_34_transpose_y_0 = const()[name = tensor("matrix_ac_34_transpose_y_0"), val = tensor(false)]; tensor transpose_258_perm_0 = const()[name = tensor("transpose_258_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_259_perm_0 = const()[name = tensor("transpose_259_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_259 = transpose(perm = transpose_259_perm_0, x = k_34_cast_fp16)[name = tensor("transpose_348")]; tensor transpose_258 = transpose(perm = transpose_258_perm_0, x = var_3006_cast_fp16)[name = tensor("transpose_349")]; tensor matrix_ac_34_cast_fp16 = matmul(transpose_x = matrix_ac_34_transpose_x_0, transpose_y = matrix_ac_34_transpose_y_0, x = transpose_258, y = transpose_259)[name = tensor("matrix_ac_34_cast_fp16")]; tensor var_3027_shape_cast_fp16 = shape(x = matrix_ac_34_cast_fp16)[name = tensor("op_3027_shape_cast_fp16")]; tensor gather_186_axis_0 = const()[name = tensor("gather_186_axis_0"), val = tensor(0)]; tensor gather_186_batch_dims_0 = const()[name = tensor("gather_186_batch_dims_0"), val = tensor(0)]; tensor gather_186_validate_indices_0 = const()[name = tensor("gather_186_validate_indices_0"), val = tensor(false)]; tensor var_3027_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3027_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_186_to_uint16 = const()[name = tensor("select_186_to_uint16"), val = tensor(3)]; tensor var_3027_shape_cast_fp16_to_uint16 = cast(dtype = var_3027_shape_cast_fp16_to_uint16_dtype_0, x = var_3027_shape_cast_fp16)[name = tensor("cast_73")]; tensor gather_186_cast_uint16 = gather(axis = gather_186_axis_0, batch_dims = gather_186_batch_dims_0, indices = select_186_to_uint16, validate_indices = gather_186_validate_indices_0, x = var_3027_shape_cast_fp16_to_uint16)[name = tensor("gather_186_cast_uint16")]; tensor gather_186_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_186_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_141_values0_0 = const()[name = tensor("concat_141_values0_0"), val = tensor(0)]; tensor concat_141_values1_0 = const()[name = tensor("concat_141_values1_0"), val = tensor(8)]; tensor concat_141_values2_0 = const()[name = tensor("concat_141_values2_0"), val = tensor(0)]; tensor concat_141_axis_0 = const()[name = tensor("concat_141_axis_0"), val = tensor(0)]; tensor concat_141_interleave_0 = const()[name = tensor("concat_141_interleave_0"), val = tensor(false)]; tensor gather_186_cast_uint16_to_int32 = cast(dtype = gather_186_cast_uint16_to_int32_dtype_0, x = gather_186_cast_uint16)[name = tensor("cast_72")]; tensor concat_141 = concat(axis = concat_141_axis_0, interleave = concat_141_interleave_0, values = (concat_141_values0_0, concat_141_values1_0, concat_141_values2_0, gather_186_cast_uint16_to_int32))[name = tensor("concat_141")]; tensor matrix_bd0_34_begin_0 = const()[name = tensor("matrix_bd0_34_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_34_end_mask_0 = const()[name = tensor("matrix_bd0_34_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_34_cast_fp16 = slice_by_index(begin = matrix_bd0_34_begin_0, end = concat_141, end_mask = matrix_bd0_34_end_mask_0, x = matrix_bd_34_cast_fp16)[name = tensor("matrix_bd0_34_cast_fp16")]; tensor var_3032_cast_fp16 = add(x = matrix_ac_34_cast_fp16, y = matrix_bd0_34_cast_fp16)[name = tensor("op_3032_cast_fp16")]; tensor _inversed_scores_34_y_0_to_fp16 = const()[name = tensor("_inversed_scores_34_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_34_cast_fp16 = mul(x = var_3032_cast_fp16, y = _inversed_scores_34_y_0_to_fp16)[name = tensor("_inversed_scores_34_cast_fp16")]; tensor value_34_cast_fp16 = transpose(perm = value_34_perm_0, x = v_34_cast_fp16)[name = tensor("transpose_347")]; tensor var_3035_shape_cast_fp16 = shape(x = value_34_cast_fp16)[name = tensor("op_3035_shape_cast_fp16")]; tensor gather_187_axis_0 = const()[name = tensor("gather_187_axis_0"), val = tensor(0)]; tensor gather_187_batch_dims_0 = const()[name = tensor("gather_187_batch_dims_0"), val = tensor(0)]; tensor gather_187_validate_indices_0 = const()[name = tensor("gather_187_validate_indices_0"), val = tensor(false)]; tensor var_3035_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3035_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_187_to_uint16 = const()[name = tensor("select_187_to_uint16"), val = tensor(0)]; tensor var_3035_shape_cast_fp16_to_uint16 = cast(dtype = var_3035_shape_cast_fp16_to_uint16_dtype_0, x = var_3035_shape_cast_fp16)[name = tensor("cast_71")]; tensor gather_187_cast_uint16 = gather(axis = gather_187_axis_0, batch_dims = gather_187_batch_dims_0, indices = select_187_to_uint16, validate_indices = gather_187_validate_indices_0, x = var_3035_shape_cast_fp16_to_uint16)[name = tensor("gather_187_cast_uint16")]; tensor gather_187_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_187_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_34_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_34_cast_fp16, cond = mask0_4)[name = tensor("scores0_34_cast_fp16")]; tensor var_3038_cast_fp16 = softmax(axis = var_21, x = scores0_34_cast_fp16)[name = tensor("op_3038_cast_fp16")]; tensor input_239_cast_fp16 = select(a = var_8_to_fp16, b = var_3038_cast_fp16, cond = mask0_4)[name = tensor("input_239_cast_fp16")]; tensor x2_34_transpose_x_0 = const()[name = tensor("x2_34_transpose_x_0"), val = tensor(false)]; tensor x2_34_transpose_y_0 = const()[name = tensor("x2_34_transpose_y_0"), val = tensor(false)]; tensor x2_34_cast_fp16 = matmul(transpose_x = x2_34_transpose_x_0, transpose_y = x2_34_transpose_y_0, x = input_239_cast_fp16, y = value_34_cast_fp16)[name = tensor("x2_34_cast_fp16")]; tensor var_3042_perm_0 = const()[name = tensor("op_3042_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_142_axis_0 = const()[name = tensor("concat_142_axis_0"), val = tensor(0)]; tensor concat_142_interleave_0 = const()[name = tensor("concat_142_interleave_0"), val = tensor(false)]; tensor gather_187_cast_uint16_to_int32 = cast(dtype = gather_187_cast_uint16_to_int32_dtype_0, x = gather_187_cast_uint16)[name = tensor("cast_70")]; tensor concat_142 = concat(axis = concat_142_axis_0, interleave = concat_142_interleave_0, values = (gather_187_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_142")]; tensor var_3042_cast_fp16 = transpose(perm = var_3042_perm_0, x = x2_34_cast_fp16)[name = tensor("transpose_346")]; tensor input0_229_cast_fp16 = reshape(shape = concat_142, x = var_3042_cast_fp16)[name = tensor("input0_229_cast_fp16")]; tensor encoder_layers_16_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(215484160))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216008512))), name = tensor("encoder_layers_16_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_151_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_self_attn_linear_out_weight_to_fp16_palettized, x = input0_229_cast_fp16)[name = tensor("linear_151_cast_fp16")]; tensor input0_231_cast_fp16 = add(x = input_237_cast_fp16, y = linear_151_cast_fp16)[name = tensor("input0_231_cast_fp16")]; tensor x_271_axes_0 = const()[name = tensor("x_271_axes_0"), val = tensor([-1])]; tensor encoder_layers_16_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_16_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216008640)))]; tensor encoder_layers_16_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_16_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216010752)))]; tensor x_271_cast_fp16 = layer_norm(axes = x_271_axes_0, beta = encoder_layers_16_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_16_norm_conv_weight_to_fp16, x = input0_231_cast_fp16)[name = tensor("x_271_cast_fp16")]; tensor input_241_perm_0 = const()[name = tensor("input_241_perm_0"), val = tensor([0, 2, 1])]; tensor input0_233_pad_type_0 = const()[name = tensor("input0_233_pad_type_0"), val = tensor("valid")]; tensor input0_233_strides_0 = const()[name = tensor("input0_233_strides_0"), val = tensor([1])]; tensor input0_233_pad_0 = const()[name = tensor("input0_233_pad_0"), val = tensor([0, 0])]; tensor input0_233_dilations_0 = const()[name = tensor("input0_233_dilations_0"), val = tensor([1])]; tensor input0_233_groups_0 = const()[name = tensor("input0_233_groups_0"), val = tensor(1)]; tensor encoder_layers_16_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(216012864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217061504))), name = tensor("encoder_layers_16_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_241_cast_fp16 = transpose(perm = input_241_perm_0, x = x_271_cast_fp16)[name = tensor("transpose_345")]; tensor input0_233_cast_fp16 = conv(dilations = input0_233_dilations_0, groups = input0_233_groups_0, pad = input0_233_pad_0, pad_type = input0_233_pad_type_0, strides = input0_233_strides_0, weight = encoder_layers_16_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_241_cast_fp16)[name = tensor("input0_233_cast_fp16")]; tensor x_273_split_num_splits_0 = const()[name = tensor("x_273_split_num_splits_0"), val = tensor(2)]; tensor x_273_split_axis_0 = const()[name = tensor("x_273_split_axis_0"), val = tensor(1)]; tensor x_273_split_cast_fp16_0, tensor x_273_split_cast_fp16_1 = split(axis = x_273_split_axis_0, num_splits = x_273_split_num_splits_0, x = input0_233_cast_fp16)[name = tensor("x_273_split_cast_fp16")]; tensor x_273_split_1_sigmoid_cast_fp16 = sigmoid(x = x_273_split_cast_fp16_1)[name = tensor("x_273_split_1_sigmoid_cast_fp16")]; tensor x_273_cast_fp16 = mul(x = x_273_split_cast_fp16_0, y = x_273_split_1_sigmoid_cast_fp16)[name = tensor("x_273_cast_fp16")]; tensor input0_235_cast_fp16 = select(a = var_8_to_fp16, b = x_273_cast_fp16, cond = var_457)[name = tensor("input0_235_cast_fp16")]; tensor input0_237_pad_0 = const()[name = tensor("input0_237_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_237_mode_0 = const()[name = tensor("input0_237_mode_0"), val = tensor("constant")]; tensor const_44_to_fp16 = const()[name = tensor("const_44_to_fp16"), val = tensor(0x0p+0)]; tensor input0_237_cast_fp16 = pad(constant_val = const_44_to_fp16, mode = input0_237_mode_0, pad = input0_237_pad_0, x = input0_235_cast_fp16)[name = tensor("input0_237_cast_fp16")]; tensor input1_70_pad_type_0 = const()[name = tensor("input1_70_pad_type_0"), val = tensor("valid")]; tensor input1_70_groups_0 = const()[name = tensor("input1_70_groups_0"), val = tensor(1024)]; tensor input1_70_strides_0 = const()[name = tensor("input1_70_strides_0"), val = tensor([1])]; tensor input1_70_pad_0 = const()[name = tensor("input1_70_pad_0"), val = tensor([0, 0])]; tensor input1_70_dilations_0 = const()[name = tensor("input1_70_dilations_0"), val = tensor([1])]; tensor const_91_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217061632))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217066304))), name = tensor("const_91_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_92_to_fp16 = const()[name = tensor("const_92_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217066432)))]; tensor input_243_cast_fp16 = conv(bias = const_92_to_fp16, dilations = input1_70_dilations_0, groups = input1_70_groups_0, pad = input1_70_pad_0, pad_type = input1_70_pad_type_0, strides = input1_70_strides_0, weight = const_91_to_fp16_palettized, x = input0_237_cast_fp16)[name = tensor("input_243_cast_fp16")]; tensor var_3080_cast_fp16 = silu(x = input_243_cast_fp16)[name = tensor("op_3080_cast_fp16")]; tensor x_275_pad_type_0 = const()[name = tensor("x_275_pad_type_0"), val = tensor("valid")]; tensor x_275_strides_0 = const()[name = tensor("x_275_strides_0"), val = tensor([1])]; tensor x_275_pad_0 = const()[name = tensor("x_275_pad_0"), val = tensor([0, 0])]; tensor x_275_dilations_0 = const()[name = tensor("x_275_dilations_0"), val = tensor([1])]; tensor x_275_groups_0 = const()[name = tensor("x_275_groups_0"), val = tensor(1)]; tensor encoder_layers_16_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217068544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217592896))), name = tensor("encoder_layers_16_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_275_cast_fp16 = conv(dilations = x_275_dilations_0, groups = x_275_groups_0, pad = x_275_pad_0, pad_type = x_275_pad_type_0, strides = x_275_strides_0, weight = encoder_layers_16_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3080_cast_fp16)[name = tensor("x_275_cast_fp16")]; tensor var_3087_perm_0 = const()[name = tensor("op_3087_perm_0"), val = tensor([0, 2, 1])]; tensor var_3087_cast_fp16 = transpose(perm = var_3087_perm_0, x = x_275_cast_fp16)[name = tensor("transpose_344")]; tensor input1_72_cast_fp16 = add(x = input0_231_cast_fp16, y = var_3087_cast_fp16)[name = tensor("input1_72_cast_fp16")]; tensor input0_239_axes_0 = const()[name = tensor("input0_239_axes_0"), val = tensor([-1])]; tensor encoder_layers_16_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_16_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217593024)))]; tensor encoder_layers_16_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_16_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217595136)))]; tensor input0_239_cast_fp16 = layer_norm(axes = input0_239_axes_0, beta = encoder_layers_16_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_16_norm_feed_forward2_weight_to_fp16, x = input1_72_cast_fp16)[name = tensor("input0_239_cast_fp16")]; tensor encoder_layers_16_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(217597248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219694464))), name = tensor("encoder_layers_16_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_152_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_16_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_239_cast_fp16)[name = tensor("linear_152_cast_fp16")]; tensor var_3098_cast_fp16 = silu(x = linear_152_cast_fp16)[name = tensor("op_3098_cast_fp16")]; tensor encoder_layers_16_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(219694592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221791808))), name = tensor("encoder_layers_16_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_153_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_16_feed_forward2_linear2_weight_to_fp16_palettized, x = var_3098_cast_fp16)[name = tensor("linear_153_cast_fp16")]; tensor var_3103_to_fp16 = const()[name = tensor("op_3103_to_fp16"), val = tensor(0x1p-1)]; tensor var_3104_cast_fp16 = mul(x = linear_153_cast_fp16, y = var_3103_to_fp16)[name = tensor("op_3104_cast_fp16")]; tensor input2_36_cast_fp16 = add(x = input1_72_cast_fp16, y = var_3104_cast_fp16)[name = tensor("input2_36_cast_fp16")]; tensor input0_241_axes_0 = const()[name = tensor("input0_241_axes_0"), val = tensor([-1])]; tensor encoder_layers_16_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_16_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221791936)))]; tensor encoder_layers_16_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_16_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221794048)))]; tensor input0_241_cast_fp16 = layer_norm(axes = input0_241_axes_0, beta = encoder_layers_16_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_16_norm_out_weight_to_fp16, x = input2_36_cast_fp16)[name = tensor("input0_241_cast_fp16")]; tensor input_247_axes_0 = const()[name = tensor("input_247_axes_0"), val = tensor([-1])]; tensor encoder_layers_17_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_17_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221796160)))]; tensor encoder_layers_17_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_17_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221798272)))]; tensor input_247_cast_fp16 = layer_norm(axes = input_247_axes_0, beta = encoder_layers_17_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_17_norm_feed_forward1_weight_to_fp16, x = input0_241_cast_fp16)[name = tensor("input_247_cast_fp16")]; tensor encoder_layers_17_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(221800384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223897600))), name = tensor("encoder_layers_17_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_154_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_17_feed_forward1_linear1_weight_to_fp16_palettized, x = input_247_cast_fp16)[name = tensor("linear_154_cast_fp16")]; tensor var_3127_cast_fp16 = silu(x = linear_154_cast_fp16)[name = tensor("op_3127_cast_fp16")]; tensor encoder_layers_17_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(223897728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225994944))), name = tensor("encoder_layers_17_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_155_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_feed_forward1_linear2_weight_to_fp16_palettized, x = var_3127_cast_fp16)[name = tensor("linear_155_cast_fp16")]; tensor var_3132_to_fp16 = const()[name = tensor("op_3132_to_fp16"), val = tensor(0x1p-1)]; tensor var_3133_cast_fp16 = mul(x = linear_155_cast_fp16, y = var_3132_to_fp16)[name = tensor("op_3133_cast_fp16")]; tensor input_251_cast_fp16 = add(x = input0_241_cast_fp16, y = var_3133_cast_fp16)[name = tensor("input_251_cast_fp16")]; tensor query_36_axes_0 = const()[name = tensor("query_36_axes_0"), val = tensor([-1])]; tensor encoder_layers_17_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_17_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225995072)))]; tensor encoder_layers_17_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_17_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225997184)))]; tensor query_36_cast_fp16 = layer_norm(axes = query_36_axes_0, beta = encoder_layers_17_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_17_norm_self_att_weight_to_fp16, x = input_251_cast_fp16)[name = tensor("query_36_cast_fp16")]; tensor var_3146_shape_cast_fp16 = shape(x = query_36_cast_fp16)[name = tensor("op_3146_shape_cast_fp16")]; tensor gather_188_axis_0 = const()[name = tensor("gather_188_axis_0"), val = tensor(0)]; tensor gather_188_batch_dims_0 = const()[name = tensor("gather_188_batch_dims_0"), val = tensor(0)]; tensor gather_188_validate_indices_0 = const()[name = tensor("gather_188_validate_indices_0"), val = tensor(false)]; tensor var_3146_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3146_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_188_to_uint16 = const()[name = tensor("select_188_to_uint16"), val = tensor(0)]; tensor var_3146_shape_cast_fp16_to_uint16 = cast(dtype = var_3146_shape_cast_fp16_to_uint16_dtype_0, x = var_3146_shape_cast_fp16)[name = tensor("cast_69")]; tensor gather_188_cast_uint16 = gather(axis = gather_188_axis_0, batch_dims = gather_188_batch_dims_0, indices = select_188_to_uint16, validate_indices = gather_188_validate_indices_0, x = var_3146_shape_cast_fp16_to_uint16)[name = tensor("gather_188_cast_uint16")]; tensor gather_188_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_188_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_17_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(225999296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226523648))), name = tensor("encoder_layers_17_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_156_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_self_attn_linear_q_weight_to_fp16_palettized, x = query_36_cast_fp16)[name = tensor("linear_156_cast_fp16")]; tensor concat_143_axis_0 = const()[name = tensor("concat_143_axis_0"), val = tensor(0)]; tensor concat_143_interleave_0 = const()[name = tensor("concat_143_interleave_0"), val = tensor(false)]; tensor gather_188_cast_uint16_to_int32 = cast(dtype = gather_188_cast_uint16_to_int32_dtype_0, x = gather_188_cast_uint16)[name = tensor("cast_68")]; tensor concat_143 = concat(axis = concat_143_axis_0, interleave = concat_143_interleave_0, values = (gather_188_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_143")]; tensor q_36_cast_fp16 = reshape(shape = concat_143, x = linear_156_cast_fp16)[name = tensor("q_36_cast_fp16")]; tensor encoder_layers_17_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(226523776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227048128))), name = tensor("encoder_layers_17_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_157_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_self_attn_linear_k_weight_to_fp16_palettized, x = query_36_cast_fp16)[name = tensor("linear_157_cast_fp16")]; tensor k_36_cast_fp16 = reshape(shape = concat_143, x = linear_157_cast_fp16)[name = tensor("k_36_cast_fp16")]; tensor encoder_layers_17_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227048256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227572608))), name = tensor("encoder_layers_17_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_158_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_self_attn_linear_v_weight_to_fp16_palettized, x = query_36_cast_fp16)[name = tensor("linear_158_cast_fp16")]; tensor v_36_cast_fp16 = reshape(shape = concat_143, x = linear_158_cast_fp16)[name = tensor("v_36_cast_fp16")]; tensor value_36_perm_0 = const()[name = tensor("value_36_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_17_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(227572736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228097088))), name = tensor("encoder_layers_17_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_159_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_159_cast_fp16")]; tensor var_3166 = const()[name = tensor("op_3166"), val = tensor([1, -1, 8, 128])]; tensor p_36_cast_fp16 = reshape(shape = var_3166, x = linear_159_cast_fp16)[name = tensor("p_36_cast_fp16")]; tensor encoder_layers_17_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_17_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228097216)))]; tensor var_3169_cast_fp16 = add(x = q_36_cast_fp16, y = encoder_layers_17_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3169_cast_fp16")]; tensor encoder_layers_17_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_17_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228099328)))]; tensor var_3171_cast_fp16 = add(x = q_36_cast_fp16, y = encoder_layers_17_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3171_cast_fp16")]; tensor x_283_transpose_x_0 = const()[name = tensor("x_283_transpose_x_0"), val = tensor(false)]; tensor x_283_transpose_y_0 = const()[name = tensor("x_283_transpose_y_0"), val = tensor(false)]; tensor transpose_260_perm_0 = const()[name = tensor("transpose_260_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_261_perm_0 = const()[name = tensor("transpose_261_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_261 = transpose(perm = transpose_261_perm_0, x = p_36_cast_fp16)[name = tensor("transpose_342")]; tensor transpose_260 = transpose(perm = transpose_260_perm_0, x = var_3171_cast_fp16)[name = tensor("transpose_343")]; tensor x_283_cast_fp16 = matmul(transpose_x = x_283_transpose_x_0, transpose_y = x_283_transpose_y_0, x = transpose_260, y = transpose_261)[name = tensor("x_283_cast_fp16")]; tensor var_3175_shape_cast_fp16 = shape(x = x_283_cast_fp16)[name = tensor("op_3175_shape_cast_fp16")]; tensor gather_190_axis_0 = const()[name = tensor("gather_190_axis_0"), val = tensor(0)]; tensor gather_190_batch_dims_0 = const()[name = tensor("gather_190_batch_dims_0"), val = tensor(0)]; tensor gather_190_validate_indices_0 = const()[name = tensor("gather_190_validate_indices_0"), val = tensor(false)]; tensor var_3175_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3175_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_190_to_uint16 = const()[name = tensor("select_190_to_uint16"), val = tensor(0)]; tensor var_3175_shape_cast_fp16_to_uint16 = cast(dtype = var_3175_shape_cast_fp16_to_uint16_dtype_0, x = var_3175_shape_cast_fp16)[name = tensor("cast_67")]; tensor gather_190_cast_uint16 = gather(axis = gather_190_axis_0, batch_dims = gather_190_batch_dims_0, indices = select_190_to_uint16, validate_indices = gather_190_validate_indices_0, x = var_3175_shape_cast_fp16_to_uint16)[name = tensor("gather_190_cast_uint16")]; tensor gather_190_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_190_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_191 = const()[name = tensor("gather_191"), val = tensor(8)]; tensor gather_192_axis_0 = const()[name = tensor("gather_192_axis_0"), val = tensor(0)]; tensor gather_192_batch_dims_0 = const()[name = tensor("gather_192_batch_dims_0"), val = tensor(0)]; tensor gather_192_validate_indices_0 = const()[name = tensor("gather_192_validate_indices_0"), val = tensor(false)]; tensor select_192_to_uint16 = const()[name = tensor("select_192_to_uint16"), val = tensor(2)]; tensor gather_192_cast_uint16 = gather(axis = gather_192_axis_0, batch_dims = gather_192_batch_dims_0, indices = select_192_to_uint16, validate_indices = gather_192_validate_indices_0, x = var_3175_shape_cast_fp16_to_uint16)[name = tensor("gather_192_cast_uint16")]; tensor gather_192_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_192_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_193_axis_0 = const()[name = tensor("gather_193_axis_0"), val = tensor(0)]; tensor gather_193_batch_dims_0 = const()[name = tensor("gather_193_batch_dims_0"), val = tensor(0)]; tensor gather_193_validate_indices_0 = const()[name = tensor("gather_193_validate_indices_0"), val = tensor(false)]; tensor select_193_to_uint16 = const()[name = tensor("select_193_to_uint16"), val = tensor(3)]; tensor gather_193_cast_uint16 = gather(axis = gather_193_axis_0, batch_dims = gather_193_batch_dims_0, indices = select_193_to_uint16, validate_indices = gather_193_validate_indices_0, x = var_3175_shape_cast_fp16_to_uint16)[name = tensor("gather_193_cast_uint16")]; tensor gather_193_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_193_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_38_pad_0 = const()[name = tensor("x0_38_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_38_mode_0 = const()[name = tensor("x0_38_mode_0"), val = tensor("constant")]; tensor const_45_to_fp16 = const()[name = tensor("const_45_to_fp16"), val = tensor(0x0p+0)]; tensor x0_38_cast_fp16 = pad(constant_val = const_45_to_fp16, mode = x0_38_mode_0, pad = x0_38_pad_0, x = x_283_cast_fp16)[name = tensor("x0_38_cast_fp16")]; tensor concat_146_axis_0 = const()[name = tensor("concat_146_axis_0"), val = tensor(0)]; tensor concat_146_interleave_0 = const()[name = tensor("concat_146_interleave_0"), val = tensor(false)]; tensor gather_190_cast_uint16_to_int32 = cast(dtype = gather_190_cast_uint16_to_int32_dtype_0, x = gather_190_cast_uint16)[name = tensor("cast_65")]; tensor gather_192_cast_uint16_to_int32 = cast(dtype = gather_192_cast_uint16_to_int32_dtype_0, x = gather_192_cast_uint16)[name = tensor("cast_66")]; tensor concat_146 = concat(axis = concat_146_axis_0, interleave = concat_146_interleave_0, values = (gather_190_cast_uint16_to_int32, gather_191, var_21, gather_192_cast_uint16_to_int32))[name = tensor("concat_146")]; tensor x1_36_cast_fp16 = reshape(shape = concat_146, x = x0_38_cast_fp16)[name = tensor("x1_36_cast_fp16")]; tensor var_3185_begin_0 = const()[name = tensor("op_3185_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3185_end_0 = const()[name = tensor("op_3185_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_3185_end_mask_0 = const()[name = tensor("op_3185_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3185_cast_fp16 = slice_by_index(begin = var_3185_begin_0, end = var_3185_end_0, end_mask = var_3185_end_mask_0, x = x1_36_cast_fp16)[name = tensor("op_3185_cast_fp16")]; tensor concat_147_axis_0 = const()[name = tensor("concat_147_axis_0"), val = tensor(0)]; tensor concat_147_interleave_0 = const()[name = tensor("concat_147_interleave_0"), val = tensor(false)]; tensor gather_193_cast_uint16_to_int32 = cast(dtype = gather_193_cast_uint16_to_int32_dtype_0, x = gather_193_cast_uint16)[name = tensor("cast_64")]; tensor concat_147 = concat(axis = concat_147_axis_0, interleave = concat_147_interleave_0, values = (gather_190_cast_uint16_to_int32, gather_191, gather_192_cast_uint16_to_int32, gather_193_cast_uint16_to_int32))[name = tensor("concat_147")]; tensor matrix_bd_36_cast_fp16 = reshape(shape = concat_147, x = var_3185_cast_fp16)[name = tensor("matrix_bd_36_cast_fp16")]; tensor matrix_ac_36_transpose_x_0 = const()[name = tensor("matrix_ac_36_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_36_transpose_y_0 = const()[name = tensor("matrix_ac_36_transpose_y_0"), val = tensor(false)]; tensor transpose_262_perm_0 = const()[name = tensor("transpose_262_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_263_perm_0 = const()[name = tensor("transpose_263_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_263 = transpose(perm = transpose_263_perm_0, x = k_36_cast_fp16)[name = tensor("transpose_340")]; tensor transpose_262 = transpose(perm = transpose_262_perm_0, x = var_3169_cast_fp16)[name = tensor("transpose_341")]; tensor matrix_ac_36_cast_fp16 = matmul(transpose_x = matrix_ac_36_transpose_x_0, transpose_y = matrix_ac_36_transpose_y_0, x = transpose_262, y = transpose_263)[name = tensor("matrix_ac_36_cast_fp16")]; tensor var_3190_shape_cast_fp16 = shape(x = matrix_ac_36_cast_fp16)[name = tensor("op_3190_shape_cast_fp16")]; tensor gather_194_axis_0 = const()[name = tensor("gather_194_axis_0"), val = tensor(0)]; tensor gather_194_batch_dims_0 = const()[name = tensor("gather_194_batch_dims_0"), val = tensor(0)]; tensor gather_194_validate_indices_0 = const()[name = tensor("gather_194_validate_indices_0"), val = tensor(false)]; tensor var_3190_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3190_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_194_to_uint16 = const()[name = tensor("select_194_to_uint16"), val = tensor(3)]; tensor var_3190_shape_cast_fp16_to_uint16 = cast(dtype = var_3190_shape_cast_fp16_to_uint16_dtype_0, x = var_3190_shape_cast_fp16)[name = tensor("cast_63")]; tensor gather_194_cast_uint16 = gather(axis = gather_194_axis_0, batch_dims = gather_194_batch_dims_0, indices = select_194_to_uint16, validate_indices = gather_194_validate_indices_0, x = var_3190_shape_cast_fp16_to_uint16)[name = tensor("gather_194_cast_uint16")]; tensor gather_194_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_194_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_148_values0_0 = const()[name = tensor("concat_148_values0_0"), val = tensor(0)]; tensor concat_148_values1_0 = const()[name = tensor("concat_148_values1_0"), val = tensor(8)]; tensor concat_148_values2_0 = const()[name = tensor("concat_148_values2_0"), val = tensor(0)]; tensor concat_148_axis_0 = const()[name = tensor("concat_148_axis_0"), val = tensor(0)]; tensor concat_148_interleave_0 = const()[name = tensor("concat_148_interleave_0"), val = tensor(false)]; tensor gather_194_cast_uint16_to_int32 = cast(dtype = gather_194_cast_uint16_to_int32_dtype_0, x = gather_194_cast_uint16)[name = tensor("cast_62")]; tensor concat_148 = concat(axis = concat_148_axis_0, interleave = concat_148_interleave_0, values = (concat_148_values0_0, concat_148_values1_0, concat_148_values2_0, gather_194_cast_uint16_to_int32))[name = tensor("concat_148")]; tensor matrix_bd0_36_begin_0 = const()[name = tensor("matrix_bd0_36_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_36_end_mask_0 = const()[name = tensor("matrix_bd0_36_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_36_cast_fp16 = slice_by_index(begin = matrix_bd0_36_begin_0, end = concat_148, end_mask = matrix_bd0_36_end_mask_0, x = matrix_bd_36_cast_fp16)[name = tensor("matrix_bd0_36_cast_fp16")]; tensor var_3195_cast_fp16 = add(x = matrix_ac_36_cast_fp16, y = matrix_bd0_36_cast_fp16)[name = tensor("op_3195_cast_fp16")]; tensor _inversed_scores_36_y_0_to_fp16 = const()[name = tensor("_inversed_scores_36_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_36_cast_fp16 = mul(x = var_3195_cast_fp16, y = _inversed_scores_36_y_0_to_fp16)[name = tensor("_inversed_scores_36_cast_fp16")]; tensor value_36_cast_fp16 = transpose(perm = value_36_perm_0, x = v_36_cast_fp16)[name = tensor("transpose_339")]; tensor var_3198_shape_cast_fp16 = shape(x = value_36_cast_fp16)[name = tensor("op_3198_shape_cast_fp16")]; tensor gather_195_axis_0 = const()[name = tensor("gather_195_axis_0"), val = tensor(0)]; tensor gather_195_batch_dims_0 = const()[name = tensor("gather_195_batch_dims_0"), val = tensor(0)]; tensor gather_195_validate_indices_0 = const()[name = tensor("gather_195_validate_indices_0"), val = tensor(false)]; tensor var_3198_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3198_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_195_to_uint16 = const()[name = tensor("select_195_to_uint16"), val = tensor(0)]; tensor var_3198_shape_cast_fp16_to_uint16 = cast(dtype = var_3198_shape_cast_fp16_to_uint16_dtype_0, x = var_3198_shape_cast_fp16)[name = tensor("cast_61")]; tensor gather_195_cast_uint16 = gather(axis = gather_195_axis_0, batch_dims = gather_195_batch_dims_0, indices = select_195_to_uint16, validate_indices = gather_195_validate_indices_0, x = var_3198_shape_cast_fp16_to_uint16)[name = tensor("gather_195_cast_uint16")]; tensor gather_195_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_195_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_36_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_36_cast_fp16, cond = mask0_4)[name = tensor("scores0_36_cast_fp16")]; tensor var_3201_cast_fp16 = softmax(axis = var_21, x = scores0_36_cast_fp16)[name = tensor("op_3201_cast_fp16")]; tensor input_253_cast_fp16 = select(a = var_8_to_fp16, b = var_3201_cast_fp16, cond = mask0_4)[name = tensor("input_253_cast_fp16")]; tensor x2_36_transpose_x_0 = const()[name = tensor("x2_36_transpose_x_0"), val = tensor(false)]; tensor x2_36_transpose_y_0 = const()[name = tensor("x2_36_transpose_y_0"), val = tensor(false)]; tensor x2_36_cast_fp16 = matmul(transpose_x = x2_36_transpose_x_0, transpose_y = x2_36_transpose_y_0, x = input_253_cast_fp16, y = value_36_cast_fp16)[name = tensor("x2_36_cast_fp16")]; tensor var_3205_perm_0 = const()[name = tensor("op_3205_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_149_axis_0 = const()[name = tensor("concat_149_axis_0"), val = tensor(0)]; tensor concat_149_interleave_0 = const()[name = tensor("concat_149_interleave_0"), val = tensor(false)]; tensor gather_195_cast_uint16_to_int32 = cast(dtype = gather_195_cast_uint16_to_int32_dtype_0, x = gather_195_cast_uint16)[name = tensor("cast_60")]; tensor concat_149 = concat(axis = concat_149_axis_0, interleave = concat_149_interleave_0, values = (gather_195_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_149")]; tensor var_3205_cast_fp16 = transpose(perm = var_3205_perm_0, x = x2_36_cast_fp16)[name = tensor("transpose_338")]; tensor input0_243_cast_fp16 = reshape(shape = concat_149, x = var_3205_cast_fp16)[name = tensor("input0_243_cast_fp16")]; tensor encoder_layers_17_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228101440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228625792))), name = tensor("encoder_layers_17_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_160_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_self_attn_linear_out_weight_to_fp16_palettized, x = input0_243_cast_fp16)[name = tensor("linear_160_cast_fp16")]; tensor input0_245_cast_fp16 = add(x = input_251_cast_fp16, y = linear_160_cast_fp16)[name = tensor("input0_245_cast_fp16")]; tensor x_287_axes_0 = const()[name = tensor("x_287_axes_0"), val = tensor([-1])]; tensor encoder_layers_17_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_17_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228625920)))]; tensor encoder_layers_17_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_17_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228628032)))]; tensor x_287_cast_fp16 = layer_norm(axes = x_287_axes_0, beta = encoder_layers_17_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_17_norm_conv_weight_to_fp16, x = input0_245_cast_fp16)[name = tensor("x_287_cast_fp16")]; tensor input_255_perm_0 = const()[name = tensor("input_255_perm_0"), val = tensor([0, 2, 1])]; tensor input0_247_pad_type_0 = const()[name = tensor("input0_247_pad_type_0"), val = tensor("valid")]; tensor input0_247_strides_0 = const()[name = tensor("input0_247_strides_0"), val = tensor([1])]; tensor input0_247_pad_0 = const()[name = tensor("input0_247_pad_0"), val = tensor([0, 0])]; tensor input0_247_dilations_0 = const()[name = tensor("input0_247_dilations_0"), val = tensor([1])]; tensor input0_247_groups_0 = const()[name = tensor("input0_247_groups_0"), val = tensor(1)]; tensor encoder_layers_17_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(228630144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229678784))), name = tensor("encoder_layers_17_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_255_cast_fp16 = transpose(perm = input_255_perm_0, x = x_287_cast_fp16)[name = tensor("transpose_337")]; tensor input0_247_cast_fp16 = conv(dilations = input0_247_dilations_0, groups = input0_247_groups_0, pad = input0_247_pad_0, pad_type = input0_247_pad_type_0, strides = input0_247_strides_0, weight = encoder_layers_17_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_255_cast_fp16)[name = tensor("input0_247_cast_fp16")]; tensor x_289_split_num_splits_0 = const()[name = tensor("x_289_split_num_splits_0"), val = tensor(2)]; tensor x_289_split_axis_0 = const()[name = tensor("x_289_split_axis_0"), val = tensor(1)]; tensor x_289_split_cast_fp16_0, tensor x_289_split_cast_fp16_1 = split(axis = x_289_split_axis_0, num_splits = x_289_split_num_splits_0, x = input0_247_cast_fp16)[name = tensor("x_289_split_cast_fp16")]; tensor x_289_split_1_sigmoid_cast_fp16 = sigmoid(x = x_289_split_cast_fp16_1)[name = tensor("x_289_split_1_sigmoid_cast_fp16")]; tensor x_289_cast_fp16 = mul(x = x_289_split_cast_fp16_0, y = x_289_split_1_sigmoid_cast_fp16)[name = tensor("x_289_cast_fp16")]; tensor input0_249_cast_fp16 = select(a = var_8_to_fp16, b = x_289_cast_fp16, cond = var_457)[name = tensor("input0_249_cast_fp16")]; tensor input0_251_pad_0 = const()[name = tensor("input0_251_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_251_mode_0 = const()[name = tensor("input0_251_mode_0"), val = tensor("constant")]; tensor const_46_to_fp16 = const()[name = tensor("const_46_to_fp16"), val = tensor(0x0p+0)]; tensor input0_251_cast_fp16 = pad(constant_val = const_46_to_fp16, mode = input0_251_mode_0, pad = input0_251_pad_0, x = input0_249_cast_fp16)[name = tensor("input0_251_cast_fp16")]; tensor input1_74_pad_type_0 = const()[name = tensor("input1_74_pad_type_0"), val = tensor("valid")]; tensor input1_74_groups_0 = const()[name = tensor("input1_74_groups_0"), val = tensor(1024)]; tensor input1_74_strides_0 = const()[name = tensor("input1_74_strides_0"), val = tensor([1])]; tensor input1_74_pad_0 = const()[name = tensor("input1_74_pad_0"), val = tensor([0, 0])]; tensor input1_74_dilations_0 = const()[name = tensor("input1_74_dilations_0"), val = tensor([1])]; tensor const_93_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229678912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229683584))), name = tensor("const_93_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_94_to_fp16 = const()[name = tensor("const_94_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229683712)))]; tensor input_257_cast_fp16 = conv(bias = const_94_to_fp16, dilations = input1_74_dilations_0, groups = input1_74_groups_0, pad = input1_74_pad_0, pad_type = input1_74_pad_type_0, strides = input1_74_strides_0, weight = const_93_to_fp16_palettized, x = input0_251_cast_fp16)[name = tensor("input_257_cast_fp16")]; tensor var_3243_cast_fp16 = silu(x = input_257_cast_fp16)[name = tensor("op_3243_cast_fp16")]; tensor x_291_pad_type_0 = const()[name = tensor("x_291_pad_type_0"), val = tensor("valid")]; tensor x_291_strides_0 = const()[name = tensor("x_291_strides_0"), val = tensor([1])]; tensor x_291_pad_0 = const()[name = tensor("x_291_pad_0"), val = tensor([0, 0])]; tensor x_291_dilations_0 = const()[name = tensor("x_291_dilations_0"), val = tensor([1])]; tensor x_291_groups_0 = const()[name = tensor("x_291_groups_0"), val = tensor(1)]; tensor encoder_layers_17_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(229685824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230210176))), name = tensor("encoder_layers_17_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_291_cast_fp16 = conv(dilations = x_291_dilations_0, groups = x_291_groups_0, pad = x_291_pad_0, pad_type = x_291_pad_type_0, strides = x_291_strides_0, weight = encoder_layers_17_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3243_cast_fp16)[name = tensor("x_291_cast_fp16")]; tensor var_3250_perm_0 = const()[name = tensor("op_3250_perm_0"), val = tensor([0, 2, 1])]; tensor var_3250_cast_fp16 = transpose(perm = var_3250_perm_0, x = x_291_cast_fp16)[name = tensor("transpose_336")]; tensor input1_76_cast_fp16 = add(x = input0_245_cast_fp16, y = var_3250_cast_fp16)[name = tensor("input1_76_cast_fp16")]; tensor input0_253_axes_0 = const()[name = tensor("input0_253_axes_0"), val = tensor([-1])]; tensor encoder_layers_17_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_17_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230210304)))]; tensor encoder_layers_17_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_17_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230212416)))]; tensor input0_253_cast_fp16 = layer_norm(axes = input0_253_axes_0, beta = encoder_layers_17_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_17_norm_feed_forward2_weight_to_fp16, x = input1_76_cast_fp16)[name = tensor("input0_253_cast_fp16")]; tensor encoder_layers_17_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(230214528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232311744))), name = tensor("encoder_layers_17_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_161_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_17_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_253_cast_fp16)[name = tensor("linear_161_cast_fp16")]; tensor var_3261_cast_fp16 = silu(x = linear_161_cast_fp16)[name = tensor("op_3261_cast_fp16")]; tensor encoder_layers_17_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(232311872))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234409088))), name = tensor("encoder_layers_17_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_162_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_17_feed_forward2_linear2_weight_to_fp16_palettized, x = var_3261_cast_fp16)[name = tensor("linear_162_cast_fp16")]; tensor var_3266_to_fp16 = const()[name = tensor("op_3266_to_fp16"), val = tensor(0x1p-1)]; tensor var_3267_cast_fp16 = mul(x = linear_162_cast_fp16, y = var_3266_to_fp16)[name = tensor("op_3267_cast_fp16")]; tensor input2_38_cast_fp16 = add(x = input1_76_cast_fp16, y = var_3267_cast_fp16)[name = tensor("input2_38_cast_fp16")]; tensor input0_255_axes_0 = const()[name = tensor("input0_255_axes_0"), val = tensor([-1])]; tensor encoder_layers_17_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_17_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234409216)))]; tensor encoder_layers_17_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_17_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234411328)))]; tensor input0_255_cast_fp16 = layer_norm(axes = input0_255_axes_0, beta = encoder_layers_17_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_17_norm_out_weight_to_fp16, x = input2_38_cast_fp16)[name = tensor("input0_255_cast_fp16")]; tensor input_261_axes_0 = const()[name = tensor("input_261_axes_0"), val = tensor([-1])]; tensor encoder_layers_18_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_18_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234413440)))]; tensor encoder_layers_18_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_18_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234415552)))]; tensor input_261_cast_fp16 = layer_norm(axes = input_261_axes_0, beta = encoder_layers_18_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_18_norm_feed_forward1_weight_to_fp16, x = input0_255_cast_fp16)[name = tensor("input_261_cast_fp16")]; tensor encoder_layers_18_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(234417664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236514880))), name = tensor("encoder_layers_18_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_163_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_18_feed_forward1_linear1_weight_to_fp16_palettized, x = input_261_cast_fp16)[name = tensor("linear_163_cast_fp16")]; tensor var_3290_cast_fp16 = silu(x = linear_163_cast_fp16)[name = tensor("op_3290_cast_fp16")]; tensor encoder_layers_18_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(236515008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238612224))), name = tensor("encoder_layers_18_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_164_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_feed_forward1_linear2_weight_to_fp16_palettized, x = var_3290_cast_fp16)[name = tensor("linear_164_cast_fp16")]; tensor var_3295_to_fp16 = const()[name = tensor("op_3295_to_fp16"), val = tensor(0x1p-1)]; tensor var_3296_cast_fp16 = mul(x = linear_164_cast_fp16, y = var_3295_to_fp16)[name = tensor("op_3296_cast_fp16")]; tensor input_265_cast_fp16 = add(x = input0_255_cast_fp16, y = var_3296_cast_fp16)[name = tensor("input_265_cast_fp16")]; tensor query_38_axes_0 = const()[name = tensor("query_38_axes_0"), val = tensor([-1])]; tensor encoder_layers_18_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_18_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238612352)))]; tensor encoder_layers_18_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_18_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238614464)))]; tensor query_38_cast_fp16 = layer_norm(axes = query_38_axes_0, beta = encoder_layers_18_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_18_norm_self_att_weight_to_fp16, x = input_265_cast_fp16)[name = tensor("query_38_cast_fp16")]; tensor var_3309_shape_cast_fp16 = shape(x = query_38_cast_fp16)[name = tensor("op_3309_shape_cast_fp16")]; tensor gather_196_axis_0 = const()[name = tensor("gather_196_axis_0"), val = tensor(0)]; tensor gather_196_batch_dims_0 = const()[name = tensor("gather_196_batch_dims_0"), val = tensor(0)]; tensor gather_196_validate_indices_0 = const()[name = tensor("gather_196_validate_indices_0"), val = tensor(false)]; tensor var_3309_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3309_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_196_to_uint16 = const()[name = tensor("select_196_to_uint16"), val = tensor(0)]; tensor var_3309_shape_cast_fp16_to_uint16 = cast(dtype = var_3309_shape_cast_fp16_to_uint16_dtype_0, x = var_3309_shape_cast_fp16)[name = tensor("cast_59")]; tensor gather_196_cast_uint16 = gather(axis = gather_196_axis_0, batch_dims = gather_196_batch_dims_0, indices = select_196_to_uint16, validate_indices = gather_196_validate_indices_0, x = var_3309_shape_cast_fp16_to_uint16)[name = tensor("gather_196_cast_uint16")]; tensor gather_196_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_196_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_18_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(238616576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239140928))), name = tensor("encoder_layers_18_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_165_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_self_attn_linear_q_weight_to_fp16_palettized, x = query_38_cast_fp16)[name = tensor("linear_165_cast_fp16")]; tensor concat_150_axis_0 = const()[name = tensor("concat_150_axis_0"), val = tensor(0)]; tensor concat_150_interleave_0 = const()[name = tensor("concat_150_interleave_0"), val = tensor(false)]; tensor gather_196_cast_uint16_to_int32 = cast(dtype = gather_196_cast_uint16_to_int32_dtype_0, x = gather_196_cast_uint16)[name = tensor("cast_58")]; tensor concat_150 = concat(axis = concat_150_axis_0, interleave = concat_150_interleave_0, values = (gather_196_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_150")]; tensor q_38_cast_fp16 = reshape(shape = concat_150, x = linear_165_cast_fp16)[name = tensor("q_38_cast_fp16")]; tensor encoder_layers_18_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239141056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239665408))), name = tensor("encoder_layers_18_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_166_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_self_attn_linear_k_weight_to_fp16_palettized, x = query_38_cast_fp16)[name = tensor("linear_166_cast_fp16")]; tensor k_38_cast_fp16 = reshape(shape = concat_150, x = linear_166_cast_fp16)[name = tensor("k_38_cast_fp16")]; tensor encoder_layers_18_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(239665536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240189888))), name = tensor("encoder_layers_18_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_167_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_self_attn_linear_v_weight_to_fp16_palettized, x = query_38_cast_fp16)[name = tensor("linear_167_cast_fp16")]; tensor v_38_cast_fp16 = reshape(shape = concat_150, x = linear_167_cast_fp16)[name = tensor("v_38_cast_fp16")]; tensor value_38_perm_0 = const()[name = tensor("value_38_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_18_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240190016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240714368))), name = tensor("encoder_layers_18_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_168_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_168_cast_fp16")]; tensor var_3329 = const()[name = tensor("op_3329"), val = tensor([1, -1, 8, 128])]; tensor p_38_cast_fp16 = reshape(shape = var_3329, x = linear_168_cast_fp16)[name = tensor("p_38_cast_fp16")]; tensor encoder_layers_18_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_18_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240714496)))]; tensor var_3332_cast_fp16 = add(x = q_38_cast_fp16, y = encoder_layers_18_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3332_cast_fp16")]; tensor encoder_layers_18_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_18_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240716608)))]; tensor var_3334_cast_fp16 = add(x = q_38_cast_fp16, y = encoder_layers_18_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3334_cast_fp16")]; tensor x_299_transpose_x_0 = const()[name = tensor("x_299_transpose_x_0"), val = tensor(false)]; tensor x_299_transpose_y_0 = const()[name = tensor("x_299_transpose_y_0"), val = tensor(false)]; tensor transpose_264_perm_0 = const()[name = tensor("transpose_264_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_265_perm_0 = const()[name = tensor("transpose_265_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_265 = transpose(perm = transpose_265_perm_0, x = p_38_cast_fp16)[name = tensor("transpose_334")]; tensor transpose_264 = transpose(perm = transpose_264_perm_0, x = var_3334_cast_fp16)[name = tensor("transpose_335")]; tensor x_299_cast_fp16 = matmul(transpose_x = x_299_transpose_x_0, transpose_y = x_299_transpose_y_0, x = transpose_264, y = transpose_265)[name = tensor("x_299_cast_fp16")]; tensor var_3338_shape_cast_fp16 = shape(x = x_299_cast_fp16)[name = tensor("op_3338_shape_cast_fp16")]; tensor gather_198_axis_0 = const()[name = tensor("gather_198_axis_0"), val = tensor(0)]; tensor gather_198_batch_dims_0 = const()[name = tensor("gather_198_batch_dims_0"), val = tensor(0)]; tensor gather_198_validate_indices_0 = const()[name = tensor("gather_198_validate_indices_0"), val = tensor(false)]; tensor var_3338_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3338_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_198_to_uint16 = const()[name = tensor("select_198_to_uint16"), val = tensor(0)]; tensor var_3338_shape_cast_fp16_to_uint16 = cast(dtype = var_3338_shape_cast_fp16_to_uint16_dtype_0, x = var_3338_shape_cast_fp16)[name = tensor("cast_57")]; tensor gather_198_cast_uint16 = gather(axis = gather_198_axis_0, batch_dims = gather_198_batch_dims_0, indices = select_198_to_uint16, validate_indices = gather_198_validate_indices_0, x = var_3338_shape_cast_fp16_to_uint16)[name = tensor("gather_198_cast_uint16")]; tensor gather_198_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_198_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_199 = const()[name = tensor("gather_199"), val = tensor(8)]; tensor gather_200_axis_0 = const()[name = tensor("gather_200_axis_0"), val = tensor(0)]; tensor gather_200_batch_dims_0 = const()[name = tensor("gather_200_batch_dims_0"), val = tensor(0)]; tensor gather_200_validate_indices_0 = const()[name = tensor("gather_200_validate_indices_0"), val = tensor(false)]; tensor select_200_to_uint16 = const()[name = tensor("select_200_to_uint16"), val = tensor(2)]; tensor gather_200_cast_uint16 = gather(axis = gather_200_axis_0, batch_dims = gather_200_batch_dims_0, indices = select_200_to_uint16, validate_indices = gather_200_validate_indices_0, x = var_3338_shape_cast_fp16_to_uint16)[name = tensor("gather_200_cast_uint16")]; tensor gather_200_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_200_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_201_axis_0 = const()[name = tensor("gather_201_axis_0"), val = tensor(0)]; tensor gather_201_batch_dims_0 = const()[name = tensor("gather_201_batch_dims_0"), val = tensor(0)]; tensor gather_201_validate_indices_0 = const()[name = tensor("gather_201_validate_indices_0"), val = tensor(false)]; tensor select_201_to_uint16 = const()[name = tensor("select_201_to_uint16"), val = tensor(3)]; tensor gather_201_cast_uint16 = gather(axis = gather_201_axis_0, batch_dims = gather_201_batch_dims_0, indices = select_201_to_uint16, validate_indices = gather_201_validate_indices_0, x = var_3338_shape_cast_fp16_to_uint16)[name = tensor("gather_201_cast_uint16")]; tensor gather_201_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_201_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_40_pad_0 = const()[name = tensor("x0_40_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_40_mode_0 = const()[name = tensor("x0_40_mode_0"), val = tensor("constant")]; tensor const_47_to_fp16 = const()[name = tensor("const_47_to_fp16"), val = tensor(0x0p+0)]; tensor x0_40_cast_fp16 = pad(constant_val = const_47_to_fp16, mode = x0_40_mode_0, pad = x0_40_pad_0, x = x_299_cast_fp16)[name = tensor("x0_40_cast_fp16")]; tensor concat_153_axis_0 = const()[name = tensor("concat_153_axis_0"), val = tensor(0)]; tensor concat_153_interleave_0 = const()[name = tensor("concat_153_interleave_0"), val = tensor(false)]; tensor gather_198_cast_uint16_to_int32 = cast(dtype = gather_198_cast_uint16_to_int32_dtype_0, x = gather_198_cast_uint16)[name = tensor("cast_55")]; tensor gather_200_cast_uint16_to_int32 = cast(dtype = gather_200_cast_uint16_to_int32_dtype_0, x = gather_200_cast_uint16)[name = tensor("cast_56")]; tensor concat_153 = concat(axis = concat_153_axis_0, interleave = concat_153_interleave_0, values = (gather_198_cast_uint16_to_int32, gather_199, var_21, gather_200_cast_uint16_to_int32))[name = tensor("concat_153")]; tensor x1_38_cast_fp16 = reshape(shape = concat_153, x = x0_40_cast_fp16)[name = tensor("x1_38_cast_fp16")]; tensor var_3348_begin_0 = const()[name = tensor("op_3348_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3348_end_0 = const()[name = tensor("op_3348_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_3348_end_mask_0 = const()[name = tensor("op_3348_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3348_cast_fp16 = slice_by_index(begin = var_3348_begin_0, end = var_3348_end_0, end_mask = var_3348_end_mask_0, x = x1_38_cast_fp16)[name = tensor("op_3348_cast_fp16")]; tensor concat_154_axis_0 = const()[name = tensor("concat_154_axis_0"), val = tensor(0)]; tensor concat_154_interleave_0 = const()[name = tensor("concat_154_interleave_0"), val = tensor(false)]; tensor gather_201_cast_uint16_to_int32 = cast(dtype = gather_201_cast_uint16_to_int32_dtype_0, x = gather_201_cast_uint16)[name = tensor("cast_54")]; tensor concat_154 = concat(axis = concat_154_axis_0, interleave = concat_154_interleave_0, values = (gather_198_cast_uint16_to_int32, gather_199, gather_200_cast_uint16_to_int32, gather_201_cast_uint16_to_int32))[name = tensor("concat_154")]; tensor matrix_bd_38_cast_fp16 = reshape(shape = concat_154, x = var_3348_cast_fp16)[name = tensor("matrix_bd_38_cast_fp16")]; tensor matrix_ac_38_transpose_x_0 = const()[name = tensor("matrix_ac_38_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_38_transpose_y_0 = const()[name = tensor("matrix_ac_38_transpose_y_0"), val = tensor(false)]; tensor transpose_266_perm_0 = const()[name = tensor("transpose_266_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_267_perm_0 = const()[name = tensor("transpose_267_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_267 = transpose(perm = transpose_267_perm_0, x = k_38_cast_fp16)[name = tensor("transpose_332")]; tensor transpose_266 = transpose(perm = transpose_266_perm_0, x = var_3332_cast_fp16)[name = tensor("transpose_333")]; tensor matrix_ac_38_cast_fp16 = matmul(transpose_x = matrix_ac_38_transpose_x_0, transpose_y = matrix_ac_38_transpose_y_0, x = transpose_266, y = transpose_267)[name = tensor("matrix_ac_38_cast_fp16")]; tensor var_3353_shape_cast_fp16 = shape(x = matrix_ac_38_cast_fp16)[name = tensor("op_3353_shape_cast_fp16")]; tensor gather_202_axis_0 = const()[name = tensor("gather_202_axis_0"), val = tensor(0)]; tensor gather_202_batch_dims_0 = const()[name = tensor("gather_202_batch_dims_0"), val = tensor(0)]; tensor gather_202_validate_indices_0 = const()[name = tensor("gather_202_validate_indices_0"), val = tensor(false)]; tensor var_3353_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3353_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_202_to_uint16 = const()[name = tensor("select_202_to_uint16"), val = tensor(3)]; tensor var_3353_shape_cast_fp16_to_uint16 = cast(dtype = var_3353_shape_cast_fp16_to_uint16_dtype_0, x = var_3353_shape_cast_fp16)[name = tensor("cast_53")]; tensor gather_202_cast_uint16 = gather(axis = gather_202_axis_0, batch_dims = gather_202_batch_dims_0, indices = select_202_to_uint16, validate_indices = gather_202_validate_indices_0, x = var_3353_shape_cast_fp16_to_uint16)[name = tensor("gather_202_cast_uint16")]; tensor gather_202_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_202_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_155_values0_0 = const()[name = tensor("concat_155_values0_0"), val = tensor(0)]; tensor concat_155_values1_0 = const()[name = tensor("concat_155_values1_0"), val = tensor(8)]; tensor concat_155_values2_0 = const()[name = tensor("concat_155_values2_0"), val = tensor(0)]; tensor concat_155_axis_0 = const()[name = tensor("concat_155_axis_0"), val = tensor(0)]; tensor concat_155_interleave_0 = const()[name = tensor("concat_155_interleave_0"), val = tensor(false)]; tensor gather_202_cast_uint16_to_int32 = cast(dtype = gather_202_cast_uint16_to_int32_dtype_0, x = gather_202_cast_uint16)[name = tensor("cast_52")]; tensor concat_155 = concat(axis = concat_155_axis_0, interleave = concat_155_interleave_0, values = (concat_155_values0_0, concat_155_values1_0, concat_155_values2_0, gather_202_cast_uint16_to_int32))[name = tensor("concat_155")]; tensor matrix_bd0_38_begin_0 = const()[name = tensor("matrix_bd0_38_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_38_end_mask_0 = const()[name = tensor("matrix_bd0_38_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_38_cast_fp16 = slice_by_index(begin = matrix_bd0_38_begin_0, end = concat_155, end_mask = matrix_bd0_38_end_mask_0, x = matrix_bd_38_cast_fp16)[name = tensor("matrix_bd0_38_cast_fp16")]; tensor var_3358_cast_fp16 = add(x = matrix_ac_38_cast_fp16, y = matrix_bd0_38_cast_fp16)[name = tensor("op_3358_cast_fp16")]; tensor _inversed_scores_38_y_0_to_fp16 = const()[name = tensor("_inversed_scores_38_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_38_cast_fp16 = mul(x = var_3358_cast_fp16, y = _inversed_scores_38_y_0_to_fp16)[name = tensor("_inversed_scores_38_cast_fp16")]; tensor value_38_cast_fp16 = transpose(perm = value_38_perm_0, x = v_38_cast_fp16)[name = tensor("transpose_331")]; tensor var_3361_shape_cast_fp16 = shape(x = value_38_cast_fp16)[name = tensor("op_3361_shape_cast_fp16")]; tensor gather_203_axis_0 = const()[name = tensor("gather_203_axis_0"), val = tensor(0)]; tensor gather_203_batch_dims_0 = const()[name = tensor("gather_203_batch_dims_0"), val = tensor(0)]; tensor gather_203_validate_indices_0 = const()[name = tensor("gather_203_validate_indices_0"), val = tensor(false)]; tensor var_3361_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3361_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_203_to_uint16 = const()[name = tensor("select_203_to_uint16"), val = tensor(0)]; tensor var_3361_shape_cast_fp16_to_uint16 = cast(dtype = var_3361_shape_cast_fp16_to_uint16_dtype_0, x = var_3361_shape_cast_fp16)[name = tensor("cast_51")]; tensor gather_203_cast_uint16 = gather(axis = gather_203_axis_0, batch_dims = gather_203_batch_dims_0, indices = select_203_to_uint16, validate_indices = gather_203_validate_indices_0, x = var_3361_shape_cast_fp16_to_uint16)[name = tensor("gather_203_cast_uint16")]; tensor gather_203_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_203_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_38_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_38_cast_fp16, cond = mask0_4)[name = tensor("scores0_38_cast_fp16")]; tensor var_3364_cast_fp16 = softmax(axis = var_21, x = scores0_38_cast_fp16)[name = tensor("op_3364_cast_fp16")]; tensor input_267_cast_fp16 = select(a = var_8_to_fp16, b = var_3364_cast_fp16, cond = mask0_4)[name = tensor("input_267_cast_fp16")]; tensor x2_38_transpose_x_0 = const()[name = tensor("x2_38_transpose_x_0"), val = tensor(false)]; tensor x2_38_transpose_y_0 = const()[name = tensor("x2_38_transpose_y_0"), val = tensor(false)]; tensor x2_38_cast_fp16 = matmul(transpose_x = x2_38_transpose_x_0, transpose_y = x2_38_transpose_y_0, x = input_267_cast_fp16, y = value_38_cast_fp16)[name = tensor("x2_38_cast_fp16")]; tensor var_3368_perm_0 = const()[name = tensor("op_3368_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_156_axis_0 = const()[name = tensor("concat_156_axis_0"), val = tensor(0)]; tensor concat_156_interleave_0 = const()[name = tensor("concat_156_interleave_0"), val = tensor(false)]; tensor gather_203_cast_uint16_to_int32 = cast(dtype = gather_203_cast_uint16_to_int32_dtype_0, x = gather_203_cast_uint16)[name = tensor("cast_50")]; tensor concat_156 = concat(axis = concat_156_axis_0, interleave = concat_156_interleave_0, values = (gather_203_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_156")]; tensor var_3368_cast_fp16 = transpose(perm = var_3368_perm_0, x = x2_38_cast_fp16)[name = tensor("transpose_330")]; tensor input0_257_cast_fp16 = reshape(shape = concat_156, x = var_3368_cast_fp16)[name = tensor("input0_257_cast_fp16")]; tensor encoder_layers_18_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(240718720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241243072))), name = tensor("encoder_layers_18_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_169_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_self_attn_linear_out_weight_to_fp16_palettized, x = input0_257_cast_fp16)[name = tensor("linear_169_cast_fp16")]; tensor input0_259_cast_fp16 = add(x = input_265_cast_fp16, y = linear_169_cast_fp16)[name = tensor("input0_259_cast_fp16")]; tensor x_303_axes_0 = const()[name = tensor("x_303_axes_0"), val = tensor([-1])]; tensor encoder_layers_18_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_18_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241243200)))]; tensor encoder_layers_18_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_18_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241245312)))]; tensor x_303_cast_fp16 = layer_norm(axes = x_303_axes_0, beta = encoder_layers_18_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_18_norm_conv_weight_to_fp16, x = input0_259_cast_fp16)[name = tensor("x_303_cast_fp16")]; tensor input_269_perm_0 = const()[name = tensor("input_269_perm_0"), val = tensor([0, 2, 1])]; tensor input0_261_pad_type_0 = const()[name = tensor("input0_261_pad_type_0"), val = tensor("valid")]; tensor input0_261_strides_0 = const()[name = tensor("input0_261_strides_0"), val = tensor([1])]; tensor input0_261_pad_0 = const()[name = tensor("input0_261_pad_0"), val = tensor([0, 0])]; tensor input0_261_dilations_0 = const()[name = tensor("input0_261_dilations_0"), val = tensor([1])]; tensor input0_261_groups_0 = const()[name = tensor("input0_261_groups_0"), val = tensor(1)]; tensor encoder_layers_18_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(241247424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242296064))), name = tensor("encoder_layers_18_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_269_cast_fp16 = transpose(perm = input_269_perm_0, x = x_303_cast_fp16)[name = tensor("transpose_329")]; tensor input0_261_cast_fp16 = conv(dilations = input0_261_dilations_0, groups = input0_261_groups_0, pad = input0_261_pad_0, pad_type = input0_261_pad_type_0, strides = input0_261_strides_0, weight = encoder_layers_18_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_269_cast_fp16)[name = tensor("input0_261_cast_fp16")]; tensor x_305_split_num_splits_0 = const()[name = tensor("x_305_split_num_splits_0"), val = tensor(2)]; tensor x_305_split_axis_0 = const()[name = tensor("x_305_split_axis_0"), val = tensor(1)]; tensor x_305_split_cast_fp16_0, tensor x_305_split_cast_fp16_1 = split(axis = x_305_split_axis_0, num_splits = x_305_split_num_splits_0, x = input0_261_cast_fp16)[name = tensor("x_305_split_cast_fp16")]; tensor x_305_split_1_sigmoid_cast_fp16 = sigmoid(x = x_305_split_cast_fp16_1)[name = tensor("x_305_split_1_sigmoid_cast_fp16")]; tensor x_305_cast_fp16 = mul(x = x_305_split_cast_fp16_0, y = x_305_split_1_sigmoid_cast_fp16)[name = tensor("x_305_cast_fp16")]; tensor input0_263_cast_fp16 = select(a = var_8_to_fp16, b = x_305_cast_fp16, cond = var_457)[name = tensor("input0_263_cast_fp16")]; tensor input0_265_pad_0 = const()[name = tensor("input0_265_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_265_mode_0 = const()[name = tensor("input0_265_mode_0"), val = tensor("constant")]; tensor const_48_to_fp16 = const()[name = tensor("const_48_to_fp16"), val = tensor(0x0p+0)]; tensor input0_265_cast_fp16 = pad(constant_val = const_48_to_fp16, mode = input0_265_mode_0, pad = input0_265_pad_0, x = input0_263_cast_fp16)[name = tensor("input0_265_cast_fp16")]; tensor input1_78_pad_type_0 = const()[name = tensor("input1_78_pad_type_0"), val = tensor("valid")]; tensor input1_78_groups_0 = const()[name = tensor("input1_78_groups_0"), val = tensor(1024)]; tensor input1_78_strides_0 = const()[name = tensor("input1_78_strides_0"), val = tensor([1])]; tensor input1_78_pad_0 = const()[name = tensor("input1_78_pad_0"), val = tensor([0, 0])]; tensor input1_78_dilations_0 = const()[name = tensor("input1_78_dilations_0"), val = tensor([1])]; tensor const_95_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242296192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242300864))), name = tensor("const_95_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_96_to_fp16 = const()[name = tensor("const_96_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242300992)))]; tensor input_271_cast_fp16 = conv(bias = const_96_to_fp16, dilations = input1_78_dilations_0, groups = input1_78_groups_0, pad = input1_78_pad_0, pad_type = input1_78_pad_type_0, strides = input1_78_strides_0, weight = const_95_to_fp16_palettized, x = input0_265_cast_fp16)[name = tensor("input_271_cast_fp16")]; tensor var_3406_cast_fp16 = silu(x = input_271_cast_fp16)[name = tensor("op_3406_cast_fp16")]; tensor x_307_pad_type_0 = const()[name = tensor("x_307_pad_type_0"), val = tensor("valid")]; tensor x_307_strides_0 = const()[name = tensor("x_307_strides_0"), val = tensor([1])]; tensor x_307_pad_0 = const()[name = tensor("x_307_pad_0"), val = tensor([0, 0])]; tensor x_307_dilations_0 = const()[name = tensor("x_307_dilations_0"), val = tensor([1])]; tensor x_307_groups_0 = const()[name = tensor("x_307_groups_0"), val = tensor(1)]; tensor encoder_layers_18_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242303104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242827456))), name = tensor("encoder_layers_18_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_307_cast_fp16 = conv(dilations = x_307_dilations_0, groups = x_307_groups_0, pad = x_307_pad_0, pad_type = x_307_pad_type_0, strides = x_307_strides_0, weight = encoder_layers_18_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3406_cast_fp16)[name = tensor("x_307_cast_fp16")]; tensor var_3413_perm_0 = const()[name = tensor("op_3413_perm_0"), val = tensor([0, 2, 1])]; tensor var_3413_cast_fp16 = transpose(perm = var_3413_perm_0, x = x_307_cast_fp16)[name = tensor("transpose_328")]; tensor input1_80_cast_fp16 = add(x = input0_259_cast_fp16, y = var_3413_cast_fp16)[name = tensor("input1_80_cast_fp16")]; tensor input0_267_axes_0 = const()[name = tensor("input0_267_axes_0"), val = tensor([-1])]; tensor encoder_layers_18_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_18_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242827584)))]; tensor encoder_layers_18_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_18_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242829696)))]; tensor input0_267_cast_fp16 = layer_norm(axes = input0_267_axes_0, beta = encoder_layers_18_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_18_norm_feed_forward2_weight_to_fp16, x = input1_80_cast_fp16)[name = tensor("input0_267_cast_fp16")]; tensor encoder_layers_18_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(242831808))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244929024))), name = tensor("encoder_layers_18_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_170_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_18_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_267_cast_fp16)[name = tensor("linear_170_cast_fp16")]; tensor var_3424_cast_fp16 = silu(x = linear_170_cast_fp16)[name = tensor("op_3424_cast_fp16")]; tensor encoder_layers_18_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(244929152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247026368))), name = tensor("encoder_layers_18_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_171_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_18_feed_forward2_linear2_weight_to_fp16_palettized, x = var_3424_cast_fp16)[name = tensor("linear_171_cast_fp16")]; tensor var_3429_to_fp16 = const()[name = tensor("op_3429_to_fp16"), val = tensor(0x1p-1)]; tensor var_3430_cast_fp16 = mul(x = linear_171_cast_fp16, y = var_3429_to_fp16)[name = tensor("op_3430_cast_fp16")]; tensor input2_40_cast_fp16 = add(x = input1_80_cast_fp16, y = var_3430_cast_fp16)[name = tensor("input2_40_cast_fp16")]; tensor input0_269_axes_0 = const()[name = tensor("input0_269_axes_0"), val = tensor([-1])]; tensor encoder_layers_18_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_18_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247026496)))]; tensor encoder_layers_18_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_18_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247028608)))]; tensor input0_269_cast_fp16 = layer_norm(axes = input0_269_axes_0, beta = encoder_layers_18_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_18_norm_out_weight_to_fp16, x = input2_40_cast_fp16)[name = tensor("input0_269_cast_fp16")]; tensor input_275_axes_0 = const()[name = tensor("input_275_axes_0"), val = tensor([-1])]; tensor encoder_layers_19_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_19_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247030720)))]; tensor encoder_layers_19_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_19_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247032832)))]; tensor input_275_cast_fp16 = layer_norm(axes = input_275_axes_0, beta = encoder_layers_19_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_19_norm_feed_forward1_weight_to_fp16, x = input0_269_cast_fp16)[name = tensor("input_275_cast_fp16")]; tensor encoder_layers_19_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(247034944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249132160))), name = tensor("encoder_layers_19_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_172_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_19_feed_forward1_linear1_weight_to_fp16_palettized, x = input_275_cast_fp16)[name = tensor("linear_172_cast_fp16")]; tensor var_3453_cast_fp16 = silu(x = linear_172_cast_fp16)[name = tensor("op_3453_cast_fp16")]; tensor encoder_layers_19_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(249132288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251229504))), name = tensor("encoder_layers_19_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_173_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_feed_forward1_linear2_weight_to_fp16_palettized, x = var_3453_cast_fp16)[name = tensor("linear_173_cast_fp16")]; tensor var_3458_to_fp16 = const()[name = tensor("op_3458_to_fp16"), val = tensor(0x1p-1)]; tensor var_3459_cast_fp16 = mul(x = linear_173_cast_fp16, y = var_3458_to_fp16)[name = tensor("op_3459_cast_fp16")]; tensor input_279_cast_fp16 = add(x = input0_269_cast_fp16, y = var_3459_cast_fp16)[name = tensor("input_279_cast_fp16")]; tensor query_40_axes_0 = const()[name = tensor("query_40_axes_0"), val = tensor([-1])]; tensor encoder_layers_19_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_19_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251229632)))]; tensor encoder_layers_19_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_19_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251231744)))]; tensor query_40_cast_fp16 = layer_norm(axes = query_40_axes_0, beta = encoder_layers_19_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_19_norm_self_att_weight_to_fp16, x = input_279_cast_fp16)[name = tensor("query_40_cast_fp16")]; tensor var_3472_shape_cast_fp16 = shape(x = query_40_cast_fp16)[name = tensor("op_3472_shape_cast_fp16")]; tensor gather_204_axis_0 = const()[name = tensor("gather_204_axis_0"), val = tensor(0)]; tensor gather_204_batch_dims_0 = const()[name = tensor("gather_204_batch_dims_0"), val = tensor(0)]; tensor gather_204_validate_indices_0 = const()[name = tensor("gather_204_validate_indices_0"), val = tensor(false)]; tensor var_3472_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3472_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_204_to_uint16 = const()[name = tensor("select_204_to_uint16"), val = tensor(0)]; tensor var_3472_shape_cast_fp16_to_uint16 = cast(dtype = var_3472_shape_cast_fp16_to_uint16_dtype_0, x = var_3472_shape_cast_fp16)[name = tensor("cast_49")]; tensor gather_204_cast_uint16 = gather(axis = gather_204_axis_0, batch_dims = gather_204_batch_dims_0, indices = select_204_to_uint16, validate_indices = gather_204_validate_indices_0, x = var_3472_shape_cast_fp16_to_uint16)[name = tensor("gather_204_cast_uint16")]; tensor gather_204_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_204_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_19_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251233856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251758208))), name = tensor("encoder_layers_19_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_174_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_self_attn_linear_q_weight_to_fp16_palettized, x = query_40_cast_fp16)[name = tensor("linear_174_cast_fp16")]; tensor concat_157_axis_0 = const()[name = tensor("concat_157_axis_0"), val = tensor(0)]; tensor concat_157_interleave_0 = const()[name = tensor("concat_157_interleave_0"), val = tensor(false)]; tensor gather_204_cast_uint16_to_int32 = cast(dtype = gather_204_cast_uint16_to_int32_dtype_0, x = gather_204_cast_uint16)[name = tensor("cast_48")]; tensor concat_157 = concat(axis = concat_157_axis_0, interleave = concat_157_interleave_0, values = (gather_204_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_157")]; tensor q_40_cast_fp16 = reshape(shape = concat_157, x = linear_174_cast_fp16)[name = tensor("q_40_cast_fp16")]; tensor encoder_layers_19_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(251758336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252282688))), name = tensor("encoder_layers_19_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_175_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_self_attn_linear_k_weight_to_fp16_palettized, x = query_40_cast_fp16)[name = tensor("linear_175_cast_fp16")]; tensor k_40_cast_fp16 = reshape(shape = concat_157, x = linear_175_cast_fp16)[name = tensor("k_40_cast_fp16")]; tensor encoder_layers_19_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252282816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252807168))), name = tensor("encoder_layers_19_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_176_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_self_attn_linear_v_weight_to_fp16_palettized, x = query_40_cast_fp16)[name = tensor("linear_176_cast_fp16")]; tensor v_40_cast_fp16 = reshape(shape = concat_157, x = linear_176_cast_fp16)[name = tensor("v_40_cast_fp16")]; tensor value_40_perm_0 = const()[name = tensor("value_40_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_19_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(252807296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253331648))), name = tensor("encoder_layers_19_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_177_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_177_cast_fp16")]; tensor var_3492 = const()[name = tensor("op_3492"), val = tensor([1, -1, 8, 128])]; tensor p_40_cast_fp16 = reshape(shape = var_3492, x = linear_177_cast_fp16)[name = tensor("p_40_cast_fp16")]; tensor encoder_layers_19_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_19_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253331776)))]; tensor var_3495_cast_fp16 = add(x = q_40_cast_fp16, y = encoder_layers_19_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3495_cast_fp16")]; tensor encoder_layers_19_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_19_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253333888)))]; tensor var_3497_cast_fp16 = add(x = q_40_cast_fp16, y = encoder_layers_19_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3497_cast_fp16")]; tensor x_315_transpose_x_0 = const()[name = tensor("x_315_transpose_x_0"), val = tensor(false)]; tensor x_315_transpose_y_0 = const()[name = tensor("x_315_transpose_y_0"), val = tensor(false)]; tensor transpose_268_perm_0 = const()[name = tensor("transpose_268_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_269_perm_0 = const()[name = tensor("transpose_269_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_269 = transpose(perm = transpose_269_perm_0, x = p_40_cast_fp16)[name = tensor("transpose_326")]; tensor transpose_268 = transpose(perm = transpose_268_perm_0, x = var_3497_cast_fp16)[name = tensor("transpose_327")]; tensor x_315_cast_fp16 = matmul(transpose_x = x_315_transpose_x_0, transpose_y = x_315_transpose_y_0, x = transpose_268, y = transpose_269)[name = tensor("x_315_cast_fp16")]; tensor var_3501_shape_cast_fp16 = shape(x = x_315_cast_fp16)[name = tensor("op_3501_shape_cast_fp16")]; tensor gather_206_axis_0 = const()[name = tensor("gather_206_axis_0"), val = tensor(0)]; tensor gather_206_batch_dims_0 = const()[name = tensor("gather_206_batch_dims_0"), val = tensor(0)]; tensor gather_206_validate_indices_0 = const()[name = tensor("gather_206_validate_indices_0"), val = tensor(false)]; tensor var_3501_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3501_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_206_to_uint16 = const()[name = tensor("select_206_to_uint16"), val = tensor(0)]; tensor var_3501_shape_cast_fp16_to_uint16 = cast(dtype = var_3501_shape_cast_fp16_to_uint16_dtype_0, x = var_3501_shape_cast_fp16)[name = tensor("cast_47")]; tensor gather_206_cast_uint16 = gather(axis = gather_206_axis_0, batch_dims = gather_206_batch_dims_0, indices = select_206_to_uint16, validate_indices = gather_206_validate_indices_0, x = var_3501_shape_cast_fp16_to_uint16)[name = tensor("gather_206_cast_uint16")]; tensor gather_206_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_206_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_207 = const()[name = tensor("gather_207"), val = tensor(8)]; tensor gather_208_axis_0 = const()[name = tensor("gather_208_axis_0"), val = tensor(0)]; tensor gather_208_batch_dims_0 = const()[name = tensor("gather_208_batch_dims_0"), val = tensor(0)]; tensor gather_208_validate_indices_0 = const()[name = tensor("gather_208_validate_indices_0"), val = tensor(false)]; tensor select_208_to_uint16 = const()[name = tensor("select_208_to_uint16"), val = tensor(2)]; tensor gather_208_cast_uint16 = gather(axis = gather_208_axis_0, batch_dims = gather_208_batch_dims_0, indices = select_208_to_uint16, validate_indices = gather_208_validate_indices_0, x = var_3501_shape_cast_fp16_to_uint16)[name = tensor("gather_208_cast_uint16")]; tensor gather_208_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_208_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_209_axis_0 = const()[name = tensor("gather_209_axis_0"), val = tensor(0)]; tensor gather_209_batch_dims_0 = const()[name = tensor("gather_209_batch_dims_0"), val = tensor(0)]; tensor gather_209_validate_indices_0 = const()[name = tensor("gather_209_validate_indices_0"), val = tensor(false)]; tensor select_209_to_uint16 = const()[name = tensor("select_209_to_uint16"), val = tensor(3)]; tensor gather_209_cast_uint16 = gather(axis = gather_209_axis_0, batch_dims = gather_209_batch_dims_0, indices = select_209_to_uint16, validate_indices = gather_209_validate_indices_0, x = var_3501_shape_cast_fp16_to_uint16)[name = tensor("gather_209_cast_uint16")]; tensor gather_209_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_209_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_42_pad_0 = const()[name = tensor("x0_42_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_42_mode_0 = const()[name = tensor("x0_42_mode_0"), val = tensor("constant")]; tensor const_49_to_fp16 = const()[name = tensor("const_49_to_fp16"), val = tensor(0x0p+0)]; tensor x0_42_cast_fp16 = pad(constant_val = const_49_to_fp16, mode = x0_42_mode_0, pad = x0_42_pad_0, x = x_315_cast_fp16)[name = tensor("x0_42_cast_fp16")]; tensor concat_160_axis_0 = const()[name = tensor("concat_160_axis_0"), val = tensor(0)]; tensor concat_160_interleave_0 = const()[name = tensor("concat_160_interleave_0"), val = tensor(false)]; tensor gather_206_cast_uint16_to_int32 = cast(dtype = gather_206_cast_uint16_to_int32_dtype_0, x = gather_206_cast_uint16)[name = tensor("cast_45")]; tensor gather_208_cast_uint16_to_int32 = cast(dtype = gather_208_cast_uint16_to_int32_dtype_0, x = gather_208_cast_uint16)[name = tensor("cast_46")]; tensor concat_160 = concat(axis = concat_160_axis_0, interleave = concat_160_interleave_0, values = (gather_206_cast_uint16_to_int32, gather_207, var_21, gather_208_cast_uint16_to_int32))[name = tensor("concat_160")]; tensor x1_40_cast_fp16 = reshape(shape = concat_160, x = x0_42_cast_fp16)[name = tensor("x1_40_cast_fp16")]; tensor var_3511_begin_0 = const()[name = tensor("op_3511_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3511_end_0 = const()[name = tensor("op_3511_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_3511_end_mask_0 = const()[name = tensor("op_3511_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3511_cast_fp16 = slice_by_index(begin = var_3511_begin_0, end = var_3511_end_0, end_mask = var_3511_end_mask_0, x = x1_40_cast_fp16)[name = tensor("op_3511_cast_fp16")]; tensor concat_161_axis_0 = const()[name = tensor("concat_161_axis_0"), val = tensor(0)]; tensor concat_161_interleave_0 = const()[name = tensor("concat_161_interleave_0"), val = tensor(false)]; tensor gather_209_cast_uint16_to_int32 = cast(dtype = gather_209_cast_uint16_to_int32_dtype_0, x = gather_209_cast_uint16)[name = tensor("cast_44")]; tensor concat_161 = concat(axis = concat_161_axis_0, interleave = concat_161_interleave_0, values = (gather_206_cast_uint16_to_int32, gather_207, gather_208_cast_uint16_to_int32, gather_209_cast_uint16_to_int32))[name = tensor("concat_161")]; tensor matrix_bd_40_cast_fp16 = reshape(shape = concat_161, x = var_3511_cast_fp16)[name = tensor("matrix_bd_40_cast_fp16")]; tensor matrix_ac_40_transpose_x_0 = const()[name = tensor("matrix_ac_40_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_40_transpose_y_0 = const()[name = tensor("matrix_ac_40_transpose_y_0"), val = tensor(false)]; tensor transpose_270_perm_0 = const()[name = tensor("transpose_270_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_271_perm_0 = const()[name = tensor("transpose_271_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_271 = transpose(perm = transpose_271_perm_0, x = k_40_cast_fp16)[name = tensor("transpose_324")]; tensor transpose_270 = transpose(perm = transpose_270_perm_0, x = var_3495_cast_fp16)[name = tensor("transpose_325")]; tensor matrix_ac_40_cast_fp16 = matmul(transpose_x = matrix_ac_40_transpose_x_0, transpose_y = matrix_ac_40_transpose_y_0, x = transpose_270, y = transpose_271)[name = tensor("matrix_ac_40_cast_fp16")]; tensor var_3516_shape_cast_fp16 = shape(x = matrix_ac_40_cast_fp16)[name = tensor("op_3516_shape_cast_fp16")]; tensor gather_210_axis_0 = const()[name = tensor("gather_210_axis_0"), val = tensor(0)]; tensor gather_210_batch_dims_0 = const()[name = tensor("gather_210_batch_dims_0"), val = tensor(0)]; tensor gather_210_validate_indices_0 = const()[name = tensor("gather_210_validate_indices_0"), val = tensor(false)]; tensor var_3516_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3516_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_210_to_uint16 = const()[name = tensor("select_210_to_uint16"), val = tensor(3)]; tensor var_3516_shape_cast_fp16_to_uint16 = cast(dtype = var_3516_shape_cast_fp16_to_uint16_dtype_0, x = var_3516_shape_cast_fp16)[name = tensor("cast_43")]; tensor gather_210_cast_uint16 = gather(axis = gather_210_axis_0, batch_dims = gather_210_batch_dims_0, indices = select_210_to_uint16, validate_indices = gather_210_validate_indices_0, x = var_3516_shape_cast_fp16_to_uint16)[name = tensor("gather_210_cast_uint16")]; tensor gather_210_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_210_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_162_values0_0 = const()[name = tensor("concat_162_values0_0"), val = tensor(0)]; tensor concat_162_values1_0 = const()[name = tensor("concat_162_values1_0"), val = tensor(8)]; tensor concat_162_values2_0 = const()[name = tensor("concat_162_values2_0"), val = tensor(0)]; tensor concat_162_axis_0 = const()[name = tensor("concat_162_axis_0"), val = tensor(0)]; tensor concat_162_interleave_0 = const()[name = tensor("concat_162_interleave_0"), val = tensor(false)]; tensor gather_210_cast_uint16_to_int32 = cast(dtype = gather_210_cast_uint16_to_int32_dtype_0, x = gather_210_cast_uint16)[name = tensor("cast_42")]; tensor concat_162 = concat(axis = concat_162_axis_0, interleave = concat_162_interleave_0, values = (concat_162_values0_0, concat_162_values1_0, concat_162_values2_0, gather_210_cast_uint16_to_int32))[name = tensor("concat_162")]; tensor matrix_bd0_40_begin_0 = const()[name = tensor("matrix_bd0_40_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_40_end_mask_0 = const()[name = tensor("matrix_bd0_40_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_40_cast_fp16 = slice_by_index(begin = matrix_bd0_40_begin_0, end = concat_162, end_mask = matrix_bd0_40_end_mask_0, x = matrix_bd_40_cast_fp16)[name = tensor("matrix_bd0_40_cast_fp16")]; tensor var_3521_cast_fp16 = add(x = matrix_ac_40_cast_fp16, y = matrix_bd0_40_cast_fp16)[name = tensor("op_3521_cast_fp16")]; tensor _inversed_scores_40_y_0_to_fp16 = const()[name = tensor("_inversed_scores_40_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_40_cast_fp16 = mul(x = var_3521_cast_fp16, y = _inversed_scores_40_y_0_to_fp16)[name = tensor("_inversed_scores_40_cast_fp16")]; tensor value_40_cast_fp16 = transpose(perm = value_40_perm_0, x = v_40_cast_fp16)[name = tensor("transpose_323")]; tensor var_3524_shape_cast_fp16 = shape(x = value_40_cast_fp16)[name = tensor("op_3524_shape_cast_fp16")]; tensor gather_211_axis_0 = const()[name = tensor("gather_211_axis_0"), val = tensor(0)]; tensor gather_211_batch_dims_0 = const()[name = tensor("gather_211_batch_dims_0"), val = tensor(0)]; tensor gather_211_validate_indices_0 = const()[name = tensor("gather_211_validate_indices_0"), val = tensor(false)]; tensor var_3524_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3524_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_211_to_uint16 = const()[name = tensor("select_211_to_uint16"), val = tensor(0)]; tensor var_3524_shape_cast_fp16_to_uint16 = cast(dtype = var_3524_shape_cast_fp16_to_uint16_dtype_0, x = var_3524_shape_cast_fp16)[name = tensor("cast_41")]; tensor gather_211_cast_uint16 = gather(axis = gather_211_axis_0, batch_dims = gather_211_batch_dims_0, indices = select_211_to_uint16, validate_indices = gather_211_validate_indices_0, x = var_3524_shape_cast_fp16_to_uint16)[name = tensor("gather_211_cast_uint16")]; tensor gather_211_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_211_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_40_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_40_cast_fp16, cond = mask0_4)[name = tensor("scores0_40_cast_fp16")]; tensor var_3527_cast_fp16 = softmax(axis = var_21, x = scores0_40_cast_fp16)[name = tensor("op_3527_cast_fp16")]; tensor input_281_cast_fp16 = select(a = var_8_to_fp16, b = var_3527_cast_fp16, cond = mask0_4)[name = tensor("input_281_cast_fp16")]; tensor x2_40_transpose_x_0 = const()[name = tensor("x2_40_transpose_x_0"), val = tensor(false)]; tensor x2_40_transpose_y_0 = const()[name = tensor("x2_40_transpose_y_0"), val = tensor(false)]; tensor x2_40_cast_fp16 = matmul(transpose_x = x2_40_transpose_x_0, transpose_y = x2_40_transpose_y_0, x = input_281_cast_fp16, y = value_40_cast_fp16)[name = tensor("x2_40_cast_fp16")]; tensor var_3531_perm_0 = const()[name = tensor("op_3531_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_163_axis_0 = const()[name = tensor("concat_163_axis_0"), val = tensor(0)]; tensor concat_163_interleave_0 = const()[name = tensor("concat_163_interleave_0"), val = tensor(false)]; tensor gather_211_cast_uint16_to_int32 = cast(dtype = gather_211_cast_uint16_to_int32_dtype_0, x = gather_211_cast_uint16)[name = tensor("cast_40")]; tensor concat_163 = concat(axis = concat_163_axis_0, interleave = concat_163_interleave_0, values = (gather_211_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_163")]; tensor var_3531_cast_fp16 = transpose(perm = var_3531_perm_0, x = x2_40_cast_fp16)[name = tensor("transpose_322")]; tensor input0_271_cast_fp16 = reshape(shape = concat_163, x = var_3531_cast_fp16)[name = tensor("input0_271_cast_fp16")]; tensor encoder_layers_19_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253336000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253860352))), name = tensor("encoder_layers_19_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_178_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_self_attn_linear_out_weight_to_fp16_palettized, x = input0_271_cast_fp16)[name = tensor("linear_178_cast_fp16")]; tensor input0_273_cast_fp16 = add(x = input_279_cast_fp16, y = linear_178_cast_fp16)[name = tensor("input0_273_cast_fp16")]; tensor x_319_axes_0 = const()[name = tensor("x_319_axes_0"), val = tensor([-1])]; tensor encoder_layers_19_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_19_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253860480)))]; tensor encoder_layers_19_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_19_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253862592)))]; tensor x_319_cast_fp16 = layer_norm(axes = x_319_axes_0, beta = encoder_layers_19_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_19_norm_conv_weight_to_fp16, x = input0_273_cast_fp16)[name = tensor("x_319_cast_fp16")]; tensor input_283_perm_0 = const()[name = tensor("input_283_perm_0"), val = tensor([0, 2, 1])]; tensor input0_275_pad_type_0 = const()[name = tensor("input0_275_pad_type_0"), val = tensor("valid")]; tensor input0_275_strides_0 = const()[name = tensor("input0_275_strides_0"), val = tensor([1])]; tensor input0_275_pad_0 = const()[name = tensor("input0_275_pad_0"), val = tensor([0, 0])]; tensor input0_275_dilations_0 = const()[name = tensor("input0_275_dilations_0"), val = tensor([1])]; tensor input0_275_groups_0 = const()[name = tensor("input0_275_groups_0"), val = tensor(1)]; tensor encoder_layers_19_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(253864704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254913344))), name = tensor("encoder_layers_19_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_283_cast_fp16 = transpose(perm = input_283_perm_0, x = x_319_cast_fp16)[name = tensor("transpose_321")]; tensor input0_275_cast_fp16 = conv(dilations = input0_275_dilations_0, groups = input0_275_groups_0, pad = input0_275_pad_0, pad_type = input0_275_pad_type_0, strides = input0_275_strides_0, weight = encoder_layers_19_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_283_cast_fp16)[name = tensor("input0_275_cast_fp16")]; tensor x_321_split_num_splits_0 = const()[name = tensor("x_321_split_num_splits_0"), val = tensor(2)]; tensor x_321_split_axis_0 = const()[name = tensor("x_321_split_axis_0"), val = tensor(1)]; tensor x_321_split_cast_fp16_0, tensor x_321_split_cast_fp16_1 = split(axis = x_321_split_axis_0, num_splits = x_321_split_num_splits_0, x = input0_275_cast_fp16)[name = tensor("x_321_split_cast_fp16")]; tensor x_321_split_1_sigmoid_cast_fp16 = sigmoid(x = x_321_split_cast_fp16_1)[name = tensor("x_321_split_1_sigmoid_cast_fp16")]; tensor x_321_cast_fp16 = mul(x = x_321_split_cast_fp16_0, y = x_321_split_1_sigmoid_cast_fp16)[name = tensor("x_321_cast_fp16")]; tensor input0_277_cast_fp16 = select(a = var_8_to_fp16, b = x_321_cast_fp16, cond = var_457)[name = tensor("input0_277_cast_fp16")]; tensor input0_279_pad_0 = const()[name = tensor("input0_279_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_279_mode_0 = const()[name = tensor("input0_279_mode_0"), val = tensor("constant")]; tensor const_50_to_fp16 = const()[name = tensor("const_50_to_fp16"), val = tensor(0x0p+0)]; tensor input0_279_cast_fp16 = pad(constant_val = const_50_to_fp16, mode = input0_279_mode_0, pad = input0_279_pad_0, x = input0_277_cast_fp16)[name = tensor("input0_279_cast_fp16")]; tensor input1_82_pad_type_0 = const()[name = tensor("input1_82_pad_type_0"), val = tensor("valid")]; tensor input1_82_groups_0 = const()[name = tensor("input1_82_groups_0"), val = tensor(1024)]; tensor input1_82_strides_0 = const()[name = tensor("input1_82_strides_0"), val = tensor([1])]; tensor input1_82_pad_0 = const()[name = tensor("input1_82_pad_0"), val = tensor([0, 0])]; tensor input1_82_dilations_0 = const()[name = tensor("input1_82_dilations_0"), val = tensor([1])]; tensor const_97_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254913472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254918144))), name = tensor("const_97_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_98_to_fp16 = const()[name = tensor("const_98_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254918272)))]; tensor input_285_cast_fp16 = conv(bias = const_98_to_fp16, dilations = input1_82_dilations_0, groups = input1_82_groups_0, pad = input1_82_pad_0, pad_type = input1_82_pad_type_0, strides = input1_82_strides_0, weight = const_97_to_fp16_palettized, x = input0_279_cast_fp16)[name = tensor("input_285_cast_fp16")]; tensor var_3569_cast_fp16 = silu(x = input_285_cast_fp16)[name = tensor("op_3569_cast_fp16")]; tensor x_323_pad_type_0 = const()[name = tensor("x_323_pad_type_0"), val = tensor("valid")]; tensor x_323_strides_0 = const()[name = tensor("x_323_strides_0"), val = tensor([1])]; tensor x_323_pad_0 = const()[name = tensor("x_323_pad_0"), val = tensor([0, 0])]; tensor x_323_dilations_0 = const()[name = tensor("x_323_dilations_0"), val = tensor([1])]; tensor x_323_groups_0 = const()[name = tensor("x_323_groups_0"), val = tensor(1)]; tensor encoder_layers_19_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(254920384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255444736))), name = tensor("encoder_layers_19_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_323_cast_fp16 = conv(dilations = x_323_dilations_0, groups = x_323_groups_0, pad = x_323_pad_0, pad_type = x_323_pad_type_0, strides = x_323_strides_0, weight = encoder_layers_19_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3569_cast_fp16)[name = tensor("x_323_cast_fp16")]; tensor var_3576_perm_0 = const()[name = tensor("op_3576_perm_0"), val = tensor([0, 2, 1])]; tensor var_3576_cast_fp16 = transpose(perm = var_3576_perm_0, x = x_323_cast_fp16)[name = tensor("transpose_320")]; tensor input1_84_cast_fp16 = add(x = input0_273_cast_fp16, y = var_3576_cast_fp16)[name = tensor("input1_84_cast_fp16")]; tensor input0_281_axes_0 = const()[name = tensor("input0_281_axes_0"), val = tensor([-1])]; tensor encoder_layers_19_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_19_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255444864)))]; tensor encoder_layers_19_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_19_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255446976)))]; tensor input0_281_cast_fp16 = layer_norm(axes = input0_281_axes_0, beta = encoder_layers_19_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_19_norm_feed_forward2_weight_to_fp16, x = input1_84_cast_fp16)[name = tensor("input0_281_cast_fp16")]; tensor encoder_layers_19_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(255449088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257546304))), name = tensor("encoder_layers_19_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_179_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_19_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_281_cast_fp16)[name = tensor("linear_179_cast_fp16")]; tensor var_3587_cast_fp16 = silu(x = linear_179_cast_fp16)[name = tensor("op_3587_cast_fp16")]; tensor encoder_layers_19_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(257546432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259643648))), name = tensor("encoder_layers_19_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_180_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_19_feed_forward2_linear2_weight_to_fp16_palettized, x = var_3587_cast_fp16)[name = tensor("linear_180_cast_fp16")]; tensor var_3592_to_fp16 = const()[name = tensor("op_3592_to_fp16"), val = tensor(0x1p-1)]; tensor var_3593_cast_fp16 = mul(x = linear_180_cast_fp16, y = var_3592_to_fp16)[name = tensor("op_3593_cast_fp16")]; tensor input2_42_cast_fp16 = add(x = input1_84_cast_fp16, y = var_3593_cast_fp16)[name = tensor("input2_42_cast_fp16")]; tensor input0_283_axes_0 = const()[name = tensor("input0_283_axes_0"), val = tensor([-1])]; tensor encoder_layers_19_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_19_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259643776)))]; tensor encoder_layers_19_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_19_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259645888)))]; tensor input0_283_cast_fp16 = layer_norm(axes = input0_283_axes_0, beta = encoder_layers_19_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_19_norm_out_weight_to_fp16, x = input2_42_cast_fp16)[name = tensor("input0_283_cast_fp16")]; tensor input_289_axes_0 = const()[name = tensor("input_289_axes_0"), val = tensor([-1])]; tensor encoder_layers_20_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_20_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259648000)))]; tensor encoder_layers_20_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_20_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259650112)))]; tensor input_289_cast_fp16 = layer_norm(axes = input_289_axes_0, beta = encoder_layers_20_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_20_norm_feed_forward1_weight_to_fp16, x = input0_283_cast_fp16)[name = tensor("input_289_cast_fp16")]; tensor encoder_layers_20_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(259652224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261749440))), name = tensor("encoder_layers_20_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_181_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_20_feed_forward1_linear1_weight_to_fp16_palettized, x = input_289_cast_fp16)[name = tensor("linear_181_cast_fp16")]; tensor var_3616_cast_fp16 = silu(x = linear_181_cast_fp16)[name = tensor("op_3616_cast_fp16")]; tensor encoder_layers_20_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(261749568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263846784))), name = tensor("encoder_layers_20_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_182_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_feed_forward1_linear2_weight_to_fp16_palettized, x = var_3616_cast_fp16)[name = tensor("linear_182_cast_fp16")]; tensor var_3621_to_fp16 = const()[name = tensor("op_3621_to_fp16"), val = tensor(0x1p-1)]; tensor var_3622_cast_fp16 = mul(x = linear_182_cast_fp16, y = var_3621_to_fp16)[name = tensor("op_3622_cast_fp16")]; tensor input_293_cast_fp16 = add(x = input0_283_cast_fp16, y = var_3622_cast_fp16)[name = tensor("input_293_cast_fp16")]; tensor query_42_axes_0 = const()[name = tensor("query_42_axes_0"), val = tensor([-1])]; tensor encoder_layers_20_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_20_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263846912)))]; tensor encoder_layers_20_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_20_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263849024)))]; tensor query_42_cast_fp16 = layer_norm(axes = query_42_axes_0, beta = encoder_layers_20_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_20_norm_self_att_weight_to_fp16, x = input_293_cast_fp16)[name = tensor("query_42_cast_fp16")]; tensor var_3635_shape_cast_fp16 = shape(x = query_42_cast_fp16)[name = tensor("op_3635_shape_cast_fp16")]; tensor gather_212_axis_0 = const()[name = tensor("gather_212_axis_0"), val = tensor(0)]; tensor gather_212_batch_dims_0 = const()[name = tensor("gather_212_batch_dims_0"), val = tensor(0)]; tensor gather_212_validate_indices_0 = const()[name = tensor("gather_212_validate_indices_0"), val = tensor(false)]; tensor var_3635_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3635_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_212_to_uint16 = const()[name = tensor("select_212_to_uint16"), val = tensor(0)]; tensor var_3635_shape_cast_fp16_to_uint16 = cast(dtype = var_3635_shape_cast_fp16_to_uint16_dtype_0, x = var_3635_shape_cast_fp16)[name = tensor("cast_39")]; tensor gather_212_cast_uint16 = gather(axis = gather_212_axis_0, batch_dims = gather_212_batch_dims_0, indices = select_212_to_uint16, validate_indices = gather_212_validate_indices_0, x = var_3635_shape_cast_fp16_to_uint16)[name = tensor("gather_212_cast_uint16")]; tensor gather_212_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_212_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_20_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(263851136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264375488))), name = tensor("encoder_layers_20_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_183_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_self_attn_linear_q_weight_to_fp16_palettized, x = query_42_cast_fp16)[name = tensor("linear_183_cast_fp16")]; tensor concat_164_axis_0 = const()[name = tensor("concat_164_axis_0"), val = tensor(0)]; tensor concat_164_interleave_0 = const()[name = tensor("concat_164_interleave_0"), val = tensor(false)]; tensor gather_212_cast_uint16_to_int32 = cast(dtype = gather_212_cast_uint16_to_int32_dtype_0, x = gather_212_cast_uint16)[name = tensor("cast_38")]; tensor concat_164 = concat(axis = concat_164_axis_0, interleave = concat_164_interleave_0, values = (gather_212_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_164")]; tensor q_42_cast_fp16 = reshape(shape = concat_164, x = linear_183_cast_fp16)[name = tensor("q_42_cast_fp16")]; tensor encoder_layers_20_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264375616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264899968))), name = tensor("encoder_layers_20_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_184_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_self_attn_linear_k_weight_to_fp16_palettized, x = query_42_cast_fp16)[name = tensor("linear_184_cast_fp16")]; tensor k_42_cast_fp16 = reshape(shape = concat_164, x = linear_184_cast_fp16)[name = tensor("k_42_cast_fp16")]; tensor encoder_layers_20_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(264900096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265424448))), name = tensor("encoder_layers_20_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_185_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_self_attn_linear_v_weight_to_fp16_palettized, x = query_42_cast_fp16)[name = tensor("linear_185_cast_fp16")]; tensor v_42_cast_fp16 = reshape(shape = concat_164, x = linear_185_cast_fp16)[name = tensor("v_42_cast_fp16")]; tensor value_42_perm_0 = const()[name = tensor("value_42_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_20_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265424576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265948928))), name = tensor("encoder_layers_20_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_186_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_186_cast_fp16")]; tensor var_3655 = const()[name = tensor("op_3655"), val = tensor([1, -1, 8, 128])]; tensor p_42_cast_fp16 = reshape(shape = var_3655, x = linear_186_cast_fp16)[name = tensor("p_42_cast_fp16")]; tensor encoder_layers_20_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_20_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265949056)))]; tensor var_3658_cast_fp16 = add(x = q_42_cast_fp16, y = encoder_layers_20_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3658_cast_fp16")]; tensor encoder_layers_20_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_20_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265951168)))]; tensor var_3660_cast_fp16 = add(x = q_42_cast_fp16, y = encoder_layers_20_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3660_cast_fp16")]; tensor x_331_transpose_x_0 = const()[name = tensor("x_331_transpose_x_0"), val = tensor(false)]; tensor x_331_transpose_y_0 = const()[name = tensor("x_331_transpose_y_0"), val = tensor(false)]; tensor transpose_272_perm_0 = const()[name = tensor("transpose_272_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_273_perm_0 = const()[name = tensor("transpose_273_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_273 = transpose(perm = transpose_273_perm_0, x = p_42_cast_fp16)[name = tensor("transpose_318")]; tensor transpose_272 = transpose(perm = transpose_272_perm_0, x = var_3660_cast_fp16)[name = tensor("transpose_319")]; tensor x_331_cast_fp16 = matmul(transpose_x = x_331_transpose_x_0, transpose_y = x_331_transpose_y_0, x = transpose_272, y = transpose_273)[name = tensor("x_331_cast_fp16")]; tensor var_3664_shape_cast_fp16 = shape(x = x_331_cast_fp16)[name = tensor("op_3664_shape_cast_fp16")]; tensor gather_214_axis_0 = const()[name = tensor("gather_214_axis_0"), val = tensor(0)]; tensor gather_214_batch_dims_0 = const()[name = tensor("gather_214_batch_dims_0"), val = tensor(0)]; tensor gather_214_validate_indices_0 = const()[name = tensor("gather_214_validate_indices_0"), val = tensor(false)]; tensor var_3664_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3664_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_214_to_uint16 = const()[name = tensor("select_214_to_uint16"), val = tensor(0)]; tensor var_3664_shape_cast_fp16_to_uint16 = cast(dtype = var_3664_shape_cast_fp16_to_uint16_dtype_0, x = var_3664_shape_cast_fp16)[name = tensor("cast_37")]; tensor gather_214_cast_uint16 = gather(axis = gather_214_axis_0, batch_dims = gather_214_batch_dims_0, indices = select_214_to_uint16, validate_indices = gather_214_validate_indices_0, x = var_3664_shape_cast_fp16_to_uint16)[name = tensor("gather_214_cast_uint16")]; tensor gather_214_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_214_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_215 = const()[name = tensor("gather_215"), val = tensor(8)]; tensor gather_216_axis_0 = const()[name = tensor("gather_216_axis_0"), val = tensor(0)]; tensor gather_216_batch_dims_0 = const()[name = tensor("gather_216_batch_dims_0"), val = tensor(0)]; tensor gather_216_validate_indices_0 = const()[name = tensor("gather_216_validate_indices_0"), val = tensor(false)]; tensor select_216_to_uint16 = const()[name = tensor("select_216_to_uint16"), val = tensor(2)]; tensor gather_216_cast_uint16 = gather(axis = gather_216_axis_0, batch_dims = gather_216_batch_dims_0, indices = select_216_to_uint16, validate_indices = gather_216_validate_indices_0, x = var_3664_shape_cast_fp16_to_uint16)[name = tensor("gather_216_cast_uint16")]; tensor gather_216_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_216_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_217_axis_0 = const()[name = tensor("gather_217_axis_0"), val = tensor(0)]; tensor gather_217_batch_dims_0 = const()[name = tensor("gather_217_batch_dims_0"), val = tensor(0)]; tensor gather_217_validate_indices_0 = const()[name = tensor("gather_217_validate_indices_0"), val = tensor(false)]; tensor select_217_to_uint16 = const()[name = tensor("select_217_to_uint16"), val = tensor(3)]; tensor gather_217_cast_uint16 = gather(axis = gather_217_axis_0, batch_dims = gather_217_batch_dims_0, indices = select_217_to_uint16, validate_indices = gather_217_validate_indices_0, x = var_3664_shape_cast_fp16_to_uint16)[name = tensor("gather_217_cast_uint16")]; tensor gather_217_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_217_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_44_pad_0 = const()[name = tensor("x0_44_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_44_mode_0 = const()[name = tensor("x0_44_mode_0"), val = tensor("constant")]; tensor const_51_to_fp16 = const()[name = tensor("const_51_to_fp16"), val = tensor(0x0p+0)]; tensor x0_44_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = x0_44_mode_0, pad = x0_44_pad_0, x = x_331_cast_fp16)[name = tensor("x0_44_cast_fp16")]; tensor concat_167_axis_0 = const()[name = tensor("concat_167_axis_0"), val = tensor(0)]; tensor concat_167_interleave_0 = const()[name = tensor("concat_167_interleave_0"), val = tensor(false)]; tensor gather_214_cast_uint16_to_int32 = cast(dtype = gather_214_cast_uint16_to_int32_dtype_0, x = gather_214_cast_uint16)[name = tensor("cast_35")]; tensor gather_216_cast_uint16_to_int32 = cast(dtype = gather_216_cast_uint16_to_int32_dtype_0, x = gather_216_cast_uint16)[name = tensor("cast_36")]; tensor concat_167 = concat(axis = concat_167_axis_0, interleave = concat_167_interleave_0, values = (gather_214_cast_uint16_to_int32, gather_215, var_21, gather_216_cast_uint16_to_int32))[name = tensor("concat_167")]; tensor x1_42_cast_fp16 = reshape(shape = concat_167, x = x0_44_cast_fp16)[name = tensor("x1_42_cast_fp16")]; tensor var_3674_begin_0 = const()[name = tensor("op_3674_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3674_end_0 = const()[name = tensor("op_3674_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_3674_end_mask_0 = const()[name = tensor("op_3674_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3674_cast_fp16 = slice_by_index(begin = var_3674_begin_0, end = var_3674_end_0, end_mask = var_3674_end_mask_0, x = x1_42_cast_fp16)[name = tensor("op_3674_cast_fp16")]; tensor concat_168_axis_0 = const()[name = tensor("concat_168_axis_0"), val = tensor(0)]; tensor concat_168_interleave_0 = const()[name = tensor("concat_168_interleave_0"), val = tensor(false)]; tensor gather_217_cast_uint16_to_int32 = cast(dtype = gather_217_cast_uint16_to_int32_dtype_0, x = gather_217_cast_uint16)[name = tensor("cast_34")]; tensor concat_168 = concat(axis = concat_168_axis_0, interleave = concat_168_interleave_0, values = (gather_214_cast_uint16_to_int32, gather_215, gather_216_cast_uint16_to_int32, gather_217_cast_uint16_to_int32))[name = tensor("concat_168")]; tensor matrix_bd_42_cast_fp16 = reshape(shape = concat_168, x = var_3674_cast_fp16)[name = tensor("matrix_bd_42_cast_fp16")]; tensor matrix_ac_42_transpose_x_0 = const()[name = tensor("matrix_ac_42_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_42_transpose_y_0 = const()[name = tensor("matrix_ac_42_transpose_y_0"), val = tensor(false)]; tensor transpose_274_perm_0 = const()[name = tensor("transpose_274_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_275_perm_0 = const()[name = tensor("transpose_275_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_275 = transpose(perm = transpose_275_perm_0, x = k_42_cast_fp16)[name = tensor("transpose_316")]; tensor transpose_274 = transpose(perm = transpose_274_perm_0, x = var_3658_cast_fp16)[name = tensor("transpose_317")]; tensor matrix_ac_42_cast_fp16 = matmul(transpose_x = matrix_ac_42_transpose_x_0, transpose_y = matrix_ac_42_transpose_y_0, x = transpose_274, y = transpose_275)[name = tensor("matrix_ac_42_cast_fp16")]; tensor var_3679_shape_cast_fp16 = shape(x = matrix_ac_42_cast_fp16)[name = tensor("op_3679_shape_cast_fp16")]; tensor gather_218_axis_0 = const()[name = tensor("gather_218_axis_0"), val = tensor(0)]; tensor gather_218_batch_dims_0 = const()[name = tensor("gather_218_batch_dims_0"), val = tensor(0)]; tensor gather_218_validate_indices_0 = const()[name = tensor("gather_218_validate_indices_0"), val = tensor(false)]; tensor var_3679_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3679_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_218_to_uint16 = const()[name = tensor("select_218_to_uint16"), val = tensor(3)]; tensor var_3679_shape_cast_fp16_to_uint16 = cast(dtype = var_3679_shape_cast_fp16_to_uint16_dtype_0, x = var_3679_shape_cast_fp16)[name = tensor("cast_33")]; tensor gather_218_cast_uint16 = gather(axis = gather_218_axis_0, batch_dims = gather_218_batch_dims_0, indices = select_218_to_uint16, validate_indices = gather_218_validate_indices_0, x = var_3679_shape_cast_fp16_to_uint16)[name = tensor("gather_218_cast_uint16")]; tensor gather_218_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_218_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_169_values0_0 = const()[name = tensor("concat_169_values0_0"), val = tensor(0)]; tensor concat_169_values1_0 = const()[name = tensor("concat_169_values1_0"), val = tensor(8)]; tensor concat_169_values2_0 = const()[name = tensor("concat_169_values2_0"), val = tensor(0)]; tensor concat_169_axis_0 = const()[name = tensor("concat_169_axis_0"), val = tensor(0)]; tensor concat_169_interleave_0 = const()[name = tensor("concat_169_interleave_0"), val = tensor(false)]; tensor gather_218_cast_uint16_to_int32 = cast(dtype = gather_218_cast_uint16_to_int32_dtype_0, x = gather_218_cast_uint16)[name = tensor("cast_32")]; tensor concat_169 = concat(axis = concat_169_axis_0, interleave = concat_169_interleave_0, values = (concat_169_values0_0, concat_169_values1_0, concat_169_values2_0, gather_218_cast_uint16_to_int32))[name = tensor("concat_169")]; tensor matrix_bd0_42_begin_0 = const()[name = tensor("matrix_bd0_42_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_42_end_mask_0 = const()[name = tensor("matrix_bd0_42_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_42_cast_fp16 = slice_by_index(begin = matrix_bd0_42_begin_0, end = concat_169, end_mask = matrix_bd0_42_end_mask_0, x = matrix_bd_42_cast_fp16)[name = tensor("matrix_bd0_42_cast_fp16")]; tensor var_3684_cast_fp16 = add(x = matrix_ac_42_cast_fp16, y = matrix_bd0_42_cast_fp16)[name = tensor("op_3684_cast_fp16")]; tensor _inversed_scores_42_y_0_to_fp16 = const()[name = tensor("_inversed_scores_42_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_42_cast_fp16 = mul(x = var_3684_cast_fp16, y = _inversed_scores_42_y_0_to_fp16)[name = tensor("_inversed_scores_42_cast_fp16")]; tensor value_42_cast_fp16 = transpose(perm = value_42_perm_0, x = v_42_cast_fp16)[name = tensor("transpose_315")]; tensor var_3687_shape_cast_fp16 = shape(x = value_42_cast_fp16)[name = tensor("op_3687_shape_cast_fp16")]; tensor gather_219_axis_0 = const()[name = tensor("gather_219_axis_0"), val = tensor(0)]; tensor gather_219_batch_dims_0 = const()[name = tensor("gather_219_batch_dims_0"), val = tensor(0)]; tensor gather_219_validate_indices_0 = const()[name = tensor("gather_219_validate_indices_0"), val = tensor(false)]; tensor var_3687_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3687_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_219_to_uint16 = const()[name = tensor("select_219_to_uint16"), val = tensor(0)]; tensor var_3687_shape_cast_fp16_to_uint16 = cast(dtype = var_3687_shape_cast_fp16_to_uint16_dtype_0, x = var_3687_shape_cast_fp16)[name = tensor("cast_31")]; tensor gather_219_cast_uint16 = gather(axis = gather_219_axis_0, batch_dims = gather_219_batch_dims_0, indices = select_219_to_uint16, validate_indices = gather_219_validate_indices_0, x = var_3687_shape_cast_fp16_to_uint16)[name = tensor("gather_219_cast_uint16")]; tensor gather_219_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_219_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_42_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_42_cast_fp16, cond = mask0_4)[name = tensor("scores0_42_cast_fp16")]; tensor var_3690_cast_fp16 = softmax(axis = var_21, x = scores0_42_cast_fp16)[name = tensor("op_3690_cast_fp16")]; tensor input_295_cast_fp16 = select(a = var_8_to_fp16, b = var_3690_cast_fp16, cond = mask0_4)[name = tensor("input_295_cast_fp16")]; tensor x2_42_transpose_x_0 = const()[name = tensor("x2_42_transpose_x_0"), val = tensor(false)]; tensor x2_42_transpose_y_0 = const()[name = tensor("x2_42_transpose_y_0"), val = tensor(false)]; tensor x2_42_cast_fp16 = matmul(transpose_x = x2_42_transpose_x_0, transpose_y = x2_42_transpose_y_0, x = input_295_cast_fp16, y = value_42_cast_fp16)[name = tensor("x2_42_cast_fp16")]; tensor var_3694_perm_0 = const()[name = tensor("op_3694_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_170_axis_0 = const()[name = tensor("concat_170_axis_0"), val = tensor(0)]; tensor concat_170_interleave_0 = const()[name = tensor("concat_170_interleave_0"), val = tensor(false)]; tensor gather_219_cast_uint16_to_int32 = cast(dtype = gather_219_cast_uint16_to_int32_dtype_0, x = gather_219_cast_uint16)[name = tensor("cast_30")]; tensor concat_170 = concat(axis = concat_170_axis_0, interleave = concat_170_interleave_0, values = (gather_219_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_170")]; tensor var_3694_cast_fp16 = transpose(perm = var_3694_perm_0, x = x2_42_cast_fp16)[name = tensor("transpose_314")]; tensor input0_285_cast_fp16 = reshape(shape = concat_170, x = var_3694_cast_fp16)[name = tensor("input0_285_cast_fp16")]; tensor encoder_layers_20_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(265953280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(266477632))), name = tensor("encoder_layers_20_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_187_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_self_attn_linear_out_weight_to_fp16_palettized, x = input0_285_cast_fp16)[name = tensor("linear_187_cast_fp16")]; tensor input0_287_cast_fp16 = add(x = input_293_cast_fp16, y = linear_187_cast_fp16)[name = tensor("input0_287_cast_fp16")]; tensor x_335_axes_0 = const()[name = tensor("x_335_axes_0"), val = tensor([-1])]; tensor encoder_layers_20_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_20_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(266477760)))]; tensor encoder_layers_20_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_20_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(266479872)))]; tensor x_335_cast_fp16 = layer_norm(axes = x_335_axes_0, beta = encoder_layers_20_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_20_norm_conv_weight_to_fp16, x = input0_287_cast_fp16)[name = tensor("x_335_cast_fp16")]; tensor input_297_perm_0 = const()[name = tensor("input_297_perm_0"), val = tensor([0, 2, 1])]; tensor input0_289_pad_type_0 = const()[name = tensor("input0_289_pad_type_0"), val = tensor("valid")]; tensor input0_289_strides_0 = const()[name = tensor("input0_289_strides_0"), val = tensor([1])]; tensor input0_289_pad_0 = const()[name = tensor("input0_289_pad_0"), val = tensor([0, 0])]; tensor input0_289_dilations_0 = const()[name = tensor("input0_289_dilations_0"), val = tensor([1])]; tensor input0_289_groups_0 = const()[name = tensor("input0_289_groups_0"), val = tensor(1)]; tensor encoder_layers_20_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(266481984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267530624))), name = tensor("encoder_layers_20_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_297_cast_fp16 = transpose(perm = input_297_perm_0, x = x_335_cast_fp16)[name = tensor("transpose_313")]; tensor input0_289_cast_fp16 = conv(dilations = input0_289_dilations_0, groups = input0_289_groups_0, pad = input0_289_pad_0, pad_type = input0_289_pad_type_0, strides = input0_289_strides_0, weight = encoder_layers_20_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_297_cast_fp16)[name = tensor("input0_289_cast_fp16")]; tensor x_337_split_num_splits_0 = const()[name = tensor("x_337_split_num_splits_0"), val = tensor(2)]; tensor x_337_split_axis_0 = const()[name = tensor("x_337_split_axis_0"), val = tensor(1)]; tensor x_337_split_cast_fp16_0, tensor x_337_split_cast_fp16_1 = split(axis = x_337_split_axis_0, num_splits = x_337_split_num_splits_0, x = input0_289_cast_fp16)[name = tensor("x_337_split_cast_fp16")]; tensor x_337_split_1_sigmoid_cast_fp16 = sigmoid(x = x_337_split_cast_fp16_1)[name = tensor("x_337_split_1_sigmoid_cast_fp16")]; tensor x_337_cast_fp16 = mul(x = x_337_split_cast_fp16_0, y = x_337_split_1_sigmoid_cast_fp16)[name = tensor("x_337_cast_fp16")]; tensor input0_291_cast_fp16 = select(a = var_8_to_fp16, b = x_337_cast_fp16, cond = var_457)[name = tensor("input0_291_cast_fp16")]; tensor input0_293_pad_0 = const()[name = tensor("input0_293_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_293_mode_0 = const()[name = tensor("input0_293_mode_0"), val = tensor("constant")]; tensor const_52_to_fp16 = const()[name = tensor("const_52_to_fp16"), val = tensor(0x0p+0)]; tensor input0_293_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input0_293_mode_0, pad = input0_293_pad_0, x = input0_291_cast_fp16)[name = tensor("input0_293_cast_fp16")]; tensor input1_86_pad_type_0 = const()[name = tensor("input1_86_pad_type_0"), val = tensor("valid")]; tensor input1_86_groups_0 = const()[name = tensor("input1_86_groups_0"), val = tensor(1024)]; tensor input1_86_strides_0 = const()[name = tensor("input1_86_strides_0"), val = tensor([1])]; tensor input1_86_pad_0 = const()[name = tensor("input1_86_pad_0"), val = tensor([0, 0])]; tensor input1_86_dilations_0 = const()[name = tensor("input1_86_dilations_0"), val = tensor([1])]; tensor const_99_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267530752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267535424))), name = tensor("const_99_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_100_to_fp16 = const()[name = tensor("const_100_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267535552)))]; tensor input_299_cast_fp16 = conv(bias = const_100_to_fp16, dilations = input1_86_dilations_0, groups = input1_86_groups_0, pad = input1_86_pad_0, pad_type = input1_86_pad_type_0, strides = input1_86_strides_0, weight = const_99_to_fp16_palettized, x = input0_293_cast_fp16)[name = tensor("input_299_cast_fp16")]; tensor var_3732_cast_fp16 = silu(x = input_299_cast_fp16)[name = tensor("op_3732_cast_fp16")]; tensor x_339_pad_type_0 = const()[name = tensor("x_339_pad_type_0"), val = tensor("valid")]; tensor x_339_strides_0 = const()[name = tensor("x_339_strides_0"), val = tensor([1])]; tensor x_339_pad_0 = const()[name = tensor("x_339_pad_0"), val = tensor([0, 0])]; tensor x_339_dilations_0 = const()[name = tensor("x_339_dilations_0"), val = tensor([1])]; tensor x_339_groups_0 = const()[name = tensor("x_339_groups_0"), val = tensor(1)]; tensor encoder_layers_20_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(267537664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268062016))), name = tensor("encoder_layers_20_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_339_cast_fp16 = conv(dilations = x_339_dilations_0, groups = x_339_groups_0, pad = x_339_pad_0, pad_type = x_339_pad_type_0, strides = x_339_strides_0, weight = encoder_layers_20_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3732_cast_fp16)[name = tensor("x_339_cast_fp16")]; tensor var_3739_perm_0 = const()[name = tensor("op_3739_perm_0"), val = tensor([0, 2, 1])]; tensor var_3739_cast_fp16 = transpose(perm = var_3739_perm_0, x = x_339_cast_fp16)[name = tensor("transpose_312")]; tensor input1_88_cast_fp16 = add(x = input0_287_cast_fp16, y = var_3739_cast_fp16)[name = tensor("input1_88_cast_fp16")]; tensor input0_295_axes_0 = const()[name = tensor("input0_295_axes_0"), val = tensor([-1])]; tensor encoder_layers_20_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_20_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268062144)))]; tensor encoder_layers_20_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_20_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268064256)))]; tensor input0_295_cast_fp16 = layer_norm(axes = input0_295_axes_0, beta = encoder_layers_20_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_20_norm_feed_forward2_weight_to_fp16, x = input1_88_cast_fp16)[name = tensor("input0_295_cast_fp16")]; tensor encoder_layers_20_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(268066368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270163584))), name = tensor("encoder_layers_20_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_188_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_20_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_295_cast_fp16)[name = tensor("linear_188_cast_fp16")]; tensor var_3750_cast_fp16 = silu(x = linear_188_cast_fp16)[name = tensor("op_3750_cast_fp16")]; tensor encoder_layers_20_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(270163712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272260928))), name = tensor("encoder_layers_20_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_189_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_20_feed_forward2_linear2_weight_to_fp16_palettized, x = var_3750_cast_fp16)[name = tensor("linear_189_cast_fp16")]; tensor var_3755_to_fp16 = const()[name = tensor("op_3755_to_fp16"), val = tensor(0x1p-1)]; tensor var_3756_cast_fp16 = mul(x = linear_189_cast_fp16, y = var_3755_to_fp16)[name = tensor("op_3756_cast_fp16")]; tensor input2_44_cast_fp16 = add(x = input1_88_cast_fp16, y = var_3756_cast_fp16)[name = tensor("input2_44_cast_fp16")]; tensor input0_297_axes_0 = const()[name = tensor("input0_297_axes_0"), val = tensor([-1])]; tensor encoder_layers_20_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_20_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272261056)))]; tensor encoder_layers_20_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_20_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272263168)))]; tensor input0_297_cast_fp16 = layer_norm(axes = input0_297_axes_0, beta = encoder_layers_20_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_20_norm_out_weight_to_fp16, x = input2_44_cast_fp16)[name = tensor("input0_297_cast_fp16")]; tensor input_303_axes_0 = const()[name = tensor("input_303_axes_0"), val = tensor([-1])]; tensor encoder_layers_21_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_21_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272265280)))]; tensor encoder_layers_21_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_21_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272267392)))]; tensor input_303_cast_fp16 = layer_norm(axes = input_303_axes_0, beta = encoder_layers_21_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_21_norm_feed_forward1_weight_to_fp16, x = input0_297_cast_fp16)[name = tensor("input_303_cast_fp16")]; tensor encoder_layers_21_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(272269504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274366720))), name = tensor("encoder_layers_21_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_190_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_21_feed_forward1_linear1_weight_to_fp16_palettized, x = input_303_cast_fp16)[name = tensor("linear_190_cast_fp16")]; tensor var_3779_cast_fp16 = silu(x = linear_190_cast_fp16)[name = tensor("op_3779_cast_fp16")]; tensor encoder_layers_21_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(274366848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276464064))), name = tensor("encoder_layers_21_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_191_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_feed_forward1_linear2_weight_to_fp16_palettized, x = var_3779_cast_fp16)[name = tensor("linear_191_cast_fp16")]; tensor var_3784_to_fp16 = const()[name = tensor("op_3784_to_fp16"), val = tensor(0x1p-1)]; tensor var_3785_cast_fp16 = mul(x = linear_191_cast_fp16, y = var_3784_to_fp16)[name = tensor("op_3785_cast_fp16")]; tensor input_307_cast_fp16 = add(x = input0_297_cast_fp16, y = var_3785_cast_fp16)[name = tensor("input_307_cast_fp16")]; tensor query_44_axes_0 = const()[name = tensor("query_44_axes_0"), val = tensor([-1])]; tensor encoder_layers_21_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_21_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276464192)))]; tensor encoder_layers_21_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_21_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276466304)))]; tensor query_44_cast_fp16 = layer_norm(axes = query_44_axes_0, beta = encoder_layers_21_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_21_norm_self_att_weight_to_fp16, x = input_307_cast_fp16)[name = tensor("query_44_cast_fp16")]; tensor var_3798_shape_cast_fp16 = shape(x = query_44_cast_fp16)[name = tensor("op_3798_shape_cast_fp16")]; tensor gather_220_axis_0 = const()[name = tensor("gather_220_axis_0"), val = tensor(0)]; tensor gather_220_batch_dims_0 = const()[name = tensor("gather_220_batch_dims_0"), val = tensor(0)]; tensor gather_220_validate_indices_0 = const()[name = tensor("gather_220_validate_indices_0"), val = tensor(false)]; tensor var_3798_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3798_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_220_to_uint16 = const()[name = tensor("select_220_to_uint16"), val = tensor(0)]; tensor var_3798_shape_cast_fp16_to_uint16 = cast(dtype = var_3798_shape_cast_fp16_to_uint16_dtype_0, x = var_3798_shape_cast_fp16)[name = tensor("cast_29")]; tensor gather_220_cast_uint16 = gather(axis = gather_220_axis_0, batch_dims = gather_220_batch_dims_0, indices = select_220_to_uint16, validate_indices = gather_220_validate_indices_0, x = var_3798_shape_cast_fp16_to_uint16)[name = tensor("gather_220_cast_uint16")]; tensor gather_220_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_220_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_21_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276468416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276992768))), name = tensor("encoder_layers_21_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_192_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_self_attn_linear_q_weight_to_fp16_palettized, x = query_44_cast_fp16)[name = tensor("linear_192_cast_fp16")]; tensor concat_171_axis_0 = const()[name = tensor("concat_171_axis_0"), val = tensor(0)]; tensor concat_171_interleave_0 = const()[name = tensor("concat_171_interleave_0"), val = tensor(false)]; tensor gather_220_cast_uint16_to_int32 = cast(dtype = gather_220_cast_uint16_to_int32_dtype_0, x = gather_220_cast_uint16)[name = tensor("cast_28")]; tensor concat_171 = concat(axis = concat_171_axis_0, interleave = concat_171_interleave_0, values = (gather_220_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_171")]; tensor q_44_cast_fp16 = reshape(shape = concat_171, x = linear_192_cast_fp16)[name = tensor("q_44_cast_fp16")]; tensor encoder_layers_21_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(276992896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277517248))), name = tensor("encoder_layers_21_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_193_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_self_attn_linear_k_weight_to_fp16_palettized, x = query_44_cast_fp16)[name = tensor("linear_193_cast_fp16")]; tensor k_44_cast_fp16 = reshape(shape = concat_171, x = linear_193_cast_fp16)[name = tensor("k_44_cast_fp16")]; tensor encoder_layers_21_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(277517376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278041728))), name = tensor("encoder_layers_21_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_194_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_self_attn_linear_v_weight_to_fp16_palettized, x = query_44_cast_fp16)[name = tensor("linear_194_cast_fp16")]; tensor v_44_cast_fp16 = reshape(shape = concat_171, x = linear_194_cast_fp16)[name = tensor("v_44_cast_fp16")]; tensor value_44_perm_0 = const()[name = tensor("value_44_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_21_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278041856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278566208))), name = tensor("encoder_layers_21_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_195_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_195_cast_fp16")]; tensor var_3818 = const()[name = tensor("op_3818"), val = tensor([1, -1, 8, 128])]; tensor p_44_cast_fp16 = reshape(shape = var_3818, x = linear_195_cast_fp16)[name = tensor("p_44_cast_fp16")]; tensor encoder_layers_21_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_21_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278566336)))]; tensor var_3821_cast_fp16 = add(x = q_44_cast_fp16, y = encoder_layers_21_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3821_cast_fp16")]; tensor encoder_layers_21_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_21_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278568448)))]; tensor var_3823_cast_fp16 = add(x = q_44_cast_fp16, y = encoder_layers_21_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3823_cast_fp16")]; tensor x_347_transpose_x_0 = const()[name = tensor("x_347_transpose_x_0"), val = tensor(false)]; tensor x_347_transpose_y_0 = const()[name = tensor("x_347_transpose_y_0"), val = tensor(false)]; tensor transpose_276_perm_0 = const()[name = tensor("transpose_276_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_277_perm_0 = const()[name = tensor("transpose_277_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_277 = transpose(perm = transpose_277_perm_0, x = p_44_cast_fp16)[name = tensor("transpose_310")]; tensor transpose_276 = transpose(perm = transpose_276_perm_0, x = var_3823_cast_fp16)[name = tensor("transpose_311")]; tensor x_347_cast_fp16 = matmul(transpose_x = x_347_transpose_x_0, transpose_y = x_347_transpose_y_0, x = transpose_276, y = transpose_277)[name = tensor("x_347_cast_fp16")]; tensor var_3827_shape_cast_fp16 = shape(x = x_347_cast_fp16)[name = tensor("op_3827_shape_cast_fp16")]; tensor gather_222_axis_0 = const()[name = tensor("gather_222_axis_0"), val = tensor(0)]; tensor gather_222_batch_dims_0 = const()[name = tensor("gather_222_batch_dims_0"), val = tensor(0)]; tensor gather_222_validate_indices_0 = const()[name = tensor("gather_222_validate_indices_0"), val = tensor(false)]; tensor var_3827_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3827_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_222_to_uint16 = const()[name = tensor("select_222_to_uint16"), val = tensor(0)]; tensor var_3827_shape_cast_fp16_to_uint16 = cast(dtype = var_3827_shape_cast_fp16_to_uint16_dtype_0, x = var_3827_shape_cast_fp16)[name = tensor("cast_27")]; tensor gather_222_cast_uint16 = gather(axis = gather_222_axis_0, batch_dims = gather_222_batch_dims_0, indices = select_222_to_uint16, validate_indices = gather_222_validate_indices_0, x = var_3827_shape_cast_fp16_to_uint16)[name = tensor("gather_222_cast_uint16")]; tensor gather_222_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_222_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_223 = const()[name = tensor("gather_223"), val = tensor(8)]; tensor gather_224_axis_0 = const()[name = tensor("gather_224_axis_0"), val = tensor(0)]; tensor gather_224_batch_dims_0 = const()[name = tensor("gather_224_batch_dims_0"), val = tensor(0)]; tensor gather_224_validate_indices_0 = const()[name = tensor("gather_224_validate_indices_0"), val = tensor(false)]; tensor select_224_to_uint16 = const()[name = tensor("select_224_to_uint16"), val = tensor(2)]; tensor gather_224_cast_uint16 = gather(axis = gather_224_axis_0, batch_dims = gather_224_batch_dims_0, indices = select_224_to_uint16, validate_indices = gather_224_validate_indices_0, x = var_3827_shape_cast_fp16_to_uint16)[name = tensor("gather_224_cast_uint16")]; tensor gather_224_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_224_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_225_axis_0 = const()[name = tensor("gather_225_axis_0"), val = tensor(0)]; tensor gather_225_batch_dims_0 = const()[name = tensor("gather_225_batch_dims_0"), val = tensor(0)]; tensor gather_225_validate_indices_0 = const()[name = tensor("gather_225_validate_indices_0"), val = tensor(false)]; tensor select_225_to_uint16 = const()[name = tensor("select_225_to_uint16"), val = tensor(3)]; tensor gather_225_cast_uint16 = gather(axis = gather_225_axis_0, batch_dims = gather_225_batch_dims_0, indices = select_225_to_uint16, validate_indices = gather_225_validate_indices_0, x = var_3827_shape_cast_fp16_to_uint16)[name = tensor("gather_225_cast_uint16")]; tensor gather_225_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_225_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_46_pad_0 = const()[name = tensor("x0_46_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_46_mode_0 = const()[name = tensor("x0_46_mode_0"), val = tensor("constant")]; tensor const_53_to_fp16 = const()[name = tensor("const_53_to_fp16"), val = tensor(0x0p+0)]; tensor x0_46_cast_fp16 = pad(constant_val = const_53_to_fp16, mode = x0_46_mode_0, pad = x0_46_pad_0, x = x_347_cast_fp16)[name = tensor("x0_46_cast_fp16")]; tensor concat_174_axis_0 = const()[name = tensor("concat_174_axis_0"), val = tensor(0)]; tensor concat_174_interleave_0 = const()[name = tensor("concat_174_interleave_0"), val = tensor(false)]; tensor gather_222_cast_uint16_to_int32 = cast(dtype = gather_222_cast_uint16_to_int32_dtype_0, x = gather_222_cast_uint16)[name = tensor("cast_25")]; tensor gather_224_cast_uint16_to_int32 = cast(dtype = gather_224_cast_uint16_to_int32_dtype_0, x = gather_224_cast_uint16)[name = tensor("cast_26")]; tensor concat_174 = concat(axis = concat_174_axis_0, interleave = concat_174_interleave_0, values = (gather_222_cast_uint16_to_int32, gather_223, var_21, gather_224_cast_uint16_to_int32))[name = tensor("concat_174")]; tensor x1_44_cast_fp16 = reshape(shape = concat_174, x = x0_46_cast_fp16)[name = tensor("x1_44_cast_fp16")]; tensor var_3837_begin_0 = const()[name = tensor("op_3837_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3837_end_0 = const()[name = tensor("op_3837_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_3837_end_mask_0 = const()[name = tensor("op_3837_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3837_cast_fp16 = slice_by_index(begin = var_3837_begin_0, end = var_3837_end_0, end_mask = var_3837_end_mask_0, x = x1_44_cast_fp16)[name = tensor("op_3837_cast_fp16")]; tensor concat_175_axis_0 = const()[name = tensor("concat_175_axis_0"), val = tensor(0)]; tensor concat_175_interleave_0 = const()[name = tensor("concat_175_interleave_0"), val = tensor(false)]; tensor gather_225_cast_uint16_to_int32 = cast(dtype = gather_225_cast_uint16_to_int32_dtype_0, x = gather_225_cast_uint16)[name = tensor("cast_24")]; tensor concat_175 = concat(axis = concat_175_axis_0, interleave = concat_175_interleave_0, values = (gather_222_cast_uint16_to_int32, gather_223, gather_224_cast_uint16_to_int32, gather_225_cast_uint16_to_int32))[name = tensor("concat_175")]; tensor matrix_bd_44_cast_fp16 = reshape(shape = concat_175, x = var_3837_cast_fp16)[name = tensor("matrix_bd_44_cast_fp16")]; tensor matrix_ac_44_transpose_x_0 = const()[name = tensor("matrix_ac_44_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_44_transpose_y_0 = const()[name = tensor("matrix_ac_44_transpose_y_0"), val = tensor(false)]; tensor transpose_278_perm_0 = const()[name = tensor("transpose_278_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_279_perm_0 = const()[name = tensor("transpose_279_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_279 = transpose(perm = transpose_279_perm_0, x = k_44_cast_fp16)[name = tensor("transpose_308")]; tensor transpose_278 = transpose(perm = transpose_278_perm_0, x = var_3821_cast_fp16)[name = tensor("transpose_309")]; tensor matrix_ac_44_cast_fp16 = matmul(transpose_x = matrix_ac_44_transpose_x_0, transpose_y = matrix_ac_44_transpose_y_0, x = transpose_278, y = transpose_279)[name = tensor("matrix_ac_44_cast_fp16")]; tensor var_3842_shape_cast_fp16 = shape(x = matrix_ac_44_cast_fp16)[name = tensor("op_3842_shape_cast_fp16")]; tensor gather_226_axis_0 = const()[name = tensor("gather_226_axis_0"), val = tensor(0)]; tensor gather_226_batch_dims_0 = const()[name = tensor("gather_226_batch_dims_0"), val = tensor(0)]; tensor gather_226_validate_indices_0 = const()[name = tensor("gather_226_validate_indices_0"), val = tensor(false)]; tensor var_3842_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3842_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_226_to_uint16 = const()[name = tensor("select_226_to_uint16"), val = tensor(3)]; tensor var_3842_shape_cast_fp16_to_uint16 = cast(dtype = var_3842_shape_cast_fp16_to_uint16_dtype_0, x = var_3842_shape_cast_fp16)[name = tensor("cast_23")]; tensor gather_226_cast_uint16 = gather(axis = gather_226_axis_0, batch_dims = gather_226_batch_dims_0, indices = select_226_to_uint16, validate_indices = gather_226_validate_indices_0, x = var_3842_shape_cast_fp16_to_uint16)[name = tensor("gather_226_cast_uint16")]; tensor gather_226_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_226_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_176_values0_0 = const()[name = tensor("concat_176_values0_0"), val = tensor(0)]; tensor concat_176_values1_0 = const()[name = tensor("concat_176_values1_0"), val = tensor(8)]; tensor concat_176_values2_0 = const()[name = tensor("concat_176_values2_0"), val = tensor(0)]; tensor concat_176_axis_0 = const()[name = tensor("concat_176_axis_0"), val = tensor(0)]; tensor concat_176_interleave_0 = const()[name = tensor("concat_176_interleave_0"), val = tensor(false)]; tensor gather_226_cast_uint16_to_int32 = cast(dtype = gather_226_cast_uint16_to_int32_dtype_0, x = gather_226_cast_uint16)[name = tensor("cast_22")]; tensor concat_176 = concat(axis = concat_176_axis_0, interleave = concat_176_interleave_0, values = (concat_176_values0_0, concat_176_values1_0, concat_176_values2_0, gather_226_cast_uint16_to_int32))[name = tensor("concat_176")]; tensor matrix_bd0_44_begin_0 = const()[name = tensor("matrix_bd0_44_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_44_end_mask_0 = const()[name = tensor("matrix_bd0_44_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_44_cast_fp16 = slice_by_index(begin = matrix_bd0_44_begin_0, end = concat_176, end_mask = matrix_bd0_44_end_mask_0, x = matrix_bd_44_cast_fp16)[name = tensor("matrix_bd0_44_cast_fp16")]; tensor var_3847_cast_fp16 = add(x = matrix_ac_44_cast_fp16, y = matrix_bd0_44_cast_fp16)[name = tensor("op_3847_cast_fp16")]; tensor _inversed_scores_44_y_0_to_fp16 = const()[name = tensor("_inversed_scores_44_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_44_cast_fp16 = mul(x = var_3847_cast_fp16, y = _inversed_scores_44_y_0_to_fp16)[name = tensor("_inversed_scores_44_cast_fp16")]; tensor value_44_cast_fp16 = transpose(perm = value_44_perm_0, x = v_44_cast_fp16)[name = tensor("transpose_307")]; tensor var_3850_shape_cast_fp16 = shape(x = value_44_cast_fp16)[name = tensor("op_3850_shape_cast_fp16")]; tensor gather_227_axis_0 = const()[name = tensor("gather_227_axis_0"), val = tensor(0)]; tensor gather_227_batch_dims_0 = const()[name = tensor("gather_227_batch_dims_0"), val = tensor(0)]; tensor gather_227_validate_indices_0 = const()[name = tensor("gather_227_validate_indices_0"), val = tensor(false)]; tensor var_3850_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3850_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_227_to_uint16 = const()[name = tensor("select_227_to_uint16"), val = tensor(0)]; tensor var_3850_shape_cast_fp16_to_uint16 = cast(dtype = var_3850_shape_cast_fp16_to_uint16_dtype_0, x = var_3850_shape_cast_fp16)[name = tensor("cast_21")]; tensor gather_227_cast_uint16 = gather(axis = gather_227_axis_0, batch_dims = gather_227_batch_dims_0, indices = select_227_to_uint16, validate_indices = gather_227_validate_indices_0, x = var_3850_shape_cast_fp16_to_uint16)[name = tensor("gather_227_cast_uint16")]; tensor gather_227_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_227_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_44_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_44_cast_fp16, cond = mask0_4)[name = tensor("scores0_44_cast_fp16")]; tensor var_3853_cast_fp16 = softmax(axis = var_21, x = scores0_44_cast_fp16)[name = tensor("op_3853_cast_fp16")]; tensor input_309_cast_fp16 = select(a = var_8_to_fp16, b = var_3853_cast_fp16, cond = mask0_4)[name = tensor("input_309_cast_fp16")]; tensor x2_44_transpose_x_0 = const()[name = tensor("x2_44_transpose_x_0"), val = tensor(false)]; tensor x2_44_transpose_y_0 = const()[name = tensor("x2_44_transpose_y_0"), val = tensor(false)]; tensor x2_44_cast_fp16 = matmul(transpose_x = x2_44_transpose_x_0, transpose_y = x2_44_transpose_y_0, x = input_309_cast_fp16, y = value_44_cast_fp16)[name = tensor("x2_44_cast_fp16")]; tensor var_3857_perm_0 = const()[name = tensor("op_3857_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_177_axis_0 = const()[name = tensor("concat_177_axis_0"), val = tensor(0)]; tensor concat_177_interleave_0 = const()[name = tensor("concat_177_interleave_0"), val = tensor(false)]; tensor gather_227_cast_uint16_to_int32 = cast(dtype = gather_227_cast_uint16_to_int32_dtype_0, x = gather_227_cast_uint16)[name = tensor("cast_20")]; tensor concat_177 = concat(axis = concat_177_axis_0, interleave = concat_177_interleave_0, values = (gather_227_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_177")]; tensor var_3857_cast_fp16 = transpose(perm = var_3857_perm_0, x = x2_44_cast_fp16)[name = tensor("transpose_306")]; tensor input0_299_cast_fp16 = reshape(shape = concat_177, x = var_3857_cast_fp16)[name = tensor("input0_299_cast_fp16")]; tensor encoder_layers_21_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(278570560))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279094912))), name = tensor("encoder_layers_21_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_196_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_self_attn_linear_out_weight_to_fp16_palettized, x = input0_299_cast_fp16)[name = tensor("linear_196_cast_fp16")]; tensor input0_301_cast_fp16 = add(x = input_307_cast_fp16, y = linear_196_cast_fp16)[name = tensor("input0_301_cast_fp16")]; tensor x_351_axes_0 = const()[name = tensor("x_351_axes_0"), val = tensor([-1])]; tensor encoder_layers_21_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_21_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279095040)))]; tensor encoder_layers_21_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_21_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279097152)))]; tensor x_351_cast_fp16 = layer_norm(axes = x_351_axes_0, beta = encoder_layers_21_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_21_norm_conv_weight_to_fp16, x = input0_301_cast_fp16)[name = tensor("x_351_cast_fp16")]; tensor input_311_perm_0 = const()[name = tensor("input_311_perm_0"), val = tensor([0, 2, 1])]; tensor input0_303_pad_type_0 = const()[name = tensor("input0_303_pad_type_0"), val = tensor("valid")]; tensor input0_303_strides_0 = const()[name = tensor("input0_303_strides_0"), val = tensor([1])]; tensor input0_303_pad_0 = const()[name = tensor("input0_303_pad_0"), val = tensor([0, 0])]; tensor input0_303_dilations_0 = const()[name = tensor("input0_303_dilations_0"), val = tensor([1])]; tensor input0_303_groups_0 = const()[name = tensor("input0_303_groups_0"), val = tensor(1)]; tensor encoder_layers_21_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(279099264))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280147904))), name = tensor("encoder_layers_21_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_311_cast_fp16 = transpose(perm = input_311_perm_0, x = x_351_cast_fp16)[name = tensor("transpose_305")]; tensor input0_303_cast_fp16 = conv(dilations = input0_303_dilations_0, groups = input0_303_groups_0, pad = input0_303_pad_0, pad_type = input0_303_pad_type_0, strides = input0_303_strides_0, weight = encoder_layers_21_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_311_cast_fp16)[name = tensor("input0_303_cast_fp16")]; tensor x_353_split_num_splits_0 = const()[name = tensor("x_353_split_num_splits_0"), val = tensor(2)]; tensor x_353_split_axis_0 = const()[name = tensor("x_353_split_axis_0"), val = tensor(1)]; tensor x_353_split_cast_fp16_0, tensor x_353_split_cast_fp16_1 = split(axis = x_353_split_axis_0, num_splits = x_353_split_num_splits_0, x = input0_303_cast_fp16)[name = tensor("x_353_split_cast_fp16")]; tensor x_353_split_1_sigmoid_cast_fp16 = sigmoid(x = x_353_split_cast_fp16_1)[name = tensor("x_353_split_1_sigmoid_cast_fp16")]; tensor x_353_cast_fp16 = mul(x = x_353_split_cast_fp16_0, y = x_353_split_1_sigmoid_cast_fp16)[name = tensor("x_353_cast_fp16")]; tensor input0_305_cast_fp16 = select(a = var_8_to_fp16, b = x_353_cast_fp16, cond = var_457)[name = tensor("input0_305_cast_fp16")]; tensor input0_307_pad_0 = const()[name = tensor("input0_307_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_307_mode_0 = const()[name = tensor("input0_307_mode_0"), val = tensor("constant")]; tensor const_54_to_fp16 = const()[name = tensor("const_54_to_fp16"), val = tensor(0x0p+0)]; tensor input0_307_cast_fp16 = pad(constant_val = const_54_to_fp16, mode = input0_307_mode_0, pad = input0_307_pad_0, x = input0_305_cast_fp16)[name = tensor("input0_307_cast_fp16")]; tensor input1_90_pad_type_0 = const()[name = tensor("input1_90_pad_type_0"), val = tensor("valid")]; tensor input1_90_groups_0 = const()[name = tensor("input1_90_groups_0"), val = tensor(1024)]; tensor input1_90_strides_0 = const()[name = tensor("input1_90_strides_0"), val = tensor([1])]; tensor input1_90_pad_0 = const()[name = tensor("input1_90_pad_0"), val = tensor([0, 0])]; tensor input1_90_dilations_0 = const()[name = tensor("input1_90_dilations_0"), val = tensor([1])]; tensor const_101_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280148032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280152704))), name = tensor("const_101_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_102_to_fp16 = const()[name = tensor("const_102_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280152832)))]; tensor input_313_cast_fp16 = conv(bias = const_102_to_fp16, dilations = input1_90_dilations_0, groups = input1_90_groups_0, pad = input1_90_pad_0, pad_type = input1_90_pad_type_0, strides = input1_90_strides_0, weight = const_101_to_fp16_palettized, x = input0_307_cast_fp16)[name = tensor("input_313_cast_fp16")]; tensor var_3895_cast_fp16 = silu(x = input_313_cast_fp16)[name = tensor("op_3895_cast_fp16")]; tensor x_355_pad_type_0 = const()[name = tensor("x_355_pad_type_0"), val = tensor("valid")]; tensor x_355_strides_0 = const()[name = tensor("x_355_strides_0"), val = tensor([1])]; tensor x_355_pad_0 = const()[name = tensor("x_355_pad_0"), val = tensor([0, 0])]; tensor x_355_dilations_0 = const()[name = tensor("x_355_dilations_0"), val = tensor([1])]; tensor x_355_groups_0 = const()[name = tensor("x_355_groups_0"), val = tensor(1)]; tensor encoder_layers_21_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280154944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280679296))), name = tensor("encoder_layers_21_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_355_cast_fp16 = conv(dilations = x_355_dilations_0, groups = x_355_groups_0, pad = x_355_pad_0, pad_type = x_355_pad_type_0, strides = x_355_strides_0, weight = encoder_layers_21_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3895_cast_fp16)[name = tensor("x_355_cast_fp16")]; tensor var_3902_perm_0 = const()[name = tensor("op_3902_perm_0"), val = tensor([0, 2, 1])]; tensor var_3902_cast_fp16 = transpose(perm = var_3902_perm_0, x = x_355_cast_fp16)[name = tensor("transpose_304")]; tensor input1_92_cast_fp16 = add(x = input0_301_cast_fp16, y = var_3902_cast_fp16)[name = tensor("input1_92_cast_fp16")]; tensor input0_309_axes_0 = const()[name = tensor("input0_309_axes_0"), val = tensor([-1])]; tensor encoder_layers_21_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_21_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280679424)))]; tensor encoder_layers_21_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_21_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280681536)))]; tensor input0_309_cast_fp16 = layer_norm(axes = input0_309_axes_0, beta = encoder_layers_21_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_21_norm_feed_forward2_weight_to_fp16, x = input1_92_cast_fp16)[name = tensor("input0_309_cast_fp16")]; tensor encoder_layers_21_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(280683648))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282780864))), name = tensor("encoder_layers_21_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_197_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_21_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_309_cast_fp16)[name = tensor("linear_197_cast_fp16")]; tensor var_3913_cast_fp16 = silu(x = linear_197_cast_fp16)[name = tensor("op_3913_cast_fp16")]; tensor encoder_layers_21_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(282780992))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284878208))), name = tensor("encoder_layers_21_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_198_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_21_feed_forward2_linear2_weight_to_fp16_palettized, x = var_3913_cast_fp16)[name = tensor("linear_198_cast_fp16")]; tensor var_3918_to_fp16 = const()[name = tensor("op_3918_to_fp16"), val = tensor(0x1p-1)]; tensor var_3919_cast_fp16 = mul(x = linear_198_cast_fp16, y = var_3918_to_fp16)[name = tensor("op_3919_cast_fp16")]; tensor input2_46_cast_fp16 = add(x = input1_92_cast_fp16, y = var_3919_cast_fp16)[name = tensor("input2_46_cast_fp16")]; tensor input0_311_axes_0 = const()[name = tensor("input0_311_axes_0"), val = tensor([-1])]; tensor encoder_layers_21_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_21_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284878336)))]; tensor encoder_layers_21_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_21_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284880448)))]; tensor input0_311_cast_fp16 = layer_norm(axes = input0_311_axes_0, beta = encoder_layers_21_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_21_norm_out_weight_to_fp16, x = input2_46_cast_fp16)[name = tensor("input0_311_cast_fp16")]; tensor input_317_axes_0 = const()[name = tensor("input_317_axes_0"), val = tensor([-1])]; tensor encoder_layers_22_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_22_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284882560)))]; tensor encoder_layers_22_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_22_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284884672)))]; tensor input_317_cast_fp16 = layer_norm(axes = input_317_axes_0, beta = encoder_layers_22_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_22_norm_feed_forward1_weight_to_fp16, x = input0_311_cast_fp16)[name = tensor("input_317_cast_fp16")]; tensor encoder_layers_22_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(284886784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286984000))), name = tensor("encoder_layers_22_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_199_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_22_feed_forward1_linear1_weight_to_fp16_palettized, x = input_317_cast_fp16)[name = tensor("linear_199_cast_fp16")]; tensor var_3942_cast_fp16 = silu(x = linear_199_cast_fp16)[name = tensor("op_3942_cast_fp16")]; tensor encoder_layers_22_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(286984128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289081344))), name = tensor("encoder_layers_22_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_200_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_feed_forward1_linear2_weight_to_fp16_palettized, x = var_3942_cast_fp16)[name = tensor("linear_200_cast_fp16")]; tensor var_3947_to_fp16 = const()[name = tensor("op_3947_to_fp16"), val = tensor(0x1p-1)]; tensor var_3948_cast_fp16 = mul(x = linear_200_cast_fp16, y = var_3947_to_fp16)[name = tensor("op_3948_cast_fp16")]; tensor input_321_cast_fp16 = add(x = input0_311_cast_fp16, y = var_3948_cast_fp16)[name = tensor("input_321_cast_fp16")]; tensor query_46_axes_0 = const()[name = tensor("query_46_axes_0"), val = tensor([-1])]; tensor encoder_layers_22_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_22_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289081472)))]; tensor encoder_layers_22_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_22_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289083584)))]; tensor query_46_cast_fp16 = layer_norm(axes = query_46_axes_0, beta = encoder_layers_22_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_22_norm_self_att_weight_to_fp16, x = input_321_cast_fp16)[name = tensor("query_46_cast_fp16")]; tensor var_3961_shape_cast_fp16 = shape(x = query_46_cast_fp16)[name = tensor("op_3961_shape_cast_fp16")]; tensor gather_228_axis_0 = const()[name = tensor("gather_228_axis_0"), val = tensor(0)]; tensor gather_228_batch_dims_0 = const()[name = tensor("gather_228_batch_dims_0"), val = tensor(0)]; tensor gather_228_validate_indices_0 = const()[name = tensor("gather_228_validate_indices_0"), val = tensor(false)]; tensor var_3961_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3961_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_228_to_uint16 = const()[name = tensor("select_228_to_uint16"), val = tensor(0)]; tensor var_3961_shape_cast_fp16_to_uint16 = cast(dtype = var_3961_shape_cast_fp16_to_uint16_dtype_0, x = var_3961_shape_cast_fp16)[name = tensor("cast_19")]; tensor gather_228_cast_uint16 = gather(axis = gather_228_axis_0, batch_dims = gather_228_batch_dims_0, indices = select_228_to_uint16, validate_indices = gather_228_validate_indices_0, x = var_3961_shape_cast_fp16_to_uint16)[name = tensor("gather_228_cast_uint16")]; tensor gather_228_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_228_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_22_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289085696))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289610048))), name = tensor("encoder_layers_22_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_201_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_self_attn_linear_q_weight_to_fp16_palettized, x = query_46_cast_fp16)[name = tensor("linear_201_cast_fp16")]; tensor concat_178_axis_0 = const()[name = tensor("concat_178_axis_0"), val = tensor(0)]; tensor concat_178_interleave_0 = const()[name = tensor("concat_178_interleave_0"), val = tensor(false)]; tensor gather_228_cast_uint16_to_int32 = cast(dtype = gather_228_cast_uint16_to_int32_dtype_0, x = gather_228_cast_uint16)[name = tensor("cast_18")]; tensor concat_178 = concat(axis = concat_178_axis_0, interleave = concat_178_interleave_0, values = (gather_228_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_178")]; tensor q_46_cast_fp16 = reshape(shape = concat_178, x = linear_201_cast_fp16)[name = tensor("q_46_cast_fp16")]; tensor encoder_layers_22_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(289610176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290134528))), name = tensor("encoder_layers_22_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_202_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_self_attn_linear_k_weight_to_fp16_palettized, x = query_46_cast_fp16)[name = tensor("linear_202_cast_fp16")]; tensor k_46_cast_fp16 = reshape(shape = concat_178, x = linear_202_cast_fp16)[name = tensor("k_46_cast_fp16")]; tensor encoder_layers_22_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290134656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290659008))), name = tensor("encoder_layers_22_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_203_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_self_attn_linear_v_weight_to_fp16_palettized, x = query_46_cast_fp16)[name = tensor("linear_203_cast_fp16")]; tensor v_46_cast_fp16 = reshape(shape = concat_178, x = linear_203_cast_fp16)[name = tensor("v_46_cast_fp16")]; tensor value_46_perm_0 = const()[name = tensor("value_46_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_22_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(290659136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291183488))), name = tensor("encoder_layers_22_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_204_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_204_cast_fp16")]; tensor var_3981 = const()[name = tensor("op_3981"), val = tensor([1, -1, 8, 128])]; tensor p_46_cast_fp16 = reshape(shape = var_3981, x = linear_204_cast_fp16)[name = tensor("p_46_cast_fp16")]; tensor encoder_layers_22_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_22_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291183616)))]; tensor var_3984_cast_fp16 = add(x = q_46_cast_fp16, y = encoder_layers_22_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3984_cast_fp16")]; tensor encoder_layers_22_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_22_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291185728)))]; tensor var_3986_cast_fp16 = add(x = q_46_cast_fp16, y = encoder_layers_22_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3986_cast_fp16")]; tensor x_363_transpose_x_0 = const()[name = tensor("x_363_transpose_x_0"), val = tensor(false)]; tensor x_363_transpose_y_0 = const()[name = tensor("x_363_transpose_y_0"), val = tensor(false)]; tensor transpose_280_perm_0 = const()[name = tensor("transpose_280_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_281_perm_0 = const()[name = tensor("transpose_281_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_281 = transpose(perm = transpose_281_perm_0, x = p_46_cast_fp16)[name = tensor("transpose_302")]; tensor transpose_280 = transpose(perm = transpose_280_perm_0, x = var_3986_cast_fp16)[name = tensor("transpose_303")]; tensor x_363_cast_fp16 = matmul(transpose_x = x_363_transpose_x_0, transpose_y = x_363_transpose_y_0, x = transpose_280, y = transpose_281)[name = tensor("x_363_cast_fp16")]; tensor var_3990_shape_cast_fp16 = shape(x = x_363_cast_fp16)[name = tensor("op_3990_shape_cast_fp16")]; tensor gather_230_axis_0 = const()[name = tensor("gather_230_axis_0"), val = tensor(0)]; tensor gather_230_batch_dims_0 = const()[name = tensor("gather_230_batch_dims_0"), val = tensor(0)]; tensor gather_230_validate_indices_0 = const()[name = tensor("gather_230_validate_indices_0"), val = tensor(false)]; tensor var_3990_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_3990_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_230_to_uint16 = const()[name = tensor("select_230_to_uint16"), val = tensor(0)]; tensor var_3990_shape_cast_fp16_to_uint16 = cast(dtype = var_3990_shape_cast_fp16_to_uint16_dtype_0, x = var_3990_shape_cast_fp16)[name = tensor("cast_17")]; tensor gather_230_cast_uint16 = gather(axis = gather_230_axis_0, batch_dims = gather_230_batch_dims_0, indices = select_230_to_uint16, validate_indices = gather_230_validate_indices_0, x = var_3990_shape_cast_fp16_to_uint16)[name = tensor("gather_230_cast_uint16")]; tensor gather_230_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_230_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_231 = const()[name = tensor("gather_231"), val = tensor(8)]; tensor gather_232_axis_0 = const()[name = tensor("gather_232_axis_0"), val = tensor(0)]; tensor gather_232_batch_dims_0 = const()[name = tensor("gather_232_batch_dims_0"), val = tensor(0)]; tensor gather_232_validate_indices_0 = const()[name = tensor("gather_232_validate_indices_0"), val = tensor(false)]; tensor select_232_to_uint16 = const()[name = tensor("select_232_to_uint16"), val = tensor(2)]; tensor gather_232_cast_uint16 = gather(axis = gather_232_axis_0, batch_dims = gather_232_batch_dims_0, indices = select_232_to_uint16, validate_indices = gather_232_validate_indices_0, x = var_3990_shape_cast_fp16_to_uint16)[name = tensor("gather_232_cast_uint16")]; tensor gather_232_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_232_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_233_axis_0 = const()[name = tensor("gather_233_axis_0"), val = tensor(0)]; tensor gather_233_batch_dims_0 = const()[name = tensor("gather_233_batch_dims_0"), val = tensor(0)]; tensor gather_233_validate_indices_0 = const()[name = tensor("gather_233_validate_indices_0"), val = tensor(false)]; tensor select_233_to_uint16 = const()[name = tensor("select_233_to_uint16"), val = tensor(3)]; tensor gather_233_cast_uint16 = gather(axis = gather_233_axis_0, batch_dims = gather_233_batch_dims_0, indices = select_233_to_uint16, validate_indices = gather_233_validate_indices_0, x = var_3990_shape_cast_fp16_to_uint16)[name = tensor("gather_233_cast_uint16")]; tensor gather_233_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_233_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_48_pad_0 = const()[name = tensor("x0_48_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_48_mode_0 = const()[name = tensor("x0_48_mode_0"), val = tensor("constant")]; tensor const_55_to_fp16 = const()[name = tensor("const_55_to_fp16"), val = tensor(0x0p+0)]; tensor x0_48_cast_fp16 = pad(constant_val = const_55_to_fp16, mode = x0_48_mode_0, pad = x0_48_pad_0, x = x_363_cast_fp16)[name = tensor("x0_48_cast_fp16")]; tensor concat_181_axis_0 = const()[name = tensor("concat_181_axis_0"), val = tensor(0)]; tensor concat_181_interleave_0 = const()[name = tensor("concat_181_interleave_0"), val = tensor(false)]; tensor gather_230_cast_uint16_to_int32 = cast(dtype = gather_230_cast_uint16_to_int32_dtype_0, x = gather_230_cast_uint16)[name = tensor("cast_15")]; tensor gather_232_cast_uint16_to_int32 = cast(dtype = gather_232_cast_uint16_to_int32_dtype_0, x = gather_232_cast_uint16)[name = tensor("cast_16")]; tensor concat_181 = concat(axis = concat_181_axis_0, interleave = concat_181_interleave_0, values = (gather_230_cast_uint16_to_int32, gather_231, var_21, gather_232_cast_uint16_to_int32))[name = tensor("concat_181")]; tensor x1_46_cast_fp16 = reshape(shape = concat_181, x = x0_48_cast_fp16)[name = tensor("x1_46_cast_fp16")]; tensor var_4000_begin_0 = const()[name = tensor("op_4000_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_4000_end_0 = const()[name = tensor("op_4000_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_4000_end_mask_0 = const()[name = tensor("op_4000_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_4000_cast_fp16 = slice_by_index(begin = var_4000_begin_0, end = var_4000_end_0, end_mask = var_4000_end_mask_0, x = x1_46_cast_fp16)[name = tensor("op_4000_cast_fp16")]; tensor concat_182_axis_0 = const()[name = tensor("concat_182_axis_0"), val = tensor(0)]; tensor concat_182_interleave_0 = const()[name = tensor("concat_182_interleave_0"), val = tensor(false)]; tensor gather_233_cast_uint16_to_int32 = cast(dtype = gather_233_cast_uint16_to_int32_dtype_0, x = gather_233_cast_uint16)[name = tensor("cast_14")]; tensor concat_182 = concat(axis = concat_182_axis_0, interleave = concat_182_interleave_0, values = (gather_230_cast_uint16_to_int32, gather_231, gather_232_cast_uint16_to_int32, gather_233_cast_uint16_to_int32))[name = tensor("concat_182")]; tensor matrix_bd_46_cast_fp16 = reshape(shape = concat_182, x = var_4000_cast_fp16)[name = tensor("matrix_bd_46_cast_fp16")]; tensor matrix_ac_46_transpose_x_0 = const()[name = tensor("matrix_ac_46_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_46_transpose_y_0 = const()[name = tensor("matrix_ac_46_transpose_y_0"), val = tensor(false)]; tensor transpose_282_perm_0 = const()[name = tensor("transpose_282_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_283_perm_0 = const()[name = tensor("transpose_283_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_283 = transpose(perm = transpose_283_perm_0, x = k_46_cast_fp16)[name = tensor("transpose_300")]; tensor transpose_282 = transpose(perm = transpose_282_perm_0, x = var_3984_cast_fp16)[name = tensor("transpose_301")]; tensor matrix_ac_46_cast_fp16 = matmul(transpose_x = matrix_ac_46_transpose_x_0, transpose_y = matrix_ac_46_transpose_y_0, x = transpose_282, y = transpose_283)[name = tensor("matrix_ac_46_cast_fp16")]; tensor var_4005_shape_cast_fp16 = shape(x = matrix_ac_46_cast_fp16)[name = tensor("op_4005_shape_cast_fp16")]; tensor gather_234_axis_0 = const()[name = tensor("gather_234_axis_0"), val = tensor(0)]; tensor gather_234_batch_dims_0 = const()[name = tensor("gather_234_batch_dims_0"), val = tensor(0)]; tensor gather_234_validate_indices_0 = const()[name = tensor("gather_234_validate_indices_0"), val = tensor(false)]; tensor var_4005_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_4005_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_234_to_uint16 = const()[name = tensor("select_234_to_uint16"), val = tensor(3)]; tensor var_4005_shape_cast_fp16_to_uint16 = cast(dtype = var_4005_shape_cast_fp16_to_uint16_dtype_0, x = var_4005_shape_cast_fp16)[name = tensor("cast_13")]; tensor gather_234_cast_uint16 = gather(axis = gather_234_axis_0, batch_dims = gather_234_batch_dims_0, indices = select_234_to_uint16, validate_indices = gather_234_validate_indices_0, x = var_4005_shape_cast_fp16_to_uint16)[name = tensor("gather_234_cast_uint16")]; tensor gather_234_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_234_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_183_values0_0 = const()[name = tensor("concat_183_values0_0"), val = tensor(0)]; tensor concat_183_values1_0 = const()[name = tensor("concat_183_values1_0"), val = tensor(8)]; tensor concat_183_values2_0 = const()[name = tensor("concat_183_values2_0"), val = tensor(0)]; tensor concat_183_axis_0 = const()[name = tensor("concat_183_axis_0"), val = tensor(0)]; tensor concat_183_interleave_0 = const()[name = tensor("concat_183_interleave_0"), val = tensor(false)]; tensor gather_234_cast_uint16_to_int32 = cast(dtype = gather_234_cast_uint16_to_int32_dtype_0, x = gather_234_cast_uint16)[name = tensor("cast_12")]; tensor concat_183 = concat(axis = concat_183_axis_0, interleave = concat_183_interleave_0, values = (concat_183_values0_0, concat_183_values1_0, concat_183_values2_0, gather_234_cast_uint16_to_int32))[name = tensor("concat_183")]; tensor matrix_bd0_46_begin_0 = const()[name = tensor("matrix_bd0_46_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_46_end_mask_0 = const()[name = tensor("matrix_bd0_46_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_46_cast_fp16 = slice_by_index(begin = matrix_bd0_46_begin_0, end = concat_183, end_mask = matrix_bd0_46_end_mask_0, x = matrix_bd_46_cast_fp16)[name = tensor("matrix_bd0_46_cast_fp16")]; tensor var_4010_cast_fp16 = add(x = matrix_ac_46_cast_fp16, y = matrix_bd0_46_cast_fp16)[name = tensor("op_4010_cast_fp16")]; tensor _inversed_scores_46_y_0_to_fp16 = const()[name = tensor("_inversed_scores_46_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_46_cast_fp16 = mul(x = var_4010_cast_fp16, y = _inversed_scores_46_y_0_to_fp16)[name = tensor("_inversed_scores_46_cast_fp16")]; tensor value_46_cast_fp16 = transpose(perm = value_46_perm_0, x = v_46_cast_fp16)[name = tensor("transpose_299")]; tensor var_4013_shape_cast_fp16 = shape(x = value_46_cast_fp16)[name = tensor("op_4013_shape_cast_fp16")]; tensor gather_235_axis_0 = const()[name = tensor("gather_235_axis_0"), val = tensor(0)]; tensor gather_235_batch_dims_0 = const()[name = tensor("gather_235_batch_dims_0"), val = tensor(0)]; tensor gather_235_validate_indices_0 = const()[name = tensor("gather_235_validate_indices_0"), val = tensor(false)]; tensor var_4013_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_4013_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_235_to_uint16 = const()[name = tensor("select_235_to_uint16"), val = tensor(0)]; tensor var_4013_shape_cast_fp16_to_uint16 = cast(dtype = var_4013_shape_cast_fp16_to_uint16_dtype_0, x = var_4013_shape_cast_fp16)[name = tensor("cast_11")]; tensor gather_235_cast_uint16 = gather(axis = gather_235_axis_0, batch_dims = gather_235_batch_dims_0, indices = select_235_to_uint16, validate_indices = gather_235_validate_indices_0, x = var_4013_shape_cast_fp16_to_uint16)[name = tensor("gather_235_cast_uint16")]; tensor gather_235_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_235_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_46_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_46_cast_fp16, cond = mask0_4)[name = tensor("scores0_46_cast_fp16")]; tensor var_4016_cast_fp16 = softmax(axis = var_21, x = scores0_46_cast_fp16)[name = tensor("op_4016_cast_fp16")]; tensor input_323_cast_fp16 = select(a = var_8_to_fp16, b = var_4016_cast_fp16, cond = mask0_4)[name = tensor("input_323_cast_fp16")]; tensor x2_46_transpose_x_0 = const()[name = tensor("x2_46_transpose_x_0"), val = tensor(false)]; tensor x2_46_transpose_y_0 = const()[name = tensor("x2_46_transpose_y_0"), val = tensor(false)]; tensor x2_46_cast_fp16 = matmul(transpose_x = x2_46_transpose_x_0, transpose_y = x2_46_transpose_y_0, x = input_323_cast_fp16, y = value_46_cast_fp16)[name = tensor("x2_46_cast_fp16")]; tensor var_4020_perm_0 = const()[name = tensor("op_4020_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_184_axis_0 = const()[name = tensor("concat_184_axis_0"), val = tensor(0)]; tensor concat_184_interleave_0 = const()[name = tensor("concat_184_interleave_0"), val = tensor(false)]; tensor gather_235_cast_uint16_to_int32 = cast(dtype = gather_235_cast_uint16_to_int32_dtype_0, x = gather_235_cast_uint16)[name = tensor("cast_10")]; tensor concat_184 = concat(axis = concat_184_axis_0, interleave = concat_184_interleave_0, values = (gather_235_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_184")]; tensor var_4020_cast_fp16 = transpose(perm = var_4020_perm_0, x = x2_46_cast_fp16)[name = tensor("transpose_298")]; tensor input0_313_cast_fp16 = reshape(shape = concat_184, x = var_4020_cast_fp16)[name = tensor("input0_313_cast_fp16")]; tensor encoder_layers_22_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291187840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291712192))), name = tensor("encoder_layers_22_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_205_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_self_attn_linear_out_weight_to_fp16_palettized, x = input0_313_cast_fp16)[name = tensor("linear_205_cast_fp16")]; tensor input0_315_cast_fp16 = add(x = input_321_cast_fp16, y = linear_205_cast_fp16)[name = tensor("input0_315_cast_fp16")]; tensor x_367_axes_0 = const()[name = tensor("x_367_axes_0"), val = tensor([-1])]; tensor encoder_layers_22_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_22_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291712320)))]; tensor encoder_layers_22_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_22_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291714432)))]; tensor x_367_cast_fp16 = layer_norm(axes = x_367_axes_0, beta = encoder_layers_22_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_22_norm_conv_weight_to_fp16, x = input0_315_cast_fp16)[name = tensor("x_367_cast_fp16")]; tensor input_325_perm_0 = const()[name = tensor("input_325_perm_0"), val = tensor([0, 2, 1])]; tensor input0_317_pad_type_0 = const()[name = tensor("input0_317_pad_type_0"), val = tensor("valid")]; tensor input0_317_strides_0 = const()[name = tensor("input0_317_strides_0"), val = tensor([1])]; tensor input0_317_pad_0 = const()[name = tensor("input0_317_pad_0"), val = tensor([0, 0])]; tensor input0_317_dilations_0 = const()[name = tensor("input0_317_dilations_0"), val = tensor([1])]; tensor input0_317_groups_0 = const()[name = tensor("input0_317_groups_0"), val = tensor(1)]; tensor encoder_layers_22_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(291716544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292765184))), name = tensor("encoder_layers_22_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_325_cast_fp16 = transpose(perm = input_325_perm_0, x = x_367_cast_fp16)[name = tensor("transpose_297")]; tensor input0_317_cast_fp16 = conv(dilations = input0_317_dilations_0, groups = input0_317_groups_0, pad = input0_317_pad_0, pad_type = input0_317_pad_type_0, strides = input0_317_strides_0, weight = encoder_layers_22_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_325_cast_fp16)[name = tensor("input0_317_cast_fp16")]; tensor x_369_split_num_splits_0 = const()[name = tensor("x_369_split_num_splits_0"), val = tensor(2)]; tensor x_369_split_axis_0 = const()[name = tensor("x_369_split_axis_0"), val = tensor(1)]; tensor x_369_split_cast_fp16_0, tensor x_369_split_cast_fp16_1 = split(axis = x_369_split_axis_0, num_splits = x_369_split_num_splits_0, x = input0_317_cast_fp16)[name = tensor("x_369_split_cast_fp16")]; tensor x_369_split_1_sigmoid_cast_fp16 = sigmoid(x = x_369_split_cast_fp16_1)[name = tensor("x_369_split_1_sigmoid_cast_fp16")]; tensor x_369_cast_fp16 = mul(x = x_369_split_cast_fp16_0, y = x_369_split_1_sigmoid_cast_fp16)[name = tensor("x_369_cast_fp16")]; tensor input0_319_cast_fp16 = select(a = var_8_to_fp16, b = x_369_cast_fp16, cond = var_457)[name = tensor("input0_319_cast_fp16")]; tensor input0_321_pad_0 = const()[name = tensor("input0_321_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_321_mode_0 = const()[name = tensor("input0_321_mode_0"), val = tensor("constant")]; tensor const_56_to_fp16 = const()[name = tensor("const_56_to_fp16"), val = tensor(0x0p+0)]; tensor input0_321_cast_fp16 = pad(constant_val = const_56_to_fp16, mode = input0_321_mode_0, pad = input0_321_pad_0, x = input0_319_cast_fp16)[name = tensor("input0_321_cast_fp16")]; tensor input1_94_pad_type_0 = const()[name = tensor("input1_94_pad_type_0"), val = tensor("valid")]; tensor input1_94_groups_0 = const()[name = tensor("input1_94_groups_0"), val = tensor(1024)]; tensor input1_94_strides_0 = const()[name = tensor("input1_94_strides_0"), val = tensor([1])]; tensor input1_94_pad_0 = const()[name = tensor("input1_94_pad_0"), val = tensor([0, 0])]; tensor input1_94_dilations_0 = const()[name = tensor("input1_94_dilations_0"), val = tensor([1])]; tensor const_103_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292765312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292769984))), name = tensor("const_103_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_104_to_fp16 = const()[name = tensor("const_104_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292770112)))]; tensor input_327_cast_fp16 = conv(bias = const_104_to_fp16, dilations = input1_94_dilations_0, groups = input1_94_groups_0, pad = input1_94_pad_0, pad_type = input1_94_pad_type_0, strides = input1_94_strides_0, weight = const_103_to_fp16_palettized, x = input0_321_cast_fp16)[name = tensor("input_327_cast_fp16")]; tensor var_4058_cast_fp16 = silu(x = input_327_cast_fp16)[name = tensor("op_4058_cast_fp16")]; tensor x_371_pad_type_0 = const()[name = tensor("x_371_pad_type_0"), val = tensor("valid")]; tensor x_371_strides_0 = const()[name = tensor("x_371_strides_0"), val = tensor([1])]; tensor x_371_pad_0 = const()[name = tensor("x_371_pad_0"), val = tensor([0, 0])]; tensor x_371_dilations_0 = const()[name = tensor("x_371_dilations_0"), val = tensor([1])]; tensor x_371_groups_0 = const()[name = tensor("x_371_groups_0"), val = tensor(1)]; tensor encoder_layers_22_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(292772224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293296576))), name = tensor("encoder_layers_22_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_371_cast_fp16 = conv(dilations = x_371_dilations_0, groups = x_371_groups_0, pad = x_371_pad_0, pad_type = x_371_pad_type_0, strides = x_371_strides_0, weight = encoder_layers_22_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_4058_cast_fp16)[name = tensor("x_371_cast_fp16")]; tensor var_4065_perm_0 = const()[name = tensor("op_4065_perm_0"), val = tensor([0, 2, 1])]; tensor var_4065_cast_fp16 = transpose(perm = var_4065_perm_0, x = x_371_cast_fp16)[name = tensor("transpose_296")]; tensor input1_96_cast_fp16 = add(x = input0_315_cast_fp16, y = var_4065_cast_fp16)[name = tensor("input1_96_cast_fp16")]; tensor input0_11_axes_0 = const()[name = tensor("input0_11_axes_0"), val = tensor([-1])]; tensor encoder_layers_22_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_22_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293296704)))]; tensor encoder_layers_22_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_22_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293298816)))]; tensor input0_11_cast_fp16 = layer_norm(axes = input0_11_axes_0, beta = encoder_layers_22_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_22_norm_feed_forward2_weight_to_fp16, x = input1_96_cast_fp16)[name = tensor("input0_11_cast_fp16")]; tensor encoder_layers_22_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(293300928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295398144))), name = tensor("encoder_layers_22_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_206_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_22_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_11_cast_fp16)[name = tensor("linear_206_cast_fp16")]; tensor var_4076_cast_fp16 = silu(x = linear_206_cast_fp16)[name = tensor("op_4076_cast_fp16")]; tensor encoder_layers_22_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(295398272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297495488))), name = tensor("encoder_layers_22_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_207_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_22_feed_forward2_linear2_weight_to_fp16_palettized, x = var_4076_cast_fp16)[name = tensor("linear_207_cast_fp16")]; tensor var_4081_to_fp16 = const()[name = tensor("op_4081_to_fp16"), val = tensor(0x1p-1)]; tensor var_4082_cast_fp16 = mul(x = linear_207_cast_fp16, y = var_4081_to_fp16)[name = tensor("op_4082_cast_fp16")]; tensor input2_48_cast_fp16 = add(x = input1_96_cast_fp16, y = var_4082_cast_fp16)[name = tensor("input2_48_cast_fp16")]; tensor input0_323_axes_0 = const()[name = tensor("input0_323_axes_0"), val = tensor([-1])]; tensor encoder_layers_22_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_22_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297495616)))]; tensor encoder_layers_22_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_22_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297497728)))]; tensor input0_323_cast_fp16 = layer_norm(axes = input0_323_axes_0, beta = encoder_layers_22_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_22_norm_out_weight_to_fp16, x = input2_48_cast_fp16)[name = tensor("input0_323_cast_fp16")]; tensor input_4_axes_0 = const()[name = tensor("input_4_axes_0"), val = tensor([-1])]; tensor encoder_layers_23_norm_feed_forward1_weight_to_fp16 = const()[name = tensor("encoder_layers_23_norm_feed_forward1_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297499840)))]; tensor encoder_layers_23_norm_feed_forward1_bias_to_fp16 = const()[name = tensor("encoder_layers_23_norm_feed_forward1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297501952)))]; tensor input_4_cast_fp16 = layer_norm(axes = input_4_axes_0, beta = encoder_layers_23_norm_feed_forward1_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_23_norm_feed_forward1_weight_to_fp16, x = input0_323_cast_fp16)[name = tensor("input_4_cast_fp16")]; tensor encoder_layers_23_feed_forward1_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(297504064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299601280))), name = tensor("encoder_layers_23_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_208_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_23_feed_forward1_linear1_weight_to_fp16_palettized, x = input_4_cast_fp16)[name = tensor("linear_208_cast_fp16")]; tensor var_4105_cast_fp16 = silu(x = linear_208_cast_fp16)[name = tensor("op_4105_cast_fp16")]; tensor encoder_layers_23_feed_forward1_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(299601408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301698624))), name = tensor("encoder_layers_23_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_209_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_feed_forward1_linear2_weight_to_fp16_palettized, x = var_4105_cast_fp16)[name = tensor("linear_209_cast_fp16")]; tensor var_4110_to_fp16 = const()[name = tensor("op_4110_to_fp16"), val = tensor(0x1p-1)]; tensor var_4111_cast_fp16 = mul(x = linear_209_cast_fp16, y = var_4110_to_fp16)[name = tensor("op_4111_cast_fp16")]; tensor input_8_cast_fp16 = add(x = input0_323_cast_fp16, y = var_4111_cast_fp16)[name = tensor("input_8_cast_fp16")]; tensor query_1_axes_0 = const()[name = tensor("query_1_axes_0"), val = tensor([-1])]; tensor encoder_layers_23_norm_self_att_weight_to_fp16 = const()[name = tensor("encoder_layers_23_norm_self_att_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301698752)))]; tensor encoder_layers_23_norm_self_att_bias_to_fp16 = const()[name = tensor("encoder_layers_23_norm_self_att_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301700864)))]; tensor query_1_cast_fp16 = layer_norm(axes = query_1_axes_0, beta = encoder_layers_23_norm_self_att_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_23_norm_self_att_weight_to_fp16, x = input_8_cast_fp16)[name = tensor("query_1_cast_fp16")]; tensor var_4124_shape_cast_fp16 = shape(x = query_1_cast_fp16)[name = tensor("op_4124_shape_cast_fp16")]; tensor gather_236_axis_0 = const()[name = tensor("gather_236_axis_0"), val = tensor(0)]; tensor gather_236_batch_dims_0 = const()[name = tensor("gather_236_batch_dims_0"), val = tensor(0)]; tensor gather_236_validate_indices_0 = const()[name = tensor("gather_236_validate_indices_0"), val = tensor(false)]; tensor var_4124_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_4124_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_236_to_uint16 = const()[name = tensor("select_236_to_uint16"), val = tensor(0)]; tensor var_4124_shape_cast_fp16_to_uint16 = cast(dtype = var_4124_shape_cast_fp16_to_uint16_dtype_0, x = var_4124_shape_cast_fp16)[name = tensor("cast_9")]; tensor gather_236_cast_uint16 = gather(axis = gather_236_axis_0, batch_dims = gather_236_batch_dims_0, indices = select_236_to_uint16, validate_indices = gather_236_validate_indices_0, x = var_4124_shape_cast_fp16_to_uint16)[name = tensor("gather_236_cast_uint16")]; tensor gather_236_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_236_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor encoder_layers_23_self_attn_linear_q_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(301702976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302227328))), name = tensor("encoder_layers_23_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_210_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_self_attn_linear_q_weight_to_fp16_palettized, x = query_1_cast_fp16)[name = tensor("linear_210_cast_fp16")]; tensor concat_185_axis_0 = const()[name = tensor("concat_185_axis_0"), val = tensor(0)]; tensor concat_185_interleave_0 = const()[name = tensor("concat_185_interleave_0"), val = tensor(false)]; tensor gather_236_cast_uint16_to_int32 = cast(dtype = gather_236_cast_uint16_to_int32_dtype_0, x = gather_236_cast_uint16)[name = tensor("cast_8")]; tensor concat_185 = concat(axis = concat_185_axis_0, interleave = concat_185_interleave_0, values = (gather_236_cast_uint16_to_int32, var_21, var_12, var_11))[name = tensor("concat_185")]; tensor q_1_cast_fp16 = reshape(shape = concat_185, x = linear_210_cast_fp16)[name = tensor("q_1_cast_fp16")]; tensor encoder_layers_23_self_attn_linear_k_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302227456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302751808))), name = tensor("encoder_layers_23_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_211_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_self_attn_linear_k_weight_to_fp16_palettized, x = query_1_cast_fp16)[name = tensor("linear_211_cast_fp16")]; tensor k_1_cast_fp16 = reshape(shape = concat_185, x = linear_211_cast_fp16)[name = tensor("k_1_cast_fp16")]; tensor encoder_layers_23_self_attn_linear_v_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(302751936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303276288))), name = tensor("encoder_layers_23_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_212_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_self_attn_linear_v_weight_to_fp16_palettized, x = query_1_cast_fp16)[name = tensor("linear_212_cast_fp16")]; tensor v_1_cast_fp16 = reshape(shape = concat_185, x = linear_212_cast_fp16)[name = tensor("v_1_cast_fp16")]; tensor value_1_perm_0 = const()[name = tensor("value_1_perm_0"), val = tensor([0, 2, -3, -1])]; tensor encoder_layers_23_self_attn_linear_pos_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303276416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303800768))), name = tensor("encoder_layers_23_self_attn_linear_pos_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_213_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_self_attn_linear_pos_weight_to_fp16_palettized, x = pos_emb_1_cast_fp16)[name = tensor("linear_213_cast_fp16")]; tensor var_4144 = const()[name = tensor("op_4144"), val = tensor([1, -1, 8, 128])]; tensor p_1_cast_fp16 = reshape(shape = var_4144, x = linear_213_cast_fp16)[name = tensor("p_1_cast_fp16")]; tensor encoder_layers_23_self_attn_pos_bias_u_to_fp16 = const()[name = tensor("encoder_layers_23_self_attn_pos_bias_u_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303800896)))]; tensor var_4147_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_layers_23_self_attn_pos_bias_u_to_fp16)[name = tensor("op_4147_cast_fp16")]; tensor encoder_layers_23_self_attn_pos_bias_v_to_fp16 = const()[name = tensor("encoder_layers_23_self_attn_pos_bias_v_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303803008)))]; tensor var_4149_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_layers_23_self_attn_pos_bias_v_to_fp16)[name = tensor("op_4149_cast_fp16")]; tensor x_4_transpose_x_0 = const()[name = tensor("x_4_transpose_x_0"), val = tensor(false)]; tensor x_4_transpose_y_0 = const()[name = tensor("x_4_transpose_y_0"), val = tensor(false)]; tensor transpose_284_perm_0 = const()[name = tensor("transpose_284_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_285_perm_0 = const()[name = tensor("transpose_285_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_285 = transpose(perm = transpose_285_perm_0, x = p_1_cast_fp16)[name = tensor("transpose_294")]; tensor transpose_284 = transpose(perm = transpose_284_perm_0, x = var_4149_cast_fp16)[name = tensor("transpose_295")]; tensor x_4_cast_fp16 = matmul(transpose_x = x_4_transpose_x_0, transpose_y = x_4_transpose_y_0, x = transpose_284, y = transpose_285)[name = tensor("x_4_cast_fp16")]; tensor var_4153_shape_cast_fp16 = shape(x = x_4_cast_fp16)[name = tensor("op_4153_shape_cast_fp16")]; tensor gather_238_axis_0 = const()[name = tensor("gather_238_axis_0"), val = tensor(0)]; tensor gather_238_batch_dims_0 = const()[name = tensor("gather_238_batch_dims_0"), val = tensor(0)]; tensor gather_238_validate_indices_0 = const()[name = tensor("gather_238_validate_indices_0"), val = tensor(false)]; tensor var_4153_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_4153_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_238_to_uint16 = const()[name = tensor("select_238_to_uint16"), val = tensor(0)]; tensor var_4153_shape_cast_fp16_to_uint16 = cast(dtype = var_4153_shape_cast_fp16_to_uint16_dtype_0, x = var_4153_shape_cast_fp16)[name = tensor("cast_7")]; tensor gather_238_cast_uint16 = gather(axis = gather_238_axis_0, batch_dims = gather_238_batch_dims_0, indices = select_238_to_uint16, validate_indices = gather_238_validate_indices_0, x = var_4153_shape_cast_fp16_to_uint16)[name = tensor("gather_238_cast_uint16")]; tensor gather_238_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_238_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_239 = const()[name = tensor("gather_239"), val = tensor(8)]; tensor gather_240_axis_0 = const()[name = tensor("gather_240_axis_0"), val = tensor(0)]; tensor gather_240_batch_dims_0 = const()[name = tensor("gather_240_batch_dims_0"), val = tensor(0)]; tensor gather_240_validate_indices_0 = const()[name = tensor("gather_240_validate_indices_0"), val = tensor(false)]; tensor select_240_to_uint16 = const()[name = tensor("select_240_to_uint16"), val = tensor(2)]; tensor gather_240_cast_uint16 = gather(axis = gather_240_axis_0, batch_dims = gather_240_batch_dims_0, indices = select_240_to_uint16, validate_indices = gather_240_validate_indices_0, x = var_4153_shape_cast_fp16_to_uint16)[name = tensor("gather_240_cast_uint16")]; tensor gather_240_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_240_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor gather_241_axis_0 = const()[name = tensor("gather_241_axis_0"), val = tensor(0)]; tensor gather_241_batch_dims_0 = const()[name = tensor("gather_241_batch_dims_0"), val = tensor(0)]; tensor gather_241_validate_indices_0 = const()[name = tensor("gather_241_validate_indices_0"), val = tensor(false)]; tensor select_241_to_uint16 = const()[name = tensor("select_241_to_uint16"), val = tensor(3)]; tensor gather_241_cast_uint16 = gather(axis = gather_241_axis_0, batch_dims = gather_241_batch_dims_0, indices = select_241_to_uint16, validate_indices = gather_241_validate_indices_0, x = var_4153_shape_cast_fp16_to_uint16)[name = tensor("gather_241_cast_uint16")]; tensor gather_241_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_241_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor x0_1_pad_0 = const()[name = tensor("x0_1_pad_0"), val = tensor([0, 0, 0, 0, 0, 0, 1, 0])]; tensor x0_1_mode_0 = const()[name = tensor("x0_1_mode_0"), val = tensor("constant")]; tensor const_57_to_fp16 = const()[name = tensor("const_57_to_fp16"), val = tensor(0x0p+0)]; tensor x0_1_cast_fp16 = pad(constant_val = const_57_to_fp16, mode = x0_1_mode_0, pad = x0_1_pad_0, x = x_4_cast_fp16)[name = tensor("x0_1_cast_fp16")]; tensor concat_188_axis_0 = const()[name = tensor("concat_188_axis_0"), val = tensor(0)]; tensor concat_188_interleave_0 = const()[name = tensor("concat_188_interleave_0"), val = tensor(false)]; tensor gather_238_cast_uint16_to_int32 = cast(dtype = gather_238_cast_uint16_to_int32_dtype_0, x = gather_238_cast_uint16)[name = tensor("cast_5")]; tensor gather_240_cast_uint16_to_int32 = cast(dtype = gather_240_cast_uint16_to_int32_dtype_0, x = gather_240_cast_uint16)[name = tensor("cast_6")]; tensor concat_188 = concat(axis = concat_188_axis_0, interleave = concat_188_interleave_0, values = (gather_238_cast_uint16_to_int32, gather_239, var_21, gather_240_cast_uint16_to_int32))[name = tensor("concat_188")]; tensor x1_1_cast_fp16 = reshape(shape = concat_188, x = x0_1_cast_fp16)[name = tensor("x1_1_cast_fp16")]; tensor var_4163_begin_0 = const()[name = tensor("op_4163_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_4163_end_0 = const()[name = tensor("op_4163_end_0"), val = tensor([0, 8, 0, 0])]; tensor var_4163_end_mask_0 = const()[name = tensor("op_4163_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_4163_cast_fp16 = slice_by_index(begin = var_4163_begin_0, end = var_4163_end_0, end_mask = var_4163_end_mask_0, x = x1_1_cast_fp16)[name = tensor("op_4163_cast_fp16")]; tensor concat_189_axis_0 = const()[name = tensor("concat_189_axis_0"), val = tensor(0)]; tensor concat_189_interleave_0 = const()[name = tensor("concat_189_interleave_0"), val = tensor(false)]; tensor gather_241_cast_uint16_to_int32 = cast(dtype = gather_241_cast_uint16_to_int32_dtype_0, x = gather_241_cast_uint16)[name = tensor("cast_4")]; tensor concat_189 = concat(axis = concat_189_axis_0, interleave = concat_189_interleave_0, values = (gather_238_cast_uint16_to_int32, gather_239, gather_240_cast_uint16_to_int32, gather_241_cast_uint16_to_int32))[name = tensor("concat_189")]; tensor matrix_bd_1_cast_fp16 = reshape(shape = concat_189, x = var_4163_cast_fp16)[name = tensor("matrix_bd_1_cast_fp16")]; tensor matrix_ac_1_transpose_x_0 = const()[name = tensor("matrix_ac_1_transpose_x_0"), val = tensor(false)]; tensor matrix_ac_1_transpose_y_0 = const()[name = tensor("matrix_ac_1_transpose_y_0"), val = tensor(false)]; tensor transpose_286_perm_0 = const()[name = tensor("transpose_286_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_287_perm_0 = const()[name = tensor("transpose_287_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_287 = transpose(perm = transpose_287_perm_0, x = k_1_cast_fp16)[name = tensor("transpose_292")]; tensor transpose_286 = transpose(perm = transpose_286_perm_0, x = var_4147_cast_fp16)[name = tensor("transpose_293")]; tensor matrix_ac_1_cast_fp16 = matmul(transpose_x = matrix_ac_1_transpose_x_0, transpose_y = matrix_ac_1_transpose_y_0, x = transpose_286, y = transpose_287)[name = tensor("matrix_ac_1_cast_fp16")]; tensor var_4168_shape_cast_fp16 = shape(x = matrix_ac_1_cast_fp16)[name = tensor("op_4168_shape_cast_fp16")]; tensor gather_242_axis_0 = const()[name = tensor("gather_242_axis_0"), val = tensor(0)]; tensor gather_242_batch_dims_0 = const()[name = tensor("gather_242_batch_dims_0"), val = tensor(0)]; tensor gather_242_validate_indices_0 = const()[name = tensor("gather_242_validate_indices_0"), val = tensor(false)]; tensor var_4168_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_4168_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_242_to_uint16 = const()[name = tensor("select_242_to_uint16"), val = tensor(3)]; tensor var_4168_shape_cast_fp16_to_uint16 = cast(dtype = var_4168_shape_cast_fp16_to_uint16_dtype_0, x = var_4168_shape_cast_fp16)[name = tensor("cast_3")]; tensor gather_242_cast_uint16 = gather(axis = gather_242_axis_0, batch_dims = gather_242_batch_dims_0, indices = select_242_to_uint16, validate_indices = gather_242_validate_indices_0, x = var_4168_shape_cast_fp16_to_uint16)[name = tensor("gather_242_cast_uint16")]; tensor gather_242_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_242_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_190_values0_0 = const()[name = tensor("concat_190_values0_0"), val = tensor(0)]; tensor concat_190_values1_0 = const()[name = tensor("concat_190_values1_0"), val = tensor(8)]; tensor concat_190_values2_0 = const()[name = tensor("concat_190_values2_0"), val = tensor(0)]; tensor concat_190_axis_0 = const()[name = tensor("concat_190_axis_0"), val = tensor(0)]; tensor concat_190_interleave_0 = const()[name = tensor("concat_190_interleave_0"), val = tensor(false)]; tensor gather_242_cast_uint16_to_int32 = cast(dtype = gather_242_cast_uint16_to_int32_dtype_0, x = gather_242_cast_uint16)[name = tensor("cast_2")]; tensor concat_190 = concat(axis = concat_190_axis_0, interleave = concat_190_interleave_0, values = (concat_190_values0_0, concat_190_values1_0, concat_190_values2_0, gather_242_cast_uint16_to_int32))[name = tensor("concat_190")]; tensor matrix_bd0_1_begin_0 = const()[name = tensor("matrix_bd0_1_begin_0"), val = tensor([0, 0, 0, 0])]; tensor matrix_bd0_1_end_mask_0 = const()[name = tensor("matrix_bd0_1_end_mask_0"), val = tensor([true, true, true, false])]; tensor matrix_bd0_1_cast_fp16 = slice_by_index(begin = matrix_bd0_1_begin_0, end = concat_190, end_mask = matrix_bd0_1_end_mask_0, x = matrix_bd_1_cast_fp16)[name = tensor("matrix_bd0_1_cast_fp16")]; tensor var_4173_cast_fp16 = add(x = matrix_ac_1_cast_fp16, y = matrix_bd0_1_cast_fp16)[name = tensor("op_4173_cast_fp16")]; tensor _inversed_scores_1_y_0_to_fp16 = const()[name = tensor("_inversed_scores_1_y_0_to_fp16"), val = tensor(0x1.6ap-4)]; tensor _inversed_scores_1_cast_fp16 = mul(x = var_4173_cast_fp16, y = _inversed_scores_1_y_0_to_fp16)[name = tensor("_inversed_scores_1_cast_fp16")]; tensor value_1_cast_fp16 = transpose(perm = value_1_perm_0, x = v_1_cast_fp16)[name = tensor("transpose_291")]; tensor var_4176_shape_cast_fp16 = shape(x = value_1_cast_fp16)[name = tensor("op_4176_shape_cast_fp16")]; tensor gather_243_axis_0 = const()[name = tensor("gather_243_axis_0"), val = tensor(0)]; tensor gather_243_batch_dims_0 = const()[name = tensor("gather_243_batch_dims_0"), val = tensor(0)]; tensor gather_243_validate_indices_0 = const()[name = tensor("gather_243_validate_indices_0"), val = tensor(false)]; tensor var_4176_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_4176_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_243_to_uint16 = const()[name = tensor("select_243_to_uint16"), val = tensor(0)]; tensor var_4176_shape_cast_fp16_to_uint16 = cast(dtype = var_4176_shape_cast_fp16_to_uint16_dtype_0, x = var_4176_shape_cast_fp16)[name = tensor("cast_1")]; tensor gather_243_cast_uint16 = gather(axis = gather_243_axis_0, batch_dims = gather_243_batch_dims_0, indices = select_243_to_uint16, validate_indices = gather_243_validate_indices_0, x = var_4176_shape_cast_fp16_to_uint16)[name = tensor("gather_243_cast_uint16")]; tensor gather_243_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_243_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor scores0_1_cast_fp16 = select(a = var_9_to_fp16, b = _inversed_scores_1_cast_fp16, cond = mask0_4)[name = tensor("scores0_1_cast_fp16")]; tensor var_4179_cast_fp16 = softmax(axis = var_21, x = scores0_1_cast_fp16)[name = tensor("op_4179_cast_fp16")]; tensor input_10_cast_fp16 = select(a = var_8_to_fp16, b = var_4179_cast_fp16, cond = mask0_4)[name = tensor("input_10_cast_fp16")]; tensor x2_1_transpose_x_0 = const()[name = tensor("x2_1_transpose_x_0"), val = tensor(false)]; tensor x2_1_transpose_y_0 = const()[name = tensor("x2_1_transpose_y_0"), val = tensor(false)]; tensor x2_1_cast_fp16 = matmul(transpose_x = x2_1_transpose_x_0, transpose_y = x2_1_transpose_y_0, x = input_10_cast_fp16, y = value_1_cast_fp16)[name = tensor("x2_1_cast_fp16")]; tensor var_4183_perm_0 = const()[name = tensor("op_4183_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_191_axis_0 = const()[name = tensor("concat_191_axis_0"), val = tensor(0)]; tensor concat_191_interleave_0 = const()[name = tensor("concat_191_interleave_0"), val = tensor(false)]; tensor gather_243_cast_uint16_to_int32 = cast(dtype = gather_243_cast_uint16_to_int32_dtype_0, x = gather_243_cast_uint16)[name = tensor("cast_0")]; tensor concat_191 = concat(axis = concat_191_axis_0, interleave = concat_191_interleave_0, values = (gather_243_cast_uint16_to_int32, var_21, var_6))[name = tensor("concat_191")]; tensor var_4183_cast_fp16 = transpose(perm = var_4183_perm_0, x = x2_1_cast_fp16)[name = tensor("transpose_290")]; tensor input0_7_cast_fp16 = reshape(shape = concat_191, x = var_4183_cast_fp16)[name = tensor("input0_7_cast_fp16")]; tensor encoder_layers_23_self_attn_linear_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(303805120))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304329472))), name = tensor("encoder_layers_23_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([1024, 1024])]; tensor linear_214_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_self_attn_linear_out_weight_to_fp16_palettized, x = input0_7_cast_fp16)[name = tensor("linear_214_cast_fp16")]; tensor input0_5_cast_fp16 = add(x = input_8_cast_fp16, y = linear_214_cast_fp16)[name = tensor("input0_5_cast_fp16")]; tensor x_10_axes_0 = const()[name = tensor("x_10_axes_0"), val = tensor([-1])]; tensor encoder_layers_23_norm_conv_weight_to_fp16 = const()[name = tensor("encoder_layers_23_norm_conv_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304329600)))]; tensor encoder_layers_23_norm_conv_bias_to_fp16 = const()[name = tensor("encoder_layers_23_norm_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304331712)))]; tensor x_10_cast_fp16 = layer_norm(axes = x_10_axes_0, beta = encoder_layers_23_norm_conv_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_23_norm_conv_weight_to_fp16, x = input0_5_cast_fp16)[name = tensor("x_10_cast_fp16")]; tensor input_2_perm_0 = const()[name = tensor("input_2_perm_0"), val = tensor([0, 2, 1])]; tensor input0_4_pad_type_0 = const()[name = tensor("input0_4_pad_type_0"), val = tensor("valid")]; tensor input0_4_strides_0 = const()[name = tensor("input0_4_strides_0"), val = tensor([1])]; tensor input0_4_pad_0 = const()[name = tensor("input0_4_pad_0"), val = tensor([0, 0])]; tensor input0_4_dilations_0 = const()[name = tensor("input0_4_dilations_0"), val = tensor([1])]; tensor input0_4_groups_0 = const()[name = tensor("input0_4_groups_0"), val = tensor(1)]; tensor encoder_layers_23_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(304333824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305382464))), name = tensor("encoder_layers_23_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([2048, 1024, 1])]; tensor input_2_cast_fp16 = transpose(perm = input_2_perm_0, x = x_10_cast_fp16)[name = tensor("transpose_289")]; tensor input0_4_cast_fp16 = conv(dilations = input0_4_dilations_0, groups = input0_4_groups_0, pad = input0_4_pad_0, pad_type = input0_4_pad_type_0, strides = input0_4_strides_0, weight = encoder_layers_23_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_2_cast_fp16)[name = tensor("input0_4_cast_fp16")]; tensor x_2_split_num_splits_0 = const()[name = tensor("x_2_split_num_splits_0"), val = tensor(2)]; tensor x_2_split_axis_0 = const()[name = tensor("x_2_split_axis_0"), val = tensor(1)]; tensor x_2_split_cast_fp16_0, tensor x_2_split_cast_fp16_1 = split(axis = x_2_split_axis_0, num_splits = x_2_split_num_splits_0, x = input0_4_cast_fp16)[name = tensor("x_2_split_cast_fp16")]; tensor x_2_split_1_sigmoid_cast_fp16 = sigmoid(x = x_2_split_cast_fp16_1)[name = tensor("x_2_split_1_sigmoid_cast_fp16")]; tensor x_2_cast_fp16 = mul(x = x_2_split_cast_fp16_0, y = x_2_split_1_sigmoid_cast_fp16)[name = tensor("x_2_cast_fp16")]; tensor input0_2_cast_fp16 = select(a = var_8_to_fp16, b = x_2_cast_fp16, cond = var_457)[name = tensor("input0_2_cast_fp16")]; tensor input0_9_pad_0 = const()[name = tensor("input0_9_pad_0"), val = tensor([0, 0, 0, 0, 4, 4])]; tensor input0_9_mode_0 = const()[name = tensor("input0_9_mode_0"), val = tensor("constant")]; tensor const_58_to_fp16 = const()[name = tensor("const_58_to_fp16"), val = tensor(0x0p+0)]; tensor input0_9_cast_fp16 = pad(constant_val = const_58_to_fp16, mode = input0_9_mode_0, pad = input0_9_pad_0, x = input0_2_cast_fp16)[name = tensor("input0_9_cast_fp16")]; tensor input1_1_pad_type_0 = const()[name = tensor("input1_1_pad_type_0"), val = tensor("valid")]; tensor input1_1_groups_0 = const()[name = tensor("input1_1_groups_0"), val = tensor(1024)]; tensor input1_1_strides_0 = const()[name = tensor("input1_1_strides_0"), val = tensor([1])]; tensor input1_1_pad_0 = const()[name = tensor("input1_1_pad_0"), val = tensor([0, 0])]; tensor input1_1_dilations_0 = const()[name = tensor("input1_1_dilations_0"), val = tensor([1])]; tensor const_105_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305382592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305387264))), name = tensor("const_105_to_fp16_palettized"), shape = tensor([1024, 1, 9])]; tensor const_106_to_fp16 = const()[name = tensor("const_106_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305387392)))]; tensor input_12_cast_fp16 = conv(bias = const_106_to_fp16, dilations = input1_1_dilations_0, groups = input1_1_groups_0, pad = input1_1_pad_0, pad_type = input1_1_pad_type_0, strides = input1_1_strides_0, weight = const_105_to_fp16_palettized, x = input0_9_cast_fp16)[name = tensor("input_12_cast_fp16")]; tensor var_4221_cast_fp16 = silu(x = input_12_cast_fp16)[name = tensor("op_4221_cast_fp16")]; tensor x_12_pad_type_0 = const()[name = tensor("x_12_pad_type_0"), val = tensor("valid")]; tensor x_12_strides_0 = const()[name = tensor("x_12_strides_0"), val = tensor([1])]; tensor x_12_pad_0 = const()[name = tensor("x_12_pad_0"), val = tensor([0, 0])]; tensor x_12_dilations_0 = const()[name = tensor("x_12_dilations_0"), val = tensor([1])]; tensor x_12_groups_0 = const()[name = tensor("x_12_groups_0"), val = tensor(1)]; tensor encoder_layers_23_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305389504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305913856))), name = tensor("encoder_layers_23_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([1024, 1024, 1])]; tensor x_12_cast_fp16 = conv(dilations = x_12_dilations_0, groups = x_12_groups_0, pad = x_12_pad_0, pad_type = x_12_pad_type_0, strides = x_12_strides_0, weight = encoder_layers_23_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_4221_cast_fp16)[name = tensor("x_12_cast_fp16")]; tensor var_4228_perm_0 = const()[name = tensor("op_4228_perm_0"), val = tensor([0, 2, 1])]; tensor var_4228_cast_fp16 = transpose(perm = var_4228_perm_0, x = x_12_cast_fp16)[name = tensor("transpose_288")]; tensor input1_2_cast_fp16 = add(x = input0_5_cast_fp16, y = var_4228_cast_fp16)[name = tensor("input1_2_cast_fp16")]; tensor input0_1_axes_0 = const()[name = tensor("input0_1_axes_0"), val = tensor([-1])]; tensor encoder_layers_23_norm_feed_forward2_weight_to_fp16 = const()[name = tensor("encoder_layers_23_norm_feed_forward2_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305913984)))]; tensor encoder_layers_23_norm_feed_forward2_bias_to_fp16 = const()[name = tensor("encoder_layers_23_norm_feed_forward2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305916096)))]; tensor input0_1_cast_fp16 = layer_norm(axes = input0_1_axes_0, beta = encoder_layers_23_norm_feed_forward2_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_23_norm_feed_forward2_weight_to_fp16, x = input1_2_cast_fp16)[name = tensor("input0_1_cast_fp16")]; tensor encoder_layers_23_feed_forward2_linear1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(305918208))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308015424))), name = tensor("encoder_layers_23_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([4096, 1024])]; tensor linear_215_cast_fp16 = linear(bias = linear_1_bias_0_to_fp16, weight = encoder_layers_23_feed_forward2_linear1_weight_to_fp16_palettized, x = input0_1_cast_fp16)[name = tensor("linear_215_cast_fp16")]; tensor var_4239_cast_fp16 = silu(x = linear_215_cast_fp16)[name = tensor("op_4239_cast_fp16")]; tensor encoder_layers_23_feed_forward2_linear2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(308015552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310112768))), name = tensor("encoder_layers_23_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([1024, 4096])]; tensor linear_216_cast_fp16 = linear(bias = linear_2_bias_0_to_fp16, weight = encoder_layers_23_feed_forward2_linear2_weight_to_fp16_palettized, x = var_4239_cast_fp16)[name = tensor("linear_216_cast_fp16")]; tensor var_4244_to_fp16 = const()[name = tensor("op_4244_to_fp16"), val = tensor(0x1p-1)]; tensor var_4245_cast_fp16 = mul(x = linear_216_cast_fp16, y = var_4244_to_fp16)[name = tensor("op_4245_cast_fp16")]; tensor input2_1_cast_fp16 = add(x = input1_2_cast_fp16, y = var_4245_cast_fp16)[name = tensor("input2_1_cast_fp16")]; tensor audio_signal_1_axes_0 = const()[name = tensor("audio_signal_1_axes_0"), val = tensor([-1])]; tensor encoder_layers_23_norm_out_weight_to_fp16 = const()[name = tensor("encoder_layers_23_norm_out_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310112896)))]; tensor encoder_layers_23_norm_out_bias_to_fp16 = const()[name = tensor("encoder_layers_23_norm_out_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(310115008)))]; tensor encoded = layer_norm(axes = audio_signal_1_axes_0, beta = encoder_layers_23_norm_out_bias_to_fp16, epsilon = var_7_to_fp16, gamma = encoder_layers_23_norm_out_weight_to_fp16, x = input2_1_cast_fp16)[name = tensor("audio_signal_1_cast_fp16")]; } -> (encoded, encoded_length); }