program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}})] { func main(tensor audio_length, tensor audio_signal, tensor cache_last_channel, tensor cache_last_channel_len, tensor cache_last_time, tensor pre_cache) { tensor var_9 = const()[name = tensor("op_9"), val = tensor(2)]; tensor value_3_interleave_0 = const()[name = tensor("value_3_interleave_0"), val = tensor(false)]; tensor pre_cache_to_fp16_dtype_0 = const()[name = tensor("pre_cache_to_fp16_dtype_0"), val = tensor("fp16")]; tensor audio_signal_to_fp16_dtype_0 = const()[name = tensor("audio_signal_to_fp16_dtype_0"), val = tensor("fp16")]; tensor pre_cache_to_fp16 = cast(dtype = pre_cache_to_fp16_dtype_0, x = pre_cache)[name = tensor("cast_14")]; tensor audio_signal_to_fp16 = cast(dtype = audio_signal_to_fp16_dtype_0, x = audio_signal)[name = tensor("cast_15")]; tensor value_3_cast_fp16 = concat(axis = var_9, interleave = value_3_interleave_0, values = (pre_cache_to_fp16, audio_signal_to_fp16))[name = tensor("value_3_cast_fp16")]; tensor var_19 = const()[name = tensor("op_19"), val = tensor(9)]; tensor value0_1 = add(x = audio_length, y = var_19)[name = tensor("value0_1")]; tensor var_23_begin_0 = const()[name = tensor("op_23_begin_0"), val = tensor([0, 0, 55])]; tensor var_23_end_0 = const()[name = tensor("op_23_end_0"), val = tensor([1, 128, 64])]; tensor var_23_end_mask_0 = const()[name = tensor("op_23_end_mask_0"), val = tensor([true, true, true])]; tensor new_pre_cache = slice_by_index(begin = var_23_begin_0, end = var_23_end_0, end_mask = var_23_end_mask_0, x = audio_signal_to_fp16)[name = tensor("op_23_cast_fp16")]; tensor var_47 = const()[name = tensor("op_47"), val = tensor(-1)]; tensor var_55 = const()[name = tensor("op_55"), val = tensor(1)]; tensor x_3_perm_0 = const()[name = tensor("x_3_perm_0"), val = tensor([0, 2, 1])]; tensor tensor_2_axes_0 = const()[name = tensor("tensor_2_axes_0"), val = tensor([1])]; tensor x_3_cast_fp16 = transpose(perm = x_3_perm_0, x = value_3_cast_fp16)[name = tensor("transpose_257")]; tensor tensor_2_cast_fp16 = expand_dims(axes = tensor_2_axes_0, x = x_3_cast_fp16)[name = tensor("tensor_2_cast_fp16")]; tensor expand_dims_0 = const()[name = tensor("expand_dims_0"), val = tensor([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72]])]; tensor var_115_axes_0 = const()[name = tensor("op_115_axes_0"), val = tensor([1])]; tensor var_115 = expand_dims(axes = var_115_axes_0, x = value0_1)[name = tensor("op_115")]; tensor time_mask_1 = less(x = expand_dims_0, y = var_115)[name = tensor("time_mask_1")]; tensor var_117_axes_0 = const()[name = tensor("op_117_axes_0"), val = tensor([-1])]; tensor var_117 = expand_dims(axes = var_117_axes_0, x = time_mask_1)[name = tensor("op_117")]; tensor var_119_reps_0 = const()[name = tensor("op_119_reps_0"), val = tensor([1, 1, 128])]; tensor var_119 = tile(reps = var_119_reps_0, x = var_117)[name = tensor("op_119")]; tensor var_125_axes_0 = const()[name = tensor("op_125_axes_0"), val = tensor([1])]; tensor cast_2_to_fp16_dtype_0 = const()[name = tensor("cast_2_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_119_to_fp16 = cast(dtype = cast_2_to_fp16_dtype_0, x = var_119)[name = tensor("cast_13")]; tensor var_125_cast_fp16 = expand_dims(axes = var_125_axes_0, x = var_119_to_fp16)[name = tensor("op_125_cast_fp16")]; tensor input_3_cast_fp16 = mul(x = tensor_2_cast_fp16, y = var_125_cast_fp16)[name = tensor("input_3_cast_fp16")]; tensor input0_5_pad_0 = const()[name = tensor("input0_5_pad_0"), val = tensor([0, 0, 0, 0, 2, 1, 2, 1])]; tensor input0_5_mode_0 = const()[name = tensor("input0_5_mode_0"), val = tensor("constant")]; tensor const_9_to_fp16 = const()[name = tensor("const_9_to_fp16"), val = tensor(0x0p+0)]; tensor input0_5_cast_fp16 = pad(constant_val = const_9_to_fp16, mode = input0_5_mode_0, pad = input0_5_pad_0, x = input_3_cast_fp16)[name = tensor("input0_5_cast_fp16")]; tensor tensor_4_pad_type_0 = const()[name = tensor("tensor_4_pad_type_0"), val = tensor("valid")]; tensor tensor_4_strides_0 = const()[name = tensor("tensor_4_strides_0"), val = tensor([2, 2])]; tensor tensor_4_pad_0 = const()[name = tensor("tensor_4_pad_0"), val = tensor([0, 0, 0, 0])]; 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(2432))), 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(3008)))]; 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 = input0_5_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_138_promoted_to_fp16 = const()[name = tensor("op_138_promoted_to_fp16"), val = tensor(0x1p+1)]; tensor value0_1_to_fp16 = cast(dtype = cast_0_to_fp16_dtype_0, x = value0_1)[name = tensor("cast_12")]; tensor var_139_cast_fp16 = add(x = value0_1_to_fp16, y = var_138_promoted_to_fp16)[name = tensor("op_139_cast_fp16")]; tensor var_140_promoted_to_fp16 = const()[name = tensor("op_140_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_141_cast_fp16 = add(x = var_139_cast_fp16, y = var_140_promoted_to_fp16)[name = tensor("op_141_cast_fp16")]; tensor var_142_promoted_to_fp16 = const()[name = tensor("op_142_promoted_to_fp16"), val = tensor(0x1.8p+1)]; tensor var_143_cast_fp16 = sub(x = var_141_cast_fp16, y = var_142_promoted_to_fp16)[name = tensor("op_143_cast_fp16")]; tensor var_58_promoted_to_fp16 = const()[name = tensor("op_58_promoted_to_fp16"), val = tensor(0x1p+1)]; tensor floor_div_0_cast_fp16 = floor_div(x = var_143_cast_fp16, y = var_58_promoted_to_fp16)[name = tensor("floor_div_0_cast_fp16")]; tensor var_145_promoted_to_fp16 = const()[name = tensor("op_145_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor current_lengths0_1_cast_fp16 = add(x = floor_div_0_cast_fp16, y = var_145_promoted_to_fp16)[name = tensor("current_lengths0_1_cast_fp16")]; tensor cast_3_dtype_0 = const()[name = tensor("cast_3_dtype_0"), val = tensor("int32")]; tensor expand_dims_1 = const()[name = tensor("expand_dims_1"), val = tensor([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36]])]; tensor var_154_axes_0 = const()[name = tensor("op_154_axes_0"), val = tensor([1])]; tensor current_lengths0_1_cast_fp16_to_int32 = cast(dtype = cast_3_dtype_0, x = current_lengths0_1_cast_fp16)[name = tensor("cast_11")]; tensor var_154 = expand_dims(axes = var_154_axes_0, x = current_lengths0_1_cast_fp16_to_int32)[name = tensor("op_154")]; tensor time_mask0_1 = less(x = expand_dims_1, y = var_154)[name = tensor("time_mask0_1")]; tensor var_156_axes_0 = const()[name = tensor("op_156_axes_0"), val = tensor([-1])]; tensor var_156 = expand_dims(axes = var_156_axes_0, x = time_mask0_1)[name = tensor("op_156")]; tensor var_158_reps_0 = const()[name = tensor("op_158_reps_0"), val = tensor([1, 1, 65])]; tensor var_158 = tile(reps = var_158_reps_0, x = var_156)[name = tensor("op_158")]; tensor var_164_axes_0 = const()[name = tensor("op_164_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_158_to_fp16 = cast(dtype = cast_4_to_fp16_dtype_0, x = var_158)[name = tensor("cast_10")]; tensor var_164_cast_fp16 = expand_dims(axes = var_164_axes_0, x = var_158_to_fp16)[name = tensor("op_164_cast_fp16")]; tensor expanded_mask0_1_reps_0 = const()[name = tensor("expanded_mask0_1_reps_0"), val = tensor([1, 256, 1, 1])]; tensor expanded_mask0_1_cast_fp16 = tile(reps = expanded_mask0_1_reps_0, x = var_164_cast_fp16)[name = tensor("expanded_mask0_1_cast_fp16")]; tensor input0_7_cast_fp16 = mul(x = tensor_4_cast_fp16, y = expanded_mask0_1_cast_fp16)[name = tensor("input0_7_cast_fp16")]; tensor var_168_cast_fp16 = relu(x = input0_7_cast_fp16)[name = tensor("op_168_cast_fp16")]; tensor input1_6_cast_fp16 = mul(x = var_168_cast_fp16, y = expanded_mask0_1_cast_fp16)[name = tensor("input1_6_cast_fp16")]; tensor input0_9_pad_0 = const()[name = tensor("input0_9_pad_0"), val = tensor([0, 0, 0, 0, 2, 1, 2, 1])]; tensor input0_9_mode_0 = const()[name = tensor("input0_9_mode_0"), val = tensor("constant")]; tensor const_23_to_fp16 = const()[name = tensor("const_23_to_fp16"), val = tensor(0x0p+0)]; tensor input0_9_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input0_9_mode_0, pad = input0_9_pad_0, x = input1_6_cast_fp16)[name = tensor("input0_9_cast_fp16")]; tensor tensor_6_pad_type_0 = const()[name = tensor("tensor_6_pad_type_0"), val = tensor("valid")]; 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_pad_0 = const()[name = tensor("tensor_6_pad_0"), val = tensor([0, 0, 0, 0])]; 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(3584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5952))), 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(6528)))]; 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 = input0_9_cast_fp16)[name = tensor("tensor_6_cast_fp16")]; tensor var_186_promoted_to_fp16 = const()[name = tensor("op_186_promoted_to_fp16"), val = tensor(0x1p+1)]; tensor var_187_cast_fp16 = add(x = current_lengths0_1_cast_fp16, y = var_186_promoted_to_fp16)[name = tensor("op_187_cast_fp16")]; tensor var_188_promoted_to_fp16 = const()[name = tensor("op_188_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_189_cast_fp16 = add(x = var_187_cast_fp16, y = var_188_promoted_to_fp16)[name = tensor("op_189_cast_fp16")]; tensor var_190_promoted_to_fp16 = const()[name = tensor("op_190_promoted_to_fp16"), val = tensor(0x1.8p+1)]; tensor var_191_cast_fp16 = sub(x = var_189_cast_fp16, y = var_190_promoted_to_fp16)[name = tensor("op_191_cast_fp16")]; tensor var_58_promoted_1_to_fp16 = const()[name = tensor("op_58_promoted_1_to_fp16"), val = tensor(0x1p+1)]; tensor floor_div_1_cast_fp16 = floor_div(x = var_191_cast_fp16, y = var_58_promoted_1_to_fp16)[name = tensor("floor_div_1_cast_fp16")]; tensor var_193_promoted_to_fp16 = const()[name = tensor("op_193_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor current_lengths1_1_cast_fp16 = add(x = floor_div_1_cast_fp16, y = var_193_promoted_to_fp16)[name = tensor("current_lengths1_1_cast_fp16")]; tensor cast_5_dtype_0 = const()[name = tensor("cast_5_dtype_0"), val = tensor("int32")]; tensor expand_dims_2 = const()[name = tensor("expand_dims_2"), val = tensor([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18]])]; tensor var_202_axes_0 = const()[name = tensor("op_202_axes_0"), val = tensor([1])]; tensor current_lengths1_1_cast_fp16_to_int32 = cast(dtype = cast_5_dtype_0, x = current_lengths1_1_cast_fp16)[name = tensor("cast_9")]; tensor var_202 = expand_dims(axes = var_202_axes_0, x = current_lengths1_1_cast_fp16_to_int32)[name = tensor("op_202")]; tensor time_mask1_1 = less(x = expand_dims_2, y = var_202)[name = tensor("time_mask1_1")]; tensor var_204_axes_0 = const()[name = tensor("op_204_axes_0"), val = tensor([-1])]; tensor var_204 = expand_dims(axes = var_204_axes_0, x = time_mask1_1)[name = tensor("op_204")]; tensor var_206_reps_0 = const()[name = tensor("op_206_reps_0"), val = tensor([1, 1, 33])]; tensor var_206 = tile(reps = var_206_reps_0, x = var_204)[name = tensor("op_206")]; tensor var_212_axes_0 = const()[name = tensor("op_212_axes_0"), val = tensor([1])]; tensor cast_6_to_fp16_dtype_0 = const()[name = tensor("cast_6_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_206_to_fp16 = cast(dtype = cast_6_to_fp16_dtype_0, x = var_206)[name = tensor("cast_8")]; tensor var_212_cast_fp16 = expand_dims(axes = var_212_axes_0, x = var_206_to_fp16)[name = tensor("op_212_cast_fp16")]; tensor expanded_mask2_1_reps_0 = const()[name = tensor("expanded_mask2_1_reps_0"), val = tensor([1, 256, 1, 1])]; tensor expanded_mask2_1_cast_fp16 = tile(reps = expanded_mask2_1_reps_0, x = var_212_cast_fp16)[name = tensor("expanded_mask2_1_cast_fp16")]; tensor input2_6_cast_fp16 = mul(x = tensor_6_cast_fp16, y = expanded_mask2_1_cast_fp16)[name = tensor("input2_6_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(7104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72704))), 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(73280)))]; 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_6_cast_fp16)[name = tensor("tensor_8_cast_fp16")]; tensor input3_2_cast_fp16 = mul(x = tensor_8_cast_fp16, y = expanded_mask2_1_cast_fp16)[name = tensor("input3_2_cast_fp16")]; tensor var_231_cast_fp16 = relu(x = input3_2_cast_fp16)[name = tensor("op_231_cast_fp16")]; tensor input4_2_cast_fp16 = mul(x = var_231_cast_fp16, y = expanded_mask2_1_cast_fp16)[name = tensor("input4_2_cast_fp16")]; tensor input0_11_pad_0 = const()[name = tensor("input0_11_pad_0"), val = tensor([0, 0, 0, 0, 2, 1, 2, 1])]; tensor input0_11_mode_0 = const()[name = tensor("input0_11_mode_0"), val = tensor("constant")]; tensor const_41_to_fp16 = const()[name = tensor("const_41_to_fp16"), val = tensor(0x0p+0)]; tensor input0_11_cast_fp16 = pad(constant_val = const_41_to_fp16, mode = input0_11_mode_0, pad = input0_11_pad_0, x = input4_2_cast_fp16)[name = tensor("input0_11_cast_fp16")]; tensor tensor_10_pad_type_0 = const()[name = tensor("tensor_10_pad_type_0"), val = tensor("valid")]; 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_pad_0 = const()[name = tensor("tensor_10_pad_0"), val = tensor([0, 0, 0, 0])]; 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(73856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76224))), 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(76800)))]; 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 = input0_11_cast_fp16)[name = tensor("tensor_10_cast_fp16")]; tensor var_249_promoted_to_fp16 = const()[name = tensor("op_249_promoted_to_fp16"), val = tensor(0x1p+1)]; tensor var_250_cast_fp16 = add(x = current_lengths1_1_cast_fp16, y = var_249_promoted_to_fp16)[name = tensor("op_250_cast_fp16")]; tensor var_251_promoted_to_fp16 = const()[name = tensor("op_251_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor var_252_cast_fp16 = add(x = var_250_cast_fp16, y = var_251_promoted_to_fp16)[name = tensor("op_252_cast_fp16")]; tensor var_253_promoted_to_fp16 = const()[name = tensor("op_253_promoted_to_fp16"), val = tensor(0x1.8p+1)]; tensor var_254_cast_fp16 = sub(x = var_252_cast_fp16, y = var_253_promoted_to_fp16)[name = tensor("op_254_cast_fp16")]; tensor var_58_promoted_2_to_fp16 = const()[name = tensor("op_58_promoted_2_to_fp16"), val = tensor(0x1p+1)]; tensor floor_div_2_cast_fp16 = floor_div(x = var_254_cast_fp16, y = var_58_promoted_2_to_fp16)[name = tensor("floor_div_2_cast_fp16")]; tensor var_256_promoted_to_fp16 = const()[name = tensor("op_256_promoted_to_fp16"), val = tensor(0x1p+0)]; tensor current_lengths2_1_cast_fp16 = add(x = floor_div_2_cast_fp16, y = var_256_promoted_to_fp16)[name = tensor("current_lengths2_1_cast_fp16")]; tensor cast_7_dtype_0 = const()[name = tensor("cast_7_dtype_0"), val = tensor("int32")]; tensor expand_dims_3 = const()[name = tensor("expand_dims_3"), val = tensor([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]])]; tensor var_265_axes_0 = const()[name = tensor("op_265_axes_0"), val = tensor([1])]; tensor current_lengths2_1_cast_fp16_to_int32 = cast(dtype = cast_7_dtype_0, x = current_lengths2_1_cast_fp16)[name = tensor("cast_7")]; tensor var_265 = expand_dims(axes = var_265_axes_0, x = current_lengths2_1_cast_fp16_to_int32)[name = tensor("op_265")]; tensor time_mask2_1 = less(x = expand_dims_3, y = var_265)[name = tensor("time_mask2_1")]; tensor var_267_axes_0 = const()[name = tensor("op_267_axes_0"), val = tensor([-1])]; tensor var_267 = expand_dims(axes = var_267_axes_0, x = time_mask2_1)[name = tensor("op_267")]; tensor var_269_reps_0 = const()[name = tensor("op_269_reps_0"), val = tensor([1, 1, 17])]; tensor var_269 = tile(reps = var_269_reps_0, x = var_267)[name = tensor("op_269")]; tensor var_275_axes_0 = const()[name = tensor("op_275_axes_0"), val = tensor([1])]; tensor cast_8_to_fp16_dtype_0 = const()[name = tensor("cast_8_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_269_to_fp16 = cast(dtype = cast_8_to_fp16_dtype_0, x = var_269)[name = tensor("cast_6")]; tensor var_275_cast_fp16 = expand_dims(axes = var_275_axes_0, x = var_269_to_fp16)[name = tensor("op_275_cast_fp16")]; tensor expanded_mask5_1_reps_0 = const()[name = tensor("expanded_mask5_1_reps_0"), val = tensor([1, 256, 1, 1])]; tensor expanded_mask5_1_cast_fp16 = tile(reps = expanded_mask5_1_reps_0, x = var_275_cast_fp16)[name = tensor("expanded_mask5_1_cast_fp16")]; tensor input5_2_cast_fp16 = mul(x = tensor_10_cast_fp16, y = expanded_mask5_1_cast_fp16)[name = tensor("input5_2_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(77376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(142976))), 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(143552)))]; 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_2_cast_fp16)[name = tensor("tensor_1_cast_fp16")]; tensor input6_2_cast_fp16 = mul(x = tensor_1_cast_fp16, y = expanded_mask5_1_cast_fp16)[name = tensor("input6_2_cast_fp16")]; tensor var_294_cast_fp16 = relu(x = input6_2_cast_fp16)[name = tensor("op_294_cast_fp16")]; tensor x0_2_cast_fp16 = mul(x = var_294_cast_fp16, y = expanded_mask5_1_cast_fp16)[name = tensor("x0_2_cast_fp16")]; tensor var_309_perm_0 = const()[name = tensor("op_309_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_310 = const()[name = tensor("op_310"), val = tensor([1, 10, -1])]; tensor var_309_cast_fp16 = transpose(perm = var_309_perm_0, x = x0_2_cast_fp16)[name = tensor("transpose_256")]; tensor input_5_cast_fp16 = reshape(shape = var_310, x = var_309_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(144128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2372416))), name = tensor("encoder_pre_encode_out_weight_to_fp16_palettized"), shape = tensor([512, 4352])]; 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(2372992)))]; 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 var_320_begin_0 = const()[name = tensor("op_320_begin_0"), val = tensor([0, 2, 0])]; tensor var_320_end_0 = const()[name = tensor("op_320_end_0"), val = tensor([1, 10, 512])]; tensor var_320_end_mask_0 = const()[name = tensor("op_320_end_mask_0"), val = tensor([true, true, true])]; tensor var_320_cast_fp16 = slice_by_index(begin = var_320_begin_0, end = var_320_end_0, end_mask = var_320_end_mask_0, x = linear_0_cast_fp16)[name = tensor("op_320_cast_fp16")]; tensor var_322 = const()[name = tensor("op_322"), val = tensor(2)]; tensor var_323 = sub(x = current_lengths2_1_cast_fp16_to_int32, y = var_322)[name = tensor("op_323")]; tensor var_323_promoted_to_fp16_dtype_0 = const()[name = tensor("op_323_promoted_to_fp16_dtype_0"), val = tensor("fp16")]; tensor var_52_promoted_to_fp16 = const()[name = tensor("op_52_promoted_to_fp16"), val = tensor(0x0p+0)]; tensor const_61_to_fp16 = const()[name = tensor("const_61_to_fp16"), val = tensor(inf)]; tensor var_323_to_fp16 = cast(dtype = var_323_promoted_to_fp16_dtype_0, x = var_323)[name = tensor("cast_5")]; tensor clip_0_cast_fp16 = clip(alpha = var_52_promoted_to_fp16, beta = const_61_to_fp16, x = var_323_to_fp16)[name = tensor("clip_0_cast_fp16")]; tensor cache_keep_size_1 = const()[name = tensor("cache_keep_size_1"), val = tensor([4])]; tensor var_339_promoted_to_fp16 = const()[name = tensor("op_339_promoted_to_fp16"), val = tensor(0x1.18p+6)]; tensor padding_length_1_cast_fp16 = add(x = clip_0_cast_fp16, y = var_339_promoted_to_fp16)[name = tensor("padding_length_1_cast_fp16")]; tensor const_63 = const()[name = tensor("const_63"), val = tensor(-1)]; tensor var_341 = mul(x = cache_last_channel_len, y = const_63)[name = tensor("op_341")]; tensor var_342 = const()[name = tensor("op_342"), val = tensor(70)]; tensor offset_1 = add(x = var_341, y = var_342)[name = tensor("offset_1")]; tensor var_382_axes_0 = const()[name = tensor("op_382_axes_0"), val = tensor([-1])]; tensor var_382_cast_fp16 = expand_dims(axes = var_382_axes_0, x = padding_length_1_cast_fp16)[name = tensor("op_382_cast_fp16")]; tensor var_381_promoted_to_fp16 = const()[name = tensor("op_381_promoted_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2374080)))]; tensor pad_mask_1_cast_fp16 = less(x = var_381_promoted_to_fp16, y = var_382_cast_fp16)[name = tensor("pad_mask_1_cast_fp16")]; tensor expand_dims_5 = const()[name = tensor("expand_dims_5"), val = tensor([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77]])]; tensor var_388_axes_0 = const()[name = tensor("op_388_axes_0"), val = tensor([-1])]; tensor var_388 = expand_dims(axes = var_388_axes_0, x = offset_1)[name = tensor("op_388")]; tensor pad_mask_off_1 = greater_equal(x = expand_dims_5, y = var_388)[name = tensor("pad_mask_off_1")]; tensor pad_mask0_1 = logical_and(x = pad_mask_off_1, y = pad_mask_1_cast_fp16)[name = tensor("pad_mask0_1")]; tensor var_391_axes_0 = const()[name = tensor("op_391_axes_0"), val = tensor([1])]; tensor var_391 = expand_dims(axes = var_391_axes_0, x = pad_mask0_1)[name = tensor("op_391")]; tensor var_392 = const()[name = tensor("op_392"), val = tensor([1, 78, 1])]; tensor pad_mask_for_att_mask_1 = tile(reps = var_392, x = var_391)[name = tensor("pad_mask_for_att_mask_1")]; tensor var_394_perm_0 = const()[name = tensor("op_394_perm_0"), val = tensor([0, 2, 1])]; tensor var_394 = transpose(perm = var_394_perm_0, x = pad_mask_for_att_mask_1)[name = tensor("transpose_255")]; tensor pad_mask_for_att_mask0_1 = logical_and(x = pad_mask_for_att_mask_1, y = var_394)[name = tensor("pad_mask_for_att_mask0_1")]; tensor const_71 = const()[name = tensor("const_71"), val = tensor([[[true, true, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, false, 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true, true, true, true, true, true, true, true], [false, false, false, false, false, false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true]]])]; tensor att_mask3_1 = logical_and(x = pad_mask_for_att_mask0_1, y = const_71)[name = tensor("att_mask3_1")]; tensor att_mask4_1 = logical_not(x = att_mask3_1)[name = tensor("att_mask4_1")]; tensor pad_mask1_1 = logical_not(x = pad_mask0_1)[name = tensor("pad_mask1_1")]; tensor pad_mask2_1_begin_0 = const()[name = tensor("pad_mask2_1_begin_0"), val = tensor([0, 70])]; tensor pad_mask2_1_end_0 = const()[name = tensor("pad_mask2_1_end_0"), val = tensor([1, 78])]; tensor pad_mask2_1_end_mask_0 = const()[name = tensor("pad_mask2_1_end_mask_0"), val = tensor([true, true])]; tensor pad_mask2_1 = slice_by_index(begin = pad_mask2_1_begin_0, end = pad_mask2_1_end_0, end_mask = pad_mask2_1_end_mask_0, x = pad_mask1_1)[name = tensor("pad_mask2_1")]; tensor mask_2_begin_0 = const()[name = tensor("mask_2_begin_0"), val = tensor([0, 70, 0])]; tensor mask_2_end_0 = const()[name = tensor("mask_2_end_0"), val = tensor([1, 78, 78])]; tensor mask_2_end_mask_0 = const()[name = tensor("mask_2_end_mask_0"), val = tensor([true, true, true])]; tensor mask_2 = slice_by_index(begin = mask_2_begin_0, end = mask_2_end_0, end_mask = mask_2_end_mask_0, x = att_mask4_1)[name = tensor("mask_2")]; tensor cache_1_begin_0 = const()[name = tensor("cache_1_begin_0"), val = tensor([0, 0, 0, 0])]; tensor cache_1_end_0 = const()[name = tensor("cache_1_end_0"), val = tensor([1, 1, 70, 512])]; tensor cache_1_end_mask_0 = const()[name = tensor("cache_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache_1_squeeze_mask_0 = const()[name = tensor("cache_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache_last_channel_to_fp16_dtype_0 = const()[name = tensor("cache_last_channel_to_fp16_dtype_0"), val = tensor("fp16")]; tensor cache_last_channel_to_fp16 = cast(dtype = cache_last_channel_to_fp16_dtype_0, x = cache_last_channel)[name = tensor("cast_4")]; tensor cache_1_cast_fp16 = slice_by_index(begin = cache_1_begin_0, end = cache_1_end_0, end_mask = cache_1_end_mask_0, squeeze_mask = cache_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache_1_cast_fp16")]; tensor cache0_1_begin_0 = const()[name = tensor("cache0_1_begin_0"), val = tensor([0, 0, 0, 0])]; tensor cache0_1_end_0 = const()[name = tensor("cache0_1_end_0"), val = tensor([1, 1, 512, 8])]; tensor cache0_1_end_mask_0 = const()[name = tensor("cache0_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache0_1_squeeze_mask_0 = const()[name = tensor("cache0_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache_last_time_to_fp16_dtype_0 = const()[name = tensor("cache_last_time_to_fp16_dtype_0"), val = tensor("fp16")]; tensor cache_last_time_to_fp16 = cast(dtype = cache_last_time_to_fp16_dtype_0, x = cache_last_time)[name = tensor("cast_3")]; tensor cache0_1_cast_fp16 = slice_by_index(begin = cache0_1_begin_0, end = cache0_1_end_0, end_mask = cache0_1_end_mask_0, squeeze_mask = cache0_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache0_1_cast_fp16")]; 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(2374336)))]; 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(2375424)))]; tensor var_25_to_fp16 = const()[name = tensor("op_25_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_25_to_fp16, gamma = encoder_layers_0_norm_feed_forward1_weight_to_fp16, x = var_320_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(2376512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3425152))), name = tensor("encoder_layers_0_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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(3425728)))]; 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_426_cast_fp16 = silu(x = linear_1_cast_fp16)[name = tensor("op_426_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(3429888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4478528))), name = tensor("encoder_layers_0_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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(4479104)))]; 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_426_cast_fp16)[name = tensor("linear_2_cast_fp16")]; tensor var_431_to_fp16 = const()[name = tensor("op_431_to_fp16"), val = tensor(0x1p-1)]; tensor var_432_cast_fp16 = mul(x = linear_2_cast_fp16, y = var_431_to_fp16)[name = tensor("op_432_cast_fp16")]; tensor input_13_cast_fp16 = add(x = var_320_cast_fp16, y = var_432_cast_fp16)[name = tensor("input_13_cast_fp16")]; tensor key_2_axes_0 = const()[name = tensor("key_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(4480192)))]; 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(4481280)))]; tensor key_2_cast_fp16 = layer_norm(axes = key_2_axes_0, beta = encoder_layers_0_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_0_norm_self_att_weight_to_fp16, x = input_13_cast_fp16)[name = tensor("key_2_cast_fp16")]; tensor input_15_interleave_0 = const()[name = tensor("input_15_interleave_0"), val = tensor(false)]; tensor input_15_cast_fp16 = concat(axis = var_55, interleave = input_15_interleave_0, values = (cache_1_cast_fp16, key_2_cast_fp16))[name = tensor("input_15_cast_fp16")]; tensor var_454_begin_0 = const()[name = tensor("op_454_begin_0"), val = tensor([0, 4, 0])]; tensor var_454_end_0 = const()[name = tensor("op_454_end_0"), val = tensor([1, 70, 512])]; tensor var_454_end_mask_0 = const()[name = tensor("op_454_end_mask_0"), val = tensor([true, true, true])]; tensor var_454_cast_fp16 = slice_by_index(begin = var_454_begin_0, end = var_454_end_0, end_mask = var_454_end_mask_0, x = cache_1_cast_fp16)[name = tensor("op_454_cast_fp16")]; tensor var_457_begin_0 = const()[name = tensor("op_457_begin_0"), val = tensor([0, 0, 0])]; tensor var_457_end_0 = const()[name = tensor("op_457_end_0"), val = tensor([1, 4, 512])]; tensor var_457_end_mask_0 = const()[name = tensor("op_457_end_mask_0"), val = tensor([true, false, true])]; tensor var_457_cast_fp16 = slice_by_index(begin = var_457_begin_0, end = var_457_end_0, end_mask = var_457_end_mask_0, x = key_2_cast_fp16)[name = tensor("op_457_cast_fp16")]; tensor var_460_interleave_0 = const()[name = tensor("op_460_interleave_0"), val = tensor(false)]; tensor var_460_cast_fp16 = concat(axis = var_55, interleave = var_460_interleave_0, values = (var_454_cast_fp16, var_457_cast_fp16))[name = tensor("op_460_cast_fp16")]; 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(4482368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(4744576))), name = tensor("encoder_layers_0_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_2_cast_fp16)[name = tensor("linear_3_cast_fp16")]; tensor var_464 = const()[name = tensor("op_464"), val = tensor([1, -1, 8, 64])]; tensor q_2_cast_fp16 = reshape(shape = var_464, 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(4745152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5007360))), name = tensor("encoder_layers_0_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_15_cast_fp16)[name = tensor("linear_4_cast_fp16")]; tensor var_468 = const()[name = tensor("op_468"), val = tensor([1, -1, 8, 64])]; tensor k_2_cast_fp16 = reshape(shape = var_468, 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(5007936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5270144))), name = tensor("encoder_layers_0_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_15_cast_fp16)[name = tensor("linear_5_cast_fp16")]; tensor var_472 = const()[name = tensor("op_472"), val = tensor([1, -1, 8, 64])]; tensor v_2_cast_fp16 = reshape(shape = var_472, x = linear_5_cast_fp16)[name = tensor("v_2_cast_fp16")]; tensor value_4_perm_0 = const()[name = tensor("value_4_perm_0"), val = tensor([0, 2, -3, -1])]; 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(5270720)))]; tensor var_484_cast_fp16 = add(x = q_2_cast_fp16, y = encoder_layers_0_self_attn_pos_bias_u_to_fp16)[name = tensor("op_484_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(5271808)))]; tensor var_486_cast_fp16 = add(x = q_2_cast_fp16, y = encoder_layers_0_self_attn_pos_bias_v_to_fp16)[name = tensor("op_486_cast_fp16")]; tensor q_with_bias_v_2_perm_0 = const()[name = tensor("q_with_bias_v_2_perm_0"), val = tensor([0, 2, -3, -1])]; 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 op_488_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5272896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5352320))), name = tensor("op_488_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_2_cast_fp16 = transpose(perm = q_with_bias_v_2_perm_0, x = var_486_cast_fp16)[name = tensor("transpose_254")]; tensor x_11_cast_fp16 = matmul(transpose_x = x_11_transpose_x_0, transpose_y = x_11_transpose_y_0, x = q_with_bias_v_2_cast_fp16, y = op_488_to_fp16_palettized)[name = tensor("x_11_cast_fp16")]; 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_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(0x0p+0)]; tensor x0_4_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = x0_4_mode_0, pad = x0_4_pad_0, x = x_11_cast_fp16)[name = tensor("x0_4_cast_fp16")]; tensor var_496 = const()[name = tensor("op_496"), val = tensor([1, 8, -1, 8])]; tensor x1_2_cast_fp16 = reshape(shape = var_496, x = x0_4_cast_fp16)[name = tensor("x1_2_cast_fp16")]; tensor var_500_begin_0 = const()[name = tensor("op_500_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_500_end_0 = const()[name = tensor("op_500_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_500_end_mask_0 = const()[name = tensor("op_500_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_500_cast_fp16 = slice_by_index(begin = var_500_begin_0, end = var_500_end_0, end_mask = var_500_end_mask_0, x = x1_2_cast_fp16)[name = tensor("op_500_cast_fp16")]; tensor var_501 = const()[name = tensor("op_501"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_2_cast_fp16 = reshape(shape = var_501, x = var_500_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_68_perm_0 = const()[name = tensor("transpose_68_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_69_perm_0 = const()[name = tensor("transpose_69_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_69 = transpose(perm = transpose_69_perm_0, x = k_2_cast_fp16)[name = tensor("transpose_252")]; tensor transpose_68 = transpose(perm = transpose_68_perm_0, x = var_484_cast_fp16)[name = tensor("transpose_253")]; 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_68, y = transpose_69)[name = tensor("matrix_ac_2_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_2_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_2_end_0, end_mask = matrix_bd0_2_end_mask_0, x = matrix_bd_2_cast_fp16)[name = tensor("matrix_bd0_2_cast_fp16")]; tensor var_510_cast_fp16 = add(x = matrix_ac_2_cast_fp16, y = matrix_bd0_2_cast_fp16)[name = tensor("op_510_cast_fp16")]; tensor _inversed_scores_2_y_0_to_fp16 = const()[name = tensor("_inversed_scores_2_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_2_cast_fp16 = mul(x = var_510_cast_fp16, y = _inversed_scores_2_y_0_to_fp16)[name = tensor("_inversed_scores_2_cast_fp16")]; 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_27_to_fp16 = const()[name = tensor("op_27_to_fp16"), val = tensor(-0x1.388p+13)]; tensor scores0_2_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_2_cast_fp16, cond = mask0_4)[name = tensor("scores0_2_cast_fp16")]; tensor var_516_cast_fp16 = softmax(axis = var_47, x = scores0_2_cast_fp16)[name = tensor("op_516_cast_fp16")]; tensor var_26_to_fp16 = const()[name = tensor("op_26_to_fp16"), val = tensor(0x0p+0)]; tensor input0_13_cast_fp16 = select(a = var_26_to_fp16, b = var_516_cast_fp16, cond = mask0_4)[name = tensor("input0_13_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 value_4_cast_fp16 = transpose(perm = value_4_perm_0, x = v_2_cast_fp16)[name = tensor("transpose_251")]; tensor x2_2_cast_fp16 = matmul(transpose_x = x2_2_transpose_x_0, transpose_y = x2_2_transpose_y_0, x = input0_13_cast_fp16, y = value_4_cast_fp16)[name = tensor("x2_2_cast_fp16")]; tensor var_520_perm_0 = const()[name = tensor("op_520_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_521 = const()[name = tensor("op_521"), val = tensor([1, -1, 512])]; tensor var_520_cast_fp16 = transpose(perm = var_520_perm_0, x = x2_2_cast_fp16)[name = tensor("transpose_250")]; tensor input1_8_cast_fp16 = reshape(shape = var_521, x = var_520_cast_fp16)[name = tensor("input1_8_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(5352896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5615104))), name = tensor("encoder_layers_0_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_8_cast_fp16)[name = tensor("linear_7_cast_fp16")]; tensor input0_19_cast_fp16 = add(x = input_13_cast_fp16, y = linear_7_cast_fp16)[name = tensor("input0_19_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(5615680)))]; 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(5616768)))]; tensor x_15_cast_fp16 = layer_norm(axes = x_15_axes_0, beta = encoder_layers_0_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_0_norm_conv_weight_to_fp16, x = input0_19_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(5617856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6142208))), name = tensor("encoder_layers_0_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_17_cast_fp16 = transpose(perm = input_17_perm_0, x = x_15_cast_fp16)[name = tensor("transpose_249")]; 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_546_axes_0 = const()[name = tensor("op_546_axes_0"), val = tensor([1])]; tensor var_546 = expand_dims(axes = var_546_axes_0, x = pad_mask2_1)[name = tensor("op_546")]; tensor input3_4_cast_fp16 = select(a = var_26_to_fp16, b = x_17_cast_fp16, cond = var_546)[name = tensor("input3_4_cast_fp16")]; tensor new_x0_2_interleave_0 = const()[name = tensor("new_x0_2_interleave_0"), val = tensor(false)]; tensor new_x0_2_cast_fp16 = concat(axis = var_47, interleave = new_x0_2_interleave_0, values = (cache0_1_cast_fp16, input3_4_cast_fp16))[name = tensor("new_x0_2_cast_fp16")]; tensor next_cache_2_begin_0 = const()[name = tensor("next_cache_2_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_2_end_0 = const()[name = tensor("next_cache_2_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_2_end_mask_0 = const()[name = tensor("next_cache_2_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_2_cast_fp16 = slice_by_index(begin = next_cache_2_begin_0, end = next_cache_2_end_0, end_mask = next_cache_2_end_mask_0, x = new_x0_2_cast_fp16)[name = tensor("next_cache_2_cast_fp16")]; tensor var_562_begin_0 = const()[name = tensor("op_562_begin_0"), val = tensor([0, 0, 4])]; tensor var_562_end_0 = const()[name = tensor("op_562_end_0"), val = tensor([1, 512, 12])]; tensor var_562_end_mask_0 = const()[name = tensor("op_562_end_mask_0"), val = tensor([true, true, true])]; tensor var_562_cast_fp16 = slice_by_index(begin = var_562_begin_0, end = var_562_end_0, end_mask = var_562_end_mask_0, x = next_cache_2_cast_fp16)[name = tensor("op_562_cast_fp16")]; tensor x_19_pad_type_0 = const()[name = tensor("x_19_pad_type_0"), val = tensor("valid")]; tensor x_19_groups_0 = const()[name = tensor("x_19_groups_0"), val = tensor(512)]; 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 encoder_layers_0_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6142784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6147456))), name = tensor("encoder_layers_0_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; 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_depthwise_conv_weight_to_fp16_palettized, x = new_x0_2_cast_fp16)[name = tensor("x_19_cast_fp16")]; tensor input4_1_perm_0 = const()[name = tensor("input4_1_perm_0"), val = tensor([0, 2, 1])]; tensor x_21_axes_0 = const()[name = tensor("x_21_axes_0"), val = tensor([-1])]; tensor encoder_layers_0_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_0_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6148032)))]; tensor encoder_layers_0_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_0_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6149120)))]; tensor input4_1_cast_fp16 = transpose(perm = input4_1_perm_0, x = x_19_cast_fp16)[name = tensor("transpose_248")]; tensor x_21_cast_fp16 = layer_norm(axes = x_21_axes_0, beta = encoder_layers_0_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_0_conv_batch_norm_weight_to_fp16, x = input4_1_cast_fp16)[name = tensor("x_21_cast_fp16")]; tensor input5_1_perm_0 = const()[name = tensor("input5_1_perm_0"), val = tensor([0, 2, 1])]; tensor input5_1_cast_fp16 = transpose(perm = input5_1_perm_0, x = x_21_cast_fp16)[name = tensor("transpose_247")]; tensor var_577_cast_fp16 = silu(x = input5_1_cast_fp16)[name = tensor("op_577_cast_fp16")]; tensor x_23_pad_type_0 = const()[name = tensor("x_23_pad_type_0"), val = tensor("valid")]; tensor x_23_strides_0 = const()[name = tensor("x_23_strides_0"), val = tensor([1])]; tensor x_23_pad_0 = const()[name = tensor("x_23_pad_0"), val = tensor([0, 0])]; tensor x_23_dilations_0 = const()[name = tensor("x_23_dilations_0"), val = tensor([1])]; tensor x_23_groups_0 = const()[name = tensor("x_23_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(6150208))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6412416))), name = tensor("encoder_layers_0_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_23_cast_fp16 = conv(dilations = x_23_dilations_0, groups = x_23_groups_0, pad = x_23_pad_0, pad_type = x_23_pad_type_0, strides = x_23_strides_0, weight = encoder_layers_0_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_577_cast_fp16)[name = tensor("x_23_cast_fp16")]; tensor input6_1_perm_0 = const()[name = tensor("input6_1_perm_0"), val = tensor([0, 2, 1])]; tensor input6_1_cast_fp16 = transpose(perm = input6_1_perm_0, x = x_23_cast_fp16)[name = tensor("transpose_246")]; tensor input1_10_cast_fp16 = add(x = input0_19_cast_fp16, y = input6_1_cast_fp16)[name = tensor("input1_10_cast_fp16")]; tensor input0_17_axes_0 = const()[name = tensor("input0_17_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(6412992)))]; 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(6414080)))]; tensor input0_17_cast_fp16 = layer_norm(axes = input0_17_axes_0, beta = encoder_layers_0_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_0_norm_feed_forward2_weight_to_fp16, x = input1_10_cast_fp16)[name = tensor("input0_17_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(6415168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7463808))), name = tensor("encoder_layers_0_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_17_cast_fp16)[name = tensor("linear_8_cast_fp16")]; tensor var_598_cast_fp16 = silu(x = linear_8_cast_fp16)[name = tensor("op_598_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(7464384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(8513024))), name = tensor("encoder_layers_0_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_598_cast_fp16)[name = tensor("linear_9_cast_fp16")]; tensor var_603_to_fp16 = const()[name = tensor("op_603_to_fp16"), val = tensor(0x1p-1)]; tensor var_604_cast_fp16 = mul(x = linear_9_cast_fp16, y = var_603_to_fp16)[name = tensor("op_604_cast_fp16")]; tensor input2_4_cast_fp16 = add(x = input1_10_cast_fp16, y = var_604_cast_fp16)[name = tensor("input2_4_cast_fp16")]; tensor input0_21_axes_0 = const()[name = tensor("input0_21_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(8513600)))]; 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(8514688)))]; tensor input0_21_cast_fp16 = layer_norm(axes = input0_21_axes_0, beta = encoder_layers_0_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_0_norm_out_weight_to_fp16, x = input2_4_cast_fp16)[name = tensor("input0_21_cast_fp16")]; tensor cache1_1_begin_0 = const()[name = tensor("cache1_1_begin_0"), val = tensor([1, 0, 0, 0])]; tensor cache1_1_end_0 = const()[name = tensor("cache1_1_end_0"), val = tensor([2, 1, 70, 512])]; tensor cache1_1_end_mask_0 = const()[name = tensor("cache1_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache1_1_squeeze_mask_0 = const()[name = tensor("cache1_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache1_1_cast_fp16 = slice_by_index(begin = cache1_1_begin_0, end = cache1_1_end_0, end_mask = cache1_1_end_mask_0, squeeze_mask = cache1_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache1_1_cast_fp16")]; tensor cache2_1_begin_0 = const()[name = tensor("cache2_1_begin_0"), val = tensor([1, 0, 0, 0])]; tensor cache2_1_end_0 = const()[name = tensor("cache2_1_end_0"), val = tensor([2, 1, 512, 8])]; tensor cache2_1_end_mask_0 = const()[name = tensor("cache2_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache2_1_squeeze_mask_0 = const()[name = tensor("cache2_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache2_1_cast_fp16 = slice_by_index(begin = cache2_1_begin_0, end = cache2_1_end_0, end_mask = cache2_1_end_mask_0, squeeze_mask = cache2_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache2_1_cast_fp16")]; tensor input_21_axes_0 = const()[name = tensor("input_21_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(8515776)))]; 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(8516864)))]; tensor input_21_cast_fp16 = layer_norm(axes = input_21_axes_0, beta = encoder_layers_1_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_1_norm_feed_forward1_weight_to_fp16, x = input0_21_cast_fp16)[name = tensor("input_21_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(8517952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9566592))), name = tensor("encoder_layers_1_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_21_cast_fp16)[name = tensor("linear_10_cast_fp16")]; tensor var_633_cast_fp16 = silu(x = linear_10_cast_fp16)[name = tensor("op_633_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(9567168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10615808))), name = tensor("encoder_layers_1_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_633_cast_fp16)[name = tensor("linear_11_cast_fp16")]; tensor var_638_to_fp16 = const()[name = tensor("op_638_to_fp16"), val = tensor(0x1p-1)]; tensor var_639_cast_fp16 = mul(x = linear_11_cast_fp16, y = var_638_to_fp16)[name = tensor("op_639_cast_fp16")]; tensor input_25_cast_fp16 = add(x = input0_21_cast_fp16, y = var_639_cast_fp16)[name = tensor("input_25_cast_fp16")]; tensor key_4_axes_0 = const()[name = tensor("key_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(10616384)))]; 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(10617472)))]; tensor key_4_cast_fp16 = layer_norm(axes = key_4_axes_0, beta = encoder_layers_1_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_1_norm_self_att_weight_to_fp16, x = input_25_cast_fp16)[name = tensor("key_4_cast_fp16")]; tensor input_27_interleave_0 = const()[name = tensor("input_27_interleave_0"), val = tensor(false)]; tensor input_27_cast_fp16 = concat(axis = var_55, interleave = input_27_interleave_0, values = (cache1_1_cast_fp16, key_4_cast_fp16))[name = tensor("input_27_cast_fp16")]; tensor var_661_begin_0 = const()[name = tensor("op_661_begin_0"), val = tensor([0, 4, 0])]; tensor var_661_end_0 = const()[name = tensor("op_661_end_0"), val = tensor([1, 70, 512])]; tensor var_661_end_mask_0 = const()[name = tensor("op_661_end_mask_0"), val = tensor([true, true, true])]; tensor var_661_cast_fp16 = slice_by_index(begin = var_661_begin_0, end = var_661_end_0, end_mask = var_661_end_mask_0, x = cache1_1_cast_fp16)[name = tensor("op_661_cast_fp16")]; tensor var_664_begin_0 = const()[name = tensor("op_664_begin_0"), val = tensor([0, 0, 0])]; tensor var_664_end_0 = const()[name = tensor("op_664_end_0"), val = tensor([1, 4, 512])]; tensor var_664_end_mask_0 = const()[name = tensor("op_664_end_mask_0"), val = tensor([true, false, true])]; tensor var_664_cast_fp16 = slice_by_index(begin = var_664_begin_0, end = var_664_end_0, end_mask = var_664_end_mask_0, x = key_4_cast_fp16)[name = tensor("op_664_cast_fp16")]; tensor var_667_interleave_0 = const()[name = tensor("op_667_interleave_0"), val = tensor(false)]; tensor var_667_cast_fp16 = concat(axis = var_55, interleave = var_667_interleave_0, values = (var_661_cast_fp16, var_664_cast_fp16))[name = tensor("op_667_cast_fp16")]; 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(10618560))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(10880768))), name = tensor("encoder_layers_1_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_4_cast_fp16)[name = tensor("linear_12_cast_fp16")]; tensor var_671 = const()[name = tensor("op_671"), val = tensor([1, -1, 8, 64])]; tensor q_4_cast_fp16 = reshape(shape = var_671, 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(10881344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11143552))), name = tensor("encoder_layers_1_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_27_cast_fp16)[name = tensor("linear_13_cast_fp16")]; tensor var_675 = const()[name = tensor("op_675"), val = tensor([1, -1, 8, 64])]; tensor k_4_cast_fp16 = reshape(shape = var_675, 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(11144128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11406336))), name = tensor("encoder_layers_1_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_27_cast_fp16)[name = tensor("linear_14_cast_fp16")]; tensor var_679 = const()[name = tensor("op_679"), val = tensor([1, -1, 8, 64])]; tensor v_4_cast_fp16 = reshape(shape = var_679, x = linear_14_cast_fp16)[name = tensor("v_4_cast_fp16")]; tensor value_6_perm_0 = const()[name = tensor("value_6_perm_0"), val = tensor([0, 2, -3, -1])]; 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(11406912)))]; tensor var_691_cast_fp16 = add(x = q_4_cast_fp16, y = encoder_layers_1_self_attn_pos_bias_u_to_fp16)[name = tensor("op_691_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(11408000)))]; tensor var_693_cast_fp16 = add(x = q_4_cast_fp16, y = encoder_layers_1_self_attn_pos_bias_v_to_fp16)[name = tensor("op_693_cast_fp16")]; tensor q_with_bias_v_4_perm_0 = const()[name = tensor("q_with_bias_v_4_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_31_transpose_x_0 = const()[name = tensor("x_31_transpose_x_0"), val = tensor(false)]; tensor x_31_transpose_y_0 = const()[name = tensor("x_31_transpose_y_0"), val = tensor(false)]; tensor op_695_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11409088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11488512))), name = tensor("op_695_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_4_cast_fp16 = transpose(perm = q_with_bias_v_4_perm_0, x = var_693_cast_fp16)[name = tensor("transpose_245")]; tensor x_31_cast_fp16 = matmul(transpose_x = x_31_transpose_x_0, transpose_y = x_31_transpose_y_0, x = q_with_bias_v_4_cast_fp16, y = op_695_to_fp16_palettized)[name = tensor("x_31_cast_fp16")]; 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_92_to_fp16 = const()[name = tensor("const_92_to_fp16"), val = tensor(0x0p+0)]; tensor x0_6_cast_fp16 = pad(constant_val = const_92_to_fp16, mode = x0_6_mode_0, pad = x0_6_pad_0, x = x_31_cast_fp16)[name = tensor("x0_6_cast_fp16")]; tensor var_703 = const()[name = tensor("op_703"), val = tensor([1, 8, -1, 8])]; tensor x1_4_cast_fp16 = reshape(shape = var_703, x = x0_6_cast_fp16)[name = tensor("x1_4_cast_fp16")]; tensor var_707_begin_0 = const()[name = tensor("op_707_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_707_end_0 = const()[name = tensor("op_707_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_707_end_mask_0 = const()[name = tensor("op_707_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_707_cast_fp16 = slice_by_index(begin = var_707_begin_0, end = var_707_end_0, end_mask = var_707_end_mask_0, x = x1_4_cast_fp16)[name = tensor("op_707_cast_fp16")]; tensor var_708 = const()[name = tensor("op_708"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_4_cast_fp16 = reshape(shape = var_708, x = var_707_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_70_perm_0 = const()[name = tensor("transpose_70_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_71_perm_0 = const()[name = tensor("transpose_71_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_71 = transpose(perm = transpose_71_perm_0, x = k_4_cast_fp16)[name = tensor("transpose_243")]; tensor transpose_70 = transpose(perm = transpose_70_perm_0, x = var_691_cast_fp16)[name = tensor("transpose_244")]; 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_70, y = transpose_71)[name = tensor("matrix_ac_4_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_4_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_4_end_0, end_mask = matrix_bd0_4_end_mask_0, x = matrix_bd_4_cast_fp16)[name = tensor("matrix_bd0_4_cast_fp16")]; tensor var_717_cast_fp16 = add(x = matrix_ac_4_cast_fp16, y = matrix_bd0_4_cast_fp16)[name = tensor("op_717_cast_fp16")]; tensor _inversed_scores_4_y_0_to_fp16 = const()[name = tensor("_inversed_scores_4_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_4_cast_fp16 = mul(x = var_717_cast_fp16, y = _inversed_scores_4_y_0_to_fp16)[name = tensor("_inversed_scores_4_cast_fp16")]; tensor scores0_4_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_4_cast_fp16, cond = mask0_4)[name = tensor("scores0_4_cast_fp16")]; tensor var_723_cast_fp16 = softmax(axis = var_47, x = scores0_4_cast_fp16)[name = tensor("op_723_cast_fp16")]; tensor input0_23_cast_fp16 = select(a = var_26_to_fp16, b = var_723_cast_fp16, cond = mask0_4)[name = tensor("input0_23_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 value_6_cast_fp16 = transpose(perm = value_6_perm_0, x = v_4_cast_fp16)[name = tensor("transpose_242")]; tensor x2_4_cast_fp16 = matmul(transpose_x = x2_4_transpose_x_0, transpose_y = x2_4_transpose_y_0, x = input0_23_cast_fp16, y = value_6_cast_fp16)[name = tensor("x2_4_cast_fp16")]; tensor var_727_perm_0 = const()[name = tensor("op_727_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_728 = const()[name = tensor("op_728"), val = tensor([1, -1, 512])]; tensor var_727_cast_fp16 = transpose(perm = var_727_perm_0, x = x2_4_cast_fp16)[name = tensor("transpose_241")]; tensor input1_12_cast_fp16 = reshape(shape = var_728, x = var_727_cast_fp16)[name = tensor("input1_12_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(11489088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11751296))), name = tensor("encoder_layers_1_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_12_cast_fp16)[name = tensor("linear_16_cast_fp16")]; tensor input0_25_cast_fp16 = add(x = input_25_cast_fp16, y = linear_16_cast_fp16)[name = tensor("input0_25_cast_fp16")]; tensor x_35_axes_0 = const()[name = tensor("x_35_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(11751872)))]; 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(11752960)))]; tensor x_35_cast_fp16 = layer_norm(axes = x_35_axes_0, beta = encoder_layers_1_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_1_norm_conv_weight_to_fp16, x = input0_25_cast_fp16)[name = tensor("x_35_cast_fp16")]; tensor input_29_perm_0 = const()[name = tensor("input_29_perm_0"), val = tensor([0, 2, 1])]; tensor input0_27_pad_type_0 = const()[name = tensor("input0_27_pad_type_0"), val = tensor("valid")]; tensor input0_27_strides_0 = const()[name = tensor("input0_27_strides_0"), val = tensor([1])]; tensor input0_27_pad_0 = const()[name = tensor("input0_27_pad_0"), val = tensor([0, 0])]; tensor input0_27_dilations_0 = const()[name = tensor("input0_27_dilations_0"), val = tensor([1])]; tensor input0_27_groups_0 = const()[name = tensor("input0_27_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(11754048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12278400))), name = tensor("encoder_layers_1_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_29_cast_fp16 = transpose(perm = input_29_perm_0, x = x_35_cast_fp16)[name = tensor("transpose_240")]; tensor input0_27_cast_fp16 = conv(dilations = input0_27_dilations_0, groups = input0_27_groups_0, pad = input0_27_pad_0, pad_type = input0_27_pad_type_0, strides = input0_27_strides_0, weight = encoder_layers_1_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_29_cast_fp16)[name = tensor("input0_27_cast_fp16")]; tensor x_37_split_num_splits_0 = const()[name = tensor("x_37_split_num_splits_0"), val = tensor(2)]; tensor x_37_split_axis_0 = const()[name = tensor("x_37_split_axis_0"), val = tensor(1)]; tensor x_37_split_cast_fp16_0, tensor x_37_split_cast_fp16_1 = split(axis = x_37_split_axis_0, num_splits = x_37_split_num_splits_0, x = input0_27_cast_fp16)[name = tensor("x_37_split_cast_fp16")]; tensor x_37_split_1_sigmoid_cast_fp16 = sigmoid(x = x_37_split_cast_fp16_1)[name = tensor("x_37_split_1_sigmoid_cast_fp16")]; tensor x_37_cast_fp16 = mul(x = x_37_split_cast_fp16_0, y = x_37_split_1_sigmoid_cast_fp16)[name = tensor("x_37_cast_fp16")]; tensor input0_29_cast_fp16 = select(a = var_26_to_fp16, b = x_37_cast_fp16, cond = var_546)[name = tensor("input0_29_cast_fp16")]; tensor new_x0_4_interleave_0 = const()[name = tensor("new_x0_4_interleave_0"), val = tensor(false)]; tensor new_x0_4_cast_fp16 = concat(axis = var_47, interleave = new_x0_4_interleave_0, values = (cache2_1_cast_fp16, input0_29_cast_fp16))[name = tensor("new_x0_4_cast_fp16")]; tensor next_cache_4_begin_0 = const()[name = tensor("next_cache_4_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_4_end_0 = const()[name = tensor("next_cache_4_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_4_end_mask_0 = const()[name = tensor("next_cache_4_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_4_cast_fp16 = slice_by_index(begin = next_cache_4_begin_0, end = next_cache_4_end_0, end_mask = next_cache_4_end_mask_0, x = new_x0_4_cast_fp16)[name = tensor("next_cache_4_cast_fp16")]; tensor var_769_begin_0 = const()[name = tensor("op_769_begin_0"), val = tensor([0, 0, 4])]; tensor var_769_end_0 = const()[name = tensor("op_769_end_0"), val = tensor([1, 512, 12])]; tensor var_769_end_mask_0 = const()[name = tensor("op_769_end_mask_0"), val = tensor([true, true, true])]; tensor var_769_cast_fp16 = slice_by_index(begin = var_769_begin_0, end = var_769_end_0, end_mask = var_769_end_mask_0, x = next_cache_4_cast_fp16)[name = tensor("op_769_cast_fp16")]; tensor x_39_pad_type_0 = const()[name = tensor("x_39_pad_type_0"), val = tensor("valid")]; tensor x_39_groups_0 = const()[name = tensor("x_39_groups_0"), val = tensor(512)]; tensor x_39_strides_0 = const()[name = tensor("x_39_strides_0"), val = tensor([1])]; tensor x_39_pad_0 = const()[name = tensor("x_39_pad_0"), val = tensor([0, 0])]; tensor x_39_dilations_0 = const()[name = tensor("x_39_dilations_0"), val = tensor([1])]; tensor encoder_layers_1_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12278976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12283648))), name = tensor("encoder_layers_1_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_39_cast_fp16 = conv(dilations = x_39_dilations_0, groups = x_39_groups_0, pad = x_39_pad_0, pad_type = x_39_pad_type_0, strides = x_39_strides_0, weight = encoder_layers_1_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_4_cast_fp16)[name = tensor("x_39_cast_fp16")]; tensor input1_14_perm_0 = const()[name = tensor("input1_14_perm_0"), val = tensor([0, 2, 1])]; tensor x_41_axes_0 = const()[name = tensor("x_41_axes_0"), val = tensor([-1])]; tensor encoder_layers_1_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_1_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12284224)))]; tensor encoder_layers_1_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_1_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12285312)))]; tensor input1_14_cast_fp16 = transpose(perm = input1_14_perm_0, x = x_39_cast_fp16)[name = tensor("transpose_239")]; tensor x_41_cast_fp16 = layer_norm(axes = x_41_axes_0, beta = encoder_layers_1_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_1_conv_batch_norm_weight_to_fp16, x = input1_14_cast_fp16)[name = tensor("x_41_cast_fp16")]; tensor input2_8_perm_0 = const()[name = tensor("input2_8_perm_0"), val = tensor([0, 2, 1])]; tensor input2_8_cast_fp16 = transpose(perm = input2_8_perm_0, x = x_41_cast_fp16)[name = tensor("transpose_238")]; tensor var_784_cast_fp16 = silu(x = input2_8_cast_fp16)[name = tensor("op_784_cast_fp16")]; tensor x_43_pad_type_0 = const()[name = tensor("x_43_pad_type_0"), val = tensor("valid")]; tensor x_43_strides_0 = const()[name = tensor("x_43_strides_0"), val = tensor([1])]; tensor x_43_pad_0 = const()[name = tensor("x_43_pad_0"), val = tensor([0, 0])]; tensor x_43_dilations_0 = const()[name = tensor("x_43_dilations_0"), val = tensor([1])]; tensor x_43_groups_0 = const()[name = tensor("x_43_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(12286400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12548608))), name = tensor("encoder_layers_1_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_43_cast_fp16 = conv(dilations = x_43_dilations_0, groups = x_43_groups_0, pad = x_43_pad_0, pad_type = x_43_pad_type_0, strides = x_43_strides_0, weight = encoder_layers_1_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_784_cast_fp16)[name = tensor("x_43_cast_fp16")]; tensor input3_6_perm_0 = const()[name = tensor("input3_6_perm_0"), val = tensor([0, 2, 1])]; tensor input3_6_cast_fp16 = transpose(perm = input3_6_perm_0, x = x_43_cast_fp16)[name = tensor("transpose_237")]; tensor input1_16_cast_fp16 = add(x = input0_25_cast_fp16, y = input3_6_cast_fp16)[name = tensor("input1_16_cast_fp16")]; tensor input0_31_axes_0 = const()[name = tensor("input0_31_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(12549184)))]; 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(12550272)))]; tensor input0_31_cast_fp16 = layer_norm(axes = input0_31_axes_0, beta = encoder_layers_1_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_1_norm_feed_forward2_weight_to_fp16, x = input1_16_cast_fp16)[name = tensor("input0_31_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(12551360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(13600000))), name = tensor("encoder_layers_1_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_31_cast_fp16)[name = tensor("linear_17_cast_fp16")]; tensor var_805_cast_fp16 = silu(x = linear_17_cast_fp16)[name = tensor("op_805_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(13600576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14649216))), name = tensor("encoder_layers_1_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_805_cast_fp16)[name = tensor("linear_18_cast_fp16")]; tensor var_810_to_fp16 = const()[name = tensor("op_810_to_fp16"), val = tensor(0x1p-1)]; tensor var_811_cast_fp16 = mul(x = linear_18_cast_fp16, y = var_810_to_fp16)[name = tensor("op_811_cast_fp16")]; tensor input2_10_cast_fp16 = add(x = input1_16_cast_fp16, y = var_811_cast_fp16)[name = tensor("input2_10_cast_fp16")]; tensor input0_33_axes_0 = const()[name = tensor("input0_33_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(14649792)))]; 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(14650880)))]; tensor input0_33_cast_fp16 = layer_norm(axes = input0_33_axes_0, beta = encoder_layers_1_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_1_norm_out_weight_to_fp16, x = input2_10_cast_fp16)[name = tensor("input0_33_cast_fp16")]; tensor cache3_1_begin_0 = const()[name = tensor("cache3_1_begin_0"), val = tensor([2, 0, 0, 0])]; tensor cache3_1_end_0 = const()[name = tensor("cache3_1_end_0"), val = tensor([3, 1, 70, 512])]; tensor cache3_1_end_mask_0 = const()[name = tensor("cache3_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache3_1_squeeze_mask_0 = const()[name = tensor("cache3_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache3_1_cast_fp16 = slice_by_index(begin = cache3_1_begin_0, end = cache3_1_end_0, end_mask = cache3_1_end_mask_0, squeeze_mask = cache3_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache3_1_cast_fp16")]; tensor cache4_1_begin_0 = const()[name = tensor("cache4_1_begin_0"), val = tensor([2, 0, 0, 0])]; tensor cache4_1_end_0 = const()[name = tensor("cache4_1_end_0"), val = tensor([3, 1, 512, 8])]; tensor cache4_1_end_mask_0 = const()[name = tensor("cache4_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache4_1_squeeze_mask_0 = const()[name = tensor("cache4_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache4_1_cast_fp16 = slice_by_index(begin = cache4_1_begin_0, end = cache4_1_end_0, end_mask = cache4_1_end_mask_0, squeeze_mask = cache4_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache4_1_cast_fp16")]; tensor input_33_axes_0 = const()[name = tensor("input_33_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(14651968)))]; 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(14653056)))]; tensor input_33_cast_fp16 = layer_norm(axes = input_33_axes_0, beta = encoder_layers_2_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_2_norm_feed_forward1_weight_to_fp16, x = input0_33_cast_fp16)[name = tensor("input_33_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(14654144))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15702784))), name = tensor("encoder_layers_2_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_33_cast_fp16)[name = tensor("linear_19_cast_fp16")]; tensor var_840_cast_fp16 = silu(x = linear_19_cast_fp16)[name = tensor("op_840_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(15703360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16752000))), name = tensor("encoder_layers_2_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_840_cast_fp16)[name = tensor("linear_20_cast_fp16")]; tensor var_845_to_fp16 = const()[name = tensor("op_845_to_fp16"), val = tensor(0x1p-1)]; tensor var_846_cast_fp16 = mul(x = linear_20_cast_fp16, y = var_845_to_fp16)[name = tensor("op_846_cast_fp16")]; tensor input_37_cast_fp16 = add(x = input0_33_cast_fp16, y = var_846_cast_fp16)[name = tensor("input_37_cast_fp16")]; tensor key_6_axes_0 = const()[name = tensor("key_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(16752576)))]; 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(16753664)))]; tensor key_6_cast_fp16 = layer_norm(axes = key_6_axes_0, beta = encoder_layers_2_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_2_norm_self_att_weight_to_fp16, x = input_37_cast_fp16)[name = tensor("key_6_cast_fp16")]; tensor input_39_interleave_0 = const()[name = tensor("input_39_interleave_0"), val = tensor(false)]; tensor input_39_cast_fp16 = concat(axis = var_55, interleave = input_39_interleave_0, values = (cache3_1_cast_fp16, key_6_cast_fp16))[name = tensor("input_39_cast_fp16")]; tensor var_868_begin_0 = const()[name = tensor("op_868_begin_0"), val = tensor([0, 4, 0])]; tensor var_868_end_0 = const()[name = tensor("op_868_end_0"), val = tensor([1, 70, 512])]; tensor var_868_end_mask_0 = const()[name = tensor("op_868_end_mask_0"), val = tensor([true, true, true])]; tensor var_868_cast_fp16 = slice_by_index(begin = var_868_begin_0, end = var_868_end_0, end_mask = var_868_end_mask_0, x = cache3_1_cast_fp16)[name = tensor("op_868_cast_fp16")]; tensor var_871_begin_0 = const()[name = tensor("op_871_begin_0"), val = tensor([0, 0, 0])]; tensor var_871_end_0 = const()[name = tensor("op_871_end_0"), val = tensor([1, 4, 512])]; tensor var_871_end_mask_0 = const()[name = tensor("op_871_end_mask_0"), val = tensor([true, false, true])]; tensor var_871_cast_fp16 = slice_by_index(begin = var_871_begin_0, end = var_871_end_0, end_mask = var_871_end_mask_0, x = key_6_cast_fp16)[name = tensor("op_871_cast_fp16")]; tensor var_874_interleave_0 = const()[name = tensor("op_874_interleave_0"), val = tensor(false)]; tensor var_874_cast_fp16 = concat(axis = var_55, interleave = var_874_interleave_0, values = (var_868_cast_fp16, var_871_cast_fp16))[name = tensor("op_874_cast_fp16")]; 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(16754752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17016960))), name = tensor("encoder_layers_2_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_6_cast_fp16)[name = tensor("linear_21_cast_fp16")]; tensor var_878 = const()[name = tensor("op_878"), val = tensor([1, -1, 8, 64])]; tensor q_6_cast_fp16 = reshape(shape = var_878, 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(17017536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17279744))), name = tensor("encoder_layers_2_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_39_cast_fp16)[name = tensor("linear_22_cast_fp16")]; tensor var_882 = const()[name = tensor("op_882"), val = tensor([1, -1, 8, 64])]; tensor k_6_cast_fp16 = reshape(shape = var_882, 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(17280320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17542528))), name = tensor("encoder_layers_2_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_39_cast_fp16)[name = tensor("linear_23_cast_fp16")]; tensor var_886 = const()[name = tensor("op_886"), val = tensor([1, -1, 8, 64])]; tensor v_6_cast_fp16 = reshape(shape = var_886, x = linear_23_cast_fp16)[name = tensor("v_6_cast_fp16")]; tensor value_8_perm_0 = const()[name = tensor("value_8_perm_0"), val = tensor([0, 2, -3, -1])]; 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(17543104)))]; tensor var_898_cast_fp16 = add(x = q_6_cast_fp16, y = encoder_layers_2_self_attn_pos_bias_u_to_fp16)[name = tensor("op_898_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(17544192)))]; tensor var_900_cast_fp16 = add(x = q_6_cast_fp16, y = encoder_layers_2_self_attn_pos_bias_v_to_fp16)[name = tensor("op_900_cast_fp16")]; tensor q_with_bias_v_6_perm_0 = const()[name = tensor("q_with_bias_v_6_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_51_transpose_x_0 = const()[name = tensor("x_51_transpose_x_0"), val = tensor(false)]; tensor x_51_transpose_y_0 = const()[name = tensor("x_51_transpose_y_0"), val = tensor(false)]; tensor op_902_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17545280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17624704))), name = tensor("op_902_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_6_cast_fp16 = transpose(perm = q_with_bias_v_6_perm_0, x = var_900_cast_fp16)[name = tensor("transpose_236")]; tensor x_51_cast_fp16 = matmul(transpose_x = x_51_transpose_x_0, transpose_y = x_51_transpose_y_0, x = q_with_bias_v_6_cast_fp16, y = op_902_to_fp16_palettized)[name = tensor("x_51_cast_fp16")]; 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_105_to_fp16 = const()[name = tensor("const_105_to_fp16"), val = tensor(0x0p+0)]; tensor x0_8_cast_fp16 = pad(constant_val = const_105_to_fp16, mode = x0_8_mode_0, pad = x0_8_pad_0, x = x_51_cast_fp16)[name = tensor("x0_8_cast_fp16")]; tensor var_910 = const()[name = tensor("op_910"), val = tensor([1, 8, -1, 8])]; tensor x1_6_cast_fp16 = reshape(shape = var_910, x = x0_8_cast_fp16)[name = tensor("x1_6_cast_fp16")]; tensor var_914_begin_0 = const()[name = tensor("op_914_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_914_end_0 = const()[name = tensor("op_914_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_914_end_mask_0 = const()[name = tensor("op_914_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_914_cast_fp16 = slice_by_index(begin = var_914_begin_0, end = var_914_end_0, end_mask = var_914_end_mask_0, x = x1_6_cast_fp16)[name = tensor("op_914_cast_fp16")]; tensor var_915 = const()[name = tensor("op_915"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_6_cast_fp16 = reshape(shape = var_915, x = var_914_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_72_perm_0 = const()[name = tensor("transpose_72_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_73_perm_0 = const()[name = tensor("transpose_73_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_73 = transpose(perm = transpose_73_perm_0, x = k_6_cast_fp16)[name = tensor("transpose_234")]; tensor transpose_72 = transpose(perm = transpose_72_perm_0, x = var_898_cast_fp16)[name = tensor("transpose_235")]; 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_72, y = transpose_73)[name = tensor("matrix_ac_6_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_6_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_6_end_0, end_mask = matrix_bd0_6_end_mask_0, x = matrix_bd_6_cast_fp16)[name = tensor("matrix_bd0_6_cast_fp16")]; tensor var_924_cast_fp16 = add(x = matrix_ac_6_cast_fp16, y = matrix_bd0_6_cast_fp16)[name = tensor("op_924_cast_fp16")]; tensor _inversed_scores_6_y_0_to_fp16 = const()[name = tensor("_inversed_scores_6_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_6_cast_fp16 = mul(x = var_924_cast_fp16, y = _inversed_scores_6_y_0_to_fp16)[name = tensor("_inversed_scores_6_cast_fp16")]; tensor scores0_6_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_6_cast_fp16, cond = mask0_4)[name = tensor("scores0_6_cast_fp16")]; tensor var_930_cast_fp16 = softmax(axis = var_47, x = scores0_6_cast_fp16)[name = tensor("op_930_cast_fp16")]; tensor input0_35_cast_fp16 = select(a = var_26_to_fp16, b = var_930_cast_fp16, cond = mask0_4)[name = tensor("input0_35_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 value_8_cast_fp16 = transpose(perm = value_8_perm_0, x = v_6_cast_fp16)[name = tensor("transpose_233")]; tensor x2_6_cast_fp16 = matmul(transpose_x = x2_6_transpose_x_0, transpose_y = x2_6_transpose_y_0, x = input0_35_cast_fp16, y = value_8_cast_fp16)[name = tensor("x2_6_cast_fp16")]; tensor var_934_perm_0 = const()[name = tensor("op_934_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_935 = const()[name = tensor("op_935"), val = tensor([1, -1, 512])]; tensor var_934_cast_fp16 = transpose(perm = var_934_perm_0, x = x2_6_cast_fp16)[name = tensor("transpose_232")]; tensor input1_18_cast_fp16 = reshape(shape = var_935, x = var_934_cast_fp16)[name = tensor("input1_18_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(17625280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17887488))), name = tensor("encoder_layers_2_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_18_cast_fp16)[name = tensor("linear_25_cast_fp16")]; tensor input0_37_cast_fp16 = add(x = input_37_cast_fp16, y = linear_25_cast_fp16)[name = tensor("input0_37_cast_fp16")]; tensor x_55_axes_0 = const()[name = tensor("x_55_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(17888064)))]; 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(17889152)))]; tensor x_55_cast_fp16 = layer_norm(axes = x_55_axes_0, beta = encoder_layers_2_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_2_norm_conv_weight_to_fp16, x = input0_37_cast_fp16)[name = tensor("x_55_cast_fp16")]; tensor input_41_perm_0 = const()[name = tensor("input_41_perm_0"), val = tensor([0, 2, 1])]; tensor input0_39_pad_type_0 = const()[name = tensor("input0_39_pad_type_0"), val = tensor("valid")]; tensor input0_39_strides_0 = const()[name = tensor("input0_39_strides_0"), val = tensor([1])]; tensor input0_39_pad_0 = const()[name = tensor("input0_39_pad_0"), val = tensor([0, 0])]; tensor input0_39_dilations_0 = const()[name = tensor("input0_39_dilations_0"), val = tensor([1])]; tensor input0_39_groups_0 = const()[name = tensor("input0_39_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(17890240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18414592))), name = tensor("encoder_layers_2_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_41_cast_fp16 = transpose(perm = input_41_perm_0, x = x_55_cast_fp16)[name = tensor("transpose_231")]; tensor input0_39_cast_fp16 = conv(dilations = input0_39_dilations_0, groups = input0_39_groups_0, pad = input0_39_pad_0, pad_type = input0_39_pad_type_0, strides = input0_39_strides_0, weight = encoder_layers_2_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_41_cast_fp16)[name = tensor("input0_39_cast_fp16")]; tensor x_57_split_num_splits_0 = const()[name = tensor("x_57_split_num_splits_0"), val = tensor(2)]; tensor x_57_split_axis_0 = const()[name = tensor("x_57_split_axis_0"), val = tensor(1)]; tensor x_57_split_cast_fp16_0, tensor x_57_split_cast_fp16_1 = split(axis = x_57_split_axis_0, num_splits = x_57_split_num_splits_0, x = input0_39_cast_fp16)[name = tensor("x_57_split_cast_fp16")]; tensor x_57_split_1_sigmoid_cast_fp16 = sigmoid(x = x_57_split_cast_fp16_1)[name = tensor("x_57_split_1_sigmoid_cast_fp16")]; tensor x_57_cast_fp16 = mul(x = x_57_split_cast_fp16_0, y = x_57_split_1_sigmoid_cast_fp16)[name = tensor("x_57_cast_fp16")]; tensor input0_41_cast_fp16 = select(a = var_26_to_fp16, b = x_57_cast_fp16, cond = var_546)[name = tensor("input0_41_cast_fp16")]; tensor new_x0_6_interleave_0 = const()[name = tensor("new_x0_6_interleave_0"), val = tensor(false)]; tensor new_x0_6_cast_fp16 = concat(axis = var_47, interleave = new_x0_6_interleave_0, values = (cache4_1_cast_fp16, input0_41_cast_fp16))[name = tensor("new_x0_6_cast_fp16")]; tensor next_cache_6_begin_0 = const()[name = tensor("next_cache_6_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_6_end_0 = const()[name = tensor("next_cache_6_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_6_end_mask_0 = const()[name = tensor("next_cache_6_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_6_cast_fp16 = slice_by_index(begin = next_cache_6_begin_0, end = next_cache_6_end_0, end_mask = next_cache_6_end_mask_0, x = new_x0_6_cast_fp16)[name = tensor("next_cache_6_cast_fp16")]; tensor var_976_begin_0 = const()[name = tensor("op_976_begin_0"), val = tensor([0, 0, 4])]; tensor var_976_end_0 = const()[name = tensor("op_976_end_0"), val = tensor([1, 512, 12])]; tensor var_976_end_mask_0 = const()[name = tensor("op_976_end_mask_0"), val = tensor([true, true, true])]; tensor var_976_cast_fp16 = slice_by_index(begin = var_976_begin_0, end = var_976_end_0, end_mask = var_976_end_mask_0, x = next_cache_6_cast_fp16)[name = tensor("op_976_cast_fp16")]; tensor x_59_pad_type_0 = const()[name = tensor("x_59_pad_type_0"), val = tensor("valid")]; tensor x_59_groups_0 = const()[name = tensor("x_59_groups_0"), val = tensor(512)]; tensor x_59_strides_0 = const()[name = tensor("x_59_strides_0"), val = tensor([1])]; tensor x_59_pad_0 = const()[name = tensor("x_59_pad_0"), val = tensor([0, 0])]; tensor x_59_dilations_0 = const()[name = tensor("x_59_dilations_0"), val = tensor([1])]; tensor encoder_layers_2_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18415168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18419840))), name = tensor("encoder_layers_2_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_59_cast_fp16 = conv(dilations = x_59_dilations_0, groups = x_59_groups_0, pad = x_59_pad_0, pad_type = x_59_pad_type_0, strides = x_59_strides_0, weight = encoder_layers_2_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_6_cast_fp16)[name = tensor("x_59_cast_fp16")]; tensor input1_20_perm_0 = const()[name = tensor("input1_20_perm_0"), val = tensor([0, 2, 1])]; tensor x_61_axes_0 = const()[name = tensor("x_61_axes_0"), val = tensor([-1])]; tensor encoder_layers_2_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_2_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18420416)))]; tensor encoder_layers_2_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_2_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18421504)))]; tensor input1_20_cast_fp16 = transpose(perm = input1_20_perm_0, x = x_59_cast_fp16)[name = tensor("transpose_230")]; tensor x_61_cast_fp16 = layer_norm(axes = x_61_axes_0, beta = encoder_layers_2_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_2_conv_batch_norm_weight_to_fp16, x = input1_20_cast_fp16)[name = tensor("x_61_cast_fp16")]; tensor input2_12_perm_0 = const()[name = tensor("input2_12_perm_0"), val = tensor([0, 2, 1])]; tensor input2_12_cast_fp16 = transpose(perm = input2_12_perm_0, x = x_61_cast_fp16)[name = tensor("transpose_229")]; tensor var_991_cast_fp16 = silu(x = input2_12_cast_fp16)[name = tensor("op_991_cast_fp16")]; tensor x_63_pad_type_0 = const()[name = tensor("x_63_pad_type_0"), val = tensor("valid")]; tensor x_63_strides_0 = const()[name = tensor("x_63_strides_0"), val = tensor([1])]; tensor x_63_pad_0 = const()[name = tensor("x_63_pad_0"), val = tensor([0, 0])]; tensor x_63_dilations_0 = const()[name = tensor("x_63_dilations_0"), val = tensor([1])]; tensor x_63_groups_0 = const()[name = tensor("x_63_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(18422592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(18684800))), name = tensor("encoder_layers_2_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_63_cast_fp16 = conv(dilations = x_63_dilations_0, groups = x_63_groups_0, pad = x_63_pad_0, pad_type = x_63_pad_type_0, strides = x_63_strides_0, weight = encoder_layers_2_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_991_cast_fp16)[name = tensor("x_63_cast_fp16")]; tensor input3_8_perm_0 = const()[name = tensor("input3_8_perm_0"), val = tensor([0, 2, 1])]; tensor input3_8_cast_fp16 = transpose(perm = input3_8_perm_0, x = x_63_cast_fp16)[name = tensor("transpose_228")]; tensor input1_22_cast_fp16 = add(x = input0_37_cast_fp16, y = input3_8_cast_fp16)[name = tensor("input1_22_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(18685376)))]; 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(18686464)))]; tensor input0_43_cast_fp16 = layer_norm(axes = input0_43_axes_0, beta = encoder_layers_2_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_2_norm_feed_forward2_weight_to_fp16, x = input1_22_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(18687552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19736192))), name = tensor("encoder_layers_2_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_1012_cast_fp16 = silu(x = linear_26_cast_fp16)[name = tensor("op_1012_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(19736768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20785408))), name = tensor("encoder_layers_2_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1012_cast_fp16)[name = tensor("linear_27_cast_fp16")]; tensor var_1017_to_fp16 = const()[name = tensor("op_1017_to_fp16"), val = tensor(0x1p-1)]; tensor var_1018_cast_fp16 = mul(x = linear_27_cast_fp16, y = var_1017_to_fp16)[name = tensor("op_1018_cast_fp16")]; tensor input2_14_cast_fp16 = add(x = input1_22_cast_fp16, y = var_1018_cast_fp16)[name = tensor("input2_14_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(20785984)))]; 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(20787072)))]; tensor input0_45_cast_fp16 = layer_norm(axes = input0_45_axes_0, beta = encoder_layers_2_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_2_norm_out_weight_to_fp16, x = input2_14_cast_fp16)[name = tensor("input0_45_cast_fp16")]; tensor cache5_1_begin_0 = const()[name = tensor("cache5_1_begin_0"), val = tensor([3, 0, 0, 0])]; tensor cache5_1_end_0 = const()[name = tensor("cache5_1_end_0"), val = tensor([4, 1, 70, 512])]; tensor cache5_1_end_mask_0 = const()[name = tensor("cache5_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache5_1_squeeze_mask_0 = const()[name = tensor("cache5_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache5_1_cast_fp16 = slice_by_index(begin = cache5_1_begin_0, end = cache5_1_end_0, end_mask = cache5_1_end_mask_0, squeeze_mask = cache5_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache5_1_cast_fp16")]; tensor cache6_1_begin_0 = const()[name = tensor("cache6_1_begin_0"), val = tensor([3, 0, 0, 0])]; tensor cache6_1_end_0 = const()[name = tensor("cache6_1_end_0"), val = tensor([4, 1, 512, 8])]; tensor cache6_1_end_mask_0 = const()[name = tensor("cache6_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache6_1_squeeze_mask_0 = const()[name = tensor("cache6_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache6_1_cast_fp16 = slice_by_index(begin = cache6_1_begin_0, end = cache6_1_end_0, end_mask = cache6_1_end_mask_0, squeeze_mask = cache6_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache6_1_cast_fp16")]; tensor input_45_axes_0 = const()[name = tensor("input_45_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(20788160)))]; 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(20789248)))]; tensor input_45_cast_fp16 = layer_norm(axes = input_45_axes_0, beta = encoder_layers_3_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_3_norm_feed_forward1_weight_to_fp16, x = input0_45_cast_fp16)[name = tensor("input_45_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(20790336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21838976))), name = tensor("encoder_layers_3_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_45_cast_fp16)[name = tensor("linear_28_cast_fp16")]; tensor var_1047_cast_fp16 = silu(x = linear_28_cast_fp16)[name = tensor("op_1047_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(21839552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22888192))), name = tensor("encoder_layers_3_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1047_cast_fp16)[name = tensor("linear_29_cast_fp16")]; tensor var_1052_to_fp16 = const()[name = tensor("op_1052_to_fp16"), val = tensor(0x1p-1)]; tensor var_1053_cast_fp16 = mul(x = linear_29_cast_fp16, y = var_1052_to_fp16)[name = tensor("op_1053_cast_fp16")]; tensor input_49_cast_fp16 = add(x = input0_45_cast_fp16, y = var_1053_cast_fp16)[name = tensor("input_49_cast_fp16")]; tensor key_8_axes_0 = const()[name = tensor("key_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(22888768)))]; 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(22889856)))]; tensor key_8_cast_fp16 = layer_norm(axes = key_8_axes_0, beta = encoder_layers_3_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_3_norm_self_att_weight_to_fp16, x = input_49_cast_fp16)[name = tensor("key_8_cast_fp16")]; tensor input_51_interleave_0 = const()[name = tensor("input_51_interleave_0"), val = tensor(false)]; tensor input_51_cast_fp16 = concat(axis = var_55, interleave = input_51_interleave_0, values = (cache5_1_cast_fp16, key_8_cast_fp16))[name = tensor("input_51_cast_fp16")]; tensor var_1075_begin_0 = const()[name = tensor("op_1075_begin_0"), val = tensor([0, 4, 0])]; tensor var_1075_end_0 = const()[name = tensor("op_1075_end_0"), val = tensor([1, 70, 512])]; tensor var_1075_end_mask_0 = const()[name = tensor("op_1075_end_mask_0"), val = tensor([true, true, true])]; tensor var_1075_cast_fp16 = slice_by_index(begin = var_1075_begin_0, end = var_1075_end_0, end_mask = var_1075_end_mask_0, x = cache5_1_cast_fp16)[name = tensor("op_1075_cast_fp16")]; tensor var_1078_begin_0 = const()[name = tensor("op_1078_begin_0"), val = tensor([0, 0, 0])]; tensor var_1078_end_0 = const()[name = tensor("op_1078_end_0"), val = tensor([1, 4, 512])]; tensor var_1078_end_mask_0 = const()[name = tensor("op_1078_end_mask_0"), val = tensor([true, false, true])]; tensor var_1078_cast_fp16 = slice_by_index(begin = var_1078_begin_0, end = var_1078_end_0, end_mask = var_1078_end_mask_0, x = key_8_cast_fp16)[name = tensor("op_1078_cast_fp16")]; tensor var_1081_interleave_0 = const()[name = tensor("op_1081_interleave_0"), val = tensor(false)]; tensor var_1081_cast_fp16 = concat(axis = var_55, interleave = var_1081_interleave_0, values = (var_1075_cast_fp16, var_1078_cast_fp16))[name = tensor("op_1081_cast_fp16")]; 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(22890944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23153152))), name = tensor("encoder_layers_3_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_8_cast_fp16)[name = tensor("linear_30_cast_fp16")]; tensor var_1085 = const()[name = tensor("op_1085"), val = tensor([1, -1, 8, 64])]; tensor q_8_cast_fp16 = reshape(shape = var_1085, 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(23153728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23415936))), name = tensor("encoder_layers_3_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_51_cast_fp16)[name = tensor("linear_31_cast_fp16")]; tensor var_1089 = const()[name = tensor("op_1089"), val = tensor([1, -1, 8, 64])]; tensor k_8_cast_fp16 = reshape(shape = var_1089, 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(23416512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23678720))), name = tensor("encoder_layers_3_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_51_cast_fp16)[name = tensor("linear_32_cast_fp16")]; tensor var_1093 = const()[name = tensor("op_1093"), val = tensor([1, -1, 8, 64])]; tensor v_8_cast_fp16 = reshape(shape = var_1093, x = linear_32_cast_fp16)[name = tensor("v_8_cast_fp16")]; tensor value_10_perm_0 = const()[name = tensor("value_10_perm_0"), val = tensor([0, 2, -3, -1])]; 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(23679296)))]; tensor var_1105_cast_fp16 = add(x = q_8_cast_fp16, y = encoder_layers_3_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1105_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(23680384)))]; tensor var_1107_cast_fp16 = add(x = q_8_cast_fp16, y = encoder_layers_3_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1107_cast_fp16")]; tensor q_with_bias_v_8_perm_0 = const()[name = tensor("q_with_bias_v_8_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_71_transpose_x_0 = const()[name = tensor("x_71_transpose_x_0"), val = tensor(false)]; tensor x_71_transpose_y_0 = const()[name = tensor("x_71_transpose_y_0"), val = tensor(false)]; tensor op_1109_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23681472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23760896))), name = tensor("op_1109_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_8_cast_fp16 = transpose(perm = q_with_bias_v_8_perm_0, x = var_1107_cast_fp16)[name = tensor("transpose_227")]; tensor x_71_cast_fp16 = matmul(transpose_x = x_71_transpose_x_0, transpose_y = x_71_transpose_y_0, x = q_with_bias_v_8_cast_fp16, y = op_1109_to_fp16_palettized)[name = tensor("x_71_cast_fp16")]; 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_118_to_fp16 = const()[name = tensor("const_118_to_fp16"), val = tensor(0x0p+0)]; tensor x0_10_cast_fp16 = pad(constant_val = const_118_to_fp16, mode = x0_10_mode_0, pad = x0_10_pad_0, x = x_71_cast_fp16)[name = tensor("x0_10_cast_fp16")]; tensor var_1117 = const()[name = tensor("op_1117"), val = tensor([1, 8, -1, 8])]; tensor x1_8_cast_fp16 = reshape(shape = var_1117, x = x0_10_cast_fp16)[name = tensor("x1_8_cast_fp16")]; tensor var_1121_begin_0 = const()[name = tensor("op_1121_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1121_end_0 = const()[name = tensor("op_1121_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_1121_end_mask_0 = const()[name = tensor("op_1121_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1121_cast_fp16 = slice_by_index(begin = var_1121_begin_0, end = var_1121_end_0, end_mask = var_1121_end_mask_0, x = x1_8_cast_fp16)[name = tensor("op_1121_cast_fp16")]; tensor var_1122 = const()[name = tensor("op_1122"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_8_cast_fp16 = reshape(shape = var_1122, x = var_1121_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_74_perm_0 = const()[name = tensor("transpose_74_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_75_perm_0 = const()[name = tensor("transpose_75_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_75 = transpose(perm = transpose_75_perm_0, x = k_8_cast_fp16)[name = tensor("transpose_225")]; tensor transpose_74 = transpose(perm = transpose_74_perm_0, x = var_1105_cast_fp16)[name = tensor("transpose_226")]; 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_74, y = transpose_75)[name = tensor("matrix_ac_8_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_8_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_8_end_0, end_mask = matrix_bd0_8_end_mask_0, x = matrix_bd_8_cast_fp16)[name = tensor("matrix_bd0_8_cast_fp16")]; tensor var_1131_cast_fp16 = add(x = matrix_ac_8_cast_fp16, y = matrix_bd0_8_cast_fp16)[name = tensor("op_1131_cast_fp16")]; tensor _inversed_scores_8_y_0_to_fp16 = const()[name = tensor("_inversed_scores_8_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_8_cast_fp16 = mul(x = var_1131_cast_fp16, y = _inversed_scores_8_y_0_to_fp16)[name = tensor("_inversed_scores_8_cast_fp16")]; tensor scores0_8_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_8_cast_fp16, cond = mask0_4)[name = tensor("scores0_8_cast_fp16")]; tensor var_1137_cast_fp16 = softmax(axis = var_47, x = scores0_8_cast_fp16)[name = tensor("op_1137_cast_fp16")]; tensor input0_47_cast_fp16 = select(a = var_26_to_fp16, b = var_1137_cast_fp16, cond = mask0_4)[name = tensor("input0_47_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 value_10_cast_fp16 = transpose(perm = value_10_perm_0, x = v_8_cast_fp16)[name = tensor("transpose_224")]; tensor x2_8_cast_fp16 = matmul(transpose_x = x2_8_transpose_x_0, transpose_y = x2_8_transpose_y_0, x = input0_47_cast_fp16, y = value_10_cast_fp16)[name = tensor("x2_8_cast_fp16")]; tensor var_1141_perm_0 = const()[name = tensor("op_1141_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_1142 = const()[name = tensor("op_1142"), val = tensor([1, -1, 512])]; tensor var_1141_cast_fp16 = transpose(perm = var_1141_perm_0, x = x2_8_cast_fp16)[name = tensor("transpose_223")]; tensor input1_24_cast_fp16 = reshape(shape = var_1142, x = var_1141_cast_fp16)[name = tensor("input1_24_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(23761472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24023680))), name = tensor("encoder_layers_3_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_24_cast_fp16)[name = tensor("linear_34_cast_fp16")]; tensor input0_49_cast_fp16 = add(x = input_49_cast_fp16, y = linear_34_cast_fp16)[name = tensor("input0_49_cast_fp16")]; tensor x_75_axes_0 = const()[name = tensor("x_75_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(24024256)))]; 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(24025344)))]; tensor x_75_cast_fp16 = layer_norm(axes = x_75_axes_0, beta = encoder_layers_3_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_3_norm_conv_weight_to_fp16, x = input0_49_cast_fp16)[name = tensor("x_75_cast_fp16")]; tensor input_53_perm_0 = const()[name = tensor("input_53_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(24026432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24550784))), name = tensor("encoder_layers_3_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_53_cast_fp16 = transpose(perm = input_53_perm_0, x = x_75_cast_fp16)[name = tensor("transpose_222")]; 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_53_cast_fp16)[name = tensor("input0_51_cast_fp16")]; tensor x_77_split_num_splits_0 = const()[name = tensor("x_77_split_num_splits_0"), val = tensor(2)]; tensor x_77_split_axis_0 = const()[name = tensor("x_77_split_axis_0"), val = tensor(1)]; tensor x_77_split_cast_fp16_0, tensor x_77_split_cast_fp16_1 = split(axis = x_77_split_axis_0, num_splits = x_77_split_num_splits_0, x = input0_51_cast_fp16)[name = tensor("x_77_split_cast_fp16")]; tensor x_77_split_1_sigmoid_cast_fp16 = sigmoid(x = x_77_split_cast_fp16_1)[name = tensor("x_77_split_1_sigmoid_cast_fp16")]; tensor x_77_cast_fp16 = mul(x = x_77_split_cast_fp16_0, y = x_77_split_1_sigmoid_cast_fp16)[name = tensor("x_77_cast_fp16")]; tensor input0_53_cast_fp16 = select(a = var_26_to_fp16, b = x_77_cast_fp16, cond = var_546)[name = tensor("input0_53_cast_fp16")]; tensor new_x0_8_interleave_0 = const()[name = tensor("new_x0_8_interleave_0"), val = tensor(false)]; tensor new_x0_8_cast_fp16 = concat(axis = var_47, interleave = new_x0_8_interleave_0, values = (cache6_1_cast_fp16, input0_53_cast_fp16))[name = tensor("new_x0_8_cast_fp16")]; tensor next_cache_8_begin_0 = const()[name = tensor("next_cache_8_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_8_end_0 = const()[name = tensor("next_cache_8_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_8_end_mask_0 = const()[name = tensor("next_cache_8_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_8_cast_fp16 = slice_by_index(begin = next_cache_8_begin_0, end = next_cache_8_end_0, end_mask = next_cache_8_end_mask_0, x = new_x0_8_cast_fp16)[name = tensor("next_cache_8_cast_fp16")]; tensor var_1183_begin_0 = const()[name = tensor("op_1183_begin_0"), val = tensor([0, 0, 4])]; tensor var_1183_end_0 = const()[name = tensor("op_1183_end_0"), val = tensor([1, 512, 12])]; tensor var_1183_end_mask_0 = const()[name = tensor("op_1183_end_mask_0"), val = tensor([true, true, true])]; tensor var_1183_cast_fp16 = slice_by_index(begin = var_1183_begin_0, end = var_1183_end_0, end_mask = var_1183_end_mask_0, x = next_cache_8_cast_fp16)[name = tensor("op_1183_cast_fp16")]; tensor x_79_pad_type_0 = const()[name = tensor("x_79_pad_type_0"), val = tensor("valid")]; tensor x_79_groups_0 = const()[name = tensor("x_79_groups_0"), val = tensor(512)]; tensor x_79_strides_0 = const()[name = tensor("x_79_strides_0"), val = tensor([1])]; tensor x_79_pad_0 = const()[name = tensor("x_79_pad_0"), val = tensor([0, 0])]; tensor x_79_dilations_0 = const()[name = tensor("x_79_dilations_0"), val = tensor([1])]; tensor encoder_layers_3_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24551360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24556032))), name = tensor("encoder_layers_3_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_79_cast_fp16 = conv(dilations = x_79_dilations_0, groups = x_79_groups_0, pad = x_79_pad_0, pad_type = x_79_pad_type_0, strides = x_79_strides_0, weight = encoder_layers_3_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_8_cast_fp16)[name = tensor("x_79_cast_fp16")]; tensor input1_26_perm_0 = const()[name = tensor("input1_26_perm_0"), val = tensor([0, 2, 1])]; tensor x_81_axes_0 = const()[name = tensor("x_81_axes_0"), val = tensor([-1])]; tensor encoder_layers_3_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_3_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24556608)))]; tensor encoder_layers_3_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_3_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24557696)))]; tensor input1_26_cast_fp16 = transpose(perm = input1_26_perm_0, x = x_79_cast_fp16)[name = tensor("transpose_221")]; tensor x_81_cast_fp16 = layer_norm(axes = x_81_axes_0, beta = encoder_layers_3_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_3_conv_batch_norm_weight_to_fp16, x = input1_26_cast_fp16)[name = tensor("x_81_cast_fp16")]; tensor input2_16_perm_0 = const()[name = tensor("input2_16_perm_0"), val = tensor([0, 2, 1])]; tensor input2_16_cast_fp16 = transpose(perm = input2_16_perm_0, x = x_81_cast_fp16)[name = tensor("transpose_220")]; tensor var_1198_cast_fp16 = silu(x = input2_16_cast_fp16)[name = tensor("op_1198_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_3_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24558784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(24820992))), name = tensor("encoder_layers_3_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 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_3_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1198_cast_fp16)[name = tensor("x_83_cast_fp16")]; tensor input3_10_perm_0 = const()[name = tensor("input3_10_perm_0"), val = tensor([0, 2, 1])]; tensor input3_10_cast_fp16 = transpose(perm = input3_10_perm_0, x = x_83_cast_fp16)[name = tensor("transpose_219")]; tensor input1_28_cast_fp16 = add(x = input0_49_cast_fp16, y = input3_10_cast_fp16)[name = tensor("input1_28_cast_fp16")]; tensor input0_55_axes_0 = const()[name = tensor("input0_55_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(24821568)))]; 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(24822656)))]; tensor input0_55_cast_fp16 = layer_norm(axes = input0_55_axes_0, beta = encoder_layers_3_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_3_norm_feed_forward2_weight_to_fp16, x = input1_28_cast_fp16)[name = tensor("input0_55_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(24823744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25872384))), name = tensor("encoder_layers_3_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_55_cast_fp16)[name = tensor("linear_35_cast_fp16")]; tensor var_1219_cast_fp16 = silu(x = linear_35_cast_fp16)[name = tensor("op_1219_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(25872960))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26921600))), name = tensor("encoder_layers_3_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1219_cast_fp16)[name = tensor("linear_36_cast_fp16")]; tensor var_1224_to_fp16 = const()[name = tensor("op_1224_to_fp16"), val = tensor(0x1p-1)]; tensor var_1225_cast_fp16 = mul(x = linear_36_cast_fp16, y = var_1224_to_fp16)[name = tensor("op_1225_cast_fp16")]; tensor input2_18_cast_fp16 = add(x = input1_28_cast_fp16, y = var_1225_cast_fp16)[name = tensor("input2_18_cast_fp16")]; tensor input0_57_axes_0 = const()[name = tensor("input0_57_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(26922176)))]; 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(26923264)))]; tensor input0_57_cast_fp16 = layer_norm(axes = input0_57_axes_0, beta = encoder_layers_3_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_3_norm_out_weight_to_fp16, x = input2_18_cast_fp16)[name = tensor("input0_57_cast_fp16")]; tensor cache7_1_begin_0 = const()[name = tensor("cache7_1_begin_0"), val = tensor([4, 0, 0, 0])]; tensor cache7_1_end_0 = const()[name = tensor("cache7_1_end_0"), val = tensor([5, 1, 70, 512])]; tensor cache7_1_end_mask_0 = const()[name = tensor("cache7_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache7_1_squeeze_mask_0 = const()[name = tensor("cache7_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache7_1_cast_fp16 = slice_by_index(begin = cache7_1_begin_0, end = cache7_1_end_0, end_mask = cache7_1_end_mask_0, squeeze_mask = cache7_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache7_1_cast_fp16")]; tensor cache8_1_begin_0 = const()[name = tensor("cache8_1_begin_0"), val = tensor([4, 0, 0, 0])]; tensor cache8_1_end_0 = const()[name = tensor("cache8_1_end_0"), val = tensor([5, 1, 512, 8])]; tensor cache8_1_end_mask_0 = const()[name = tensor("cache8_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache8_1_squeeze_mask_0 = const()[name = tensor("cache8_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache8_1_cast_fp16 = slice_by_index(begin = cache8_1_begin_0, end = cache8_1_end_0, end_mask = cache8_1_end_mask_0, squeeze_mask = cache8_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache8_1_cast_fp16")]; tensor input_57_axes_0 = const()[name = tensor("input_57_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(26924352)))]; 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(26925440)))]; tensor input_57_cast_fp16 = layer_norm(axes = input_57_axes_0, beta = encoder_layers_4_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_4_norm_feed_forward1_weight_to_fp16, x = input0_57_cast_fp16)[name = tensor("input_57_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(26926528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27975168))), name = tensor("encoder_layers_4_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_57_cast_fp16)[name = tensor("linear_37_cast_fp16")]; tensor var_1254_cast_fp16 = silu(x = linear_37_cast_fp16)[name = tensor("op_1254_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(27975744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29024384))), name = tensor("encoder_layers_4_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1254_cast_fp16)[name = tensor("linear_38_cast_fp16")]; tensor var_1259_to_fp16 = const()[name = tensor("op_1259_to_fp16"), val = tensor(0x1p-1)]; tensor var_1260_cast_fp16 = mul(x = linear_38_cast_fp16, y = var_1259_to_fp16)[name = tensor("op_1260_cast_fp16")]; tensor input_61_cast_fp16 = add(x = input0_57_cast_fp16, y = var_1260_cast_fp16)[name = tensor("input_61_cast_fp16")]; tensor key_10_axes_0 = const()[name = tensor("key_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(29024960)))]; 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(29026048)))]; tensor key_10_cast_fp16 = layer_norm(axes = key_10_axes_0, beta = encoder_layers_4_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_4_norm_self_att_weight_to_fp16, x = input_61_cast_fp16)[name = tensor("key_10_cast_fp16")]; tensor input_63_interleave_0 = const()[name = tensor("input_63_interleave_0"), val = tensor(false)]; tensor input_63_cast_fp16 = concat(axis = var_55, interleave = input_63_interleave_0, values = (cache7_1_cast_fp16, key_10_cast_fp16))[name = tensor("input_63_cast_fp16")]; tensor var_1282_begin_0 = const()[name = tensor("op_1282_begin_0"), val = tensor([0, 4, 0])]; tensor var_1282_end_0 = const()[name = tensor("op_1282_end_0"), val = tensor([1, 70, 512])]; tensor var_1282_end_mask_0 = const()[name = tensor("op_1282_end_mask_0"), val = tensor([true, true, true])]; tensor var_1282_cast_fp16 = slice_by_index(begin = var_1282_begin_0, end = var_1282_end_0, end_mask = var_1282_end_mask_0, x = cache7_1_cast_fp16)[name = tensor("op_1282_cast_fp16")]; tensor var_1285_begin_0 = const()[name = tensor("op_1285_begin_0"), val = tensor([0, 0, 0])]; tensor var_1285_end_0 = const()[name = tensor("op_1285_end_0"), val = tensor([1, 4, 512])]; tensor var_1285_end_mask_0 = const()[name = tensor("op_1285_end_mask_0"), val = tensor([true, false, true])]; tensor var_1285_cast_fp16 = slice_by_index(begin = var_1285_begin_0, end = var_1285_end_0, end_mask = var_1285_end_mask_0, x = key_10_cast_fp16)[name = tensor("op_1285_cast_fp16")]; tensor var_1288_interleave_0 = const()[name = tensor("op_1288_interleave_0"), val = tensor(false)]; tensor var_1288_cast_fp16 = concat(axis = var_55, interleave = var_1288_interleave_0, values = (var_1282_cast_fp16, var_1285_cast_fp16))[name = tensor("op_1288_cast_fp16")]; 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(29027136))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29289344))), name = tensor("encoder_layers_4_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_10_cast_fp16)[name = tensor("linear_39_cast_fp16")]; tensor var_1292 = const()[name = tensor("op_1292"), val = tensor([1, -1, 8, 64])]; tensor q_10_cast_fp16 = reshape(shape = var_1292, 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(29289920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29552128))), name = tensor("encoder_layers_4_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_63_cast_fp16)[name = tensor("linear_40_cast_fp16")]; tensor var_1296 = const()[name = tensor("op_1296"), val = tensor([1, -1, 8, 64])]; tensor k_10_cast_fp16 = reshape(shape = var_1296, 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(29552704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29814912))), name = tensor("encoder_layers_4_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_63_cast_fp16)[name = tensor("linear_41_cast_fp16")]; tensor var_1300 = const()[name = tensor("op_1300"), val = tensor([1, -1, 8, 64])]; tensor v_10_cast_fp16 = reshape(shape = var_1300, x = linear_41_cast_fp16)[name = tensor("v_10_cast_fp16")]; tensor value_12_perm_0 = const()[name = tensor("value_12_perm_0"), val = tensor([0, 2, -3, -1])]; 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(29815488)))]; tensor var_1312_cast_fp16 = add(x = q_10_cast_fp16, y = encoder_layers_4_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1312_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(29816576)))]; tensor var_1314_cast_fp16 = add(x = q_10_cast_fp16, y = encoder_layers_4_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1314_cast_fp16")]; tensor q_with_bias_v_10_perm_0 = const()[name = tensor("q_with_bias_v_10_perm_0"), val = tensor([0, 2, -3, -1])]; 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 op_1316_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29817664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(29897088))), name = tensor("op_1316_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_10_cast_fp16 = transpose(perm = q_with_bias_v_10_perm_0, x = var_1314_cast_fp16)[name = tensor("transpose_218")]; tensor x_91_cast_fp16 = matmul(transpose_x = x_91_transpose_x_0, transpose_y = x_91_transpose_y_0, x = q_with_bias_v_10_cast_fp16, y = op_1316_to_fp16_palettized)[name = tensor("x_91_cast_fp16")]; 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_131_to_fp16 = const()[name = tensor("const_131_to_fp16"), val = tensor(0x0p+0)]; tensor x0_12_cast_fp16 = pad(constant_val = const_131_to_fp16, mode = x0_12_mode_0, pad = x0_12_pad_0, x = x_91_cast_fp16)[name = tensor("x0_12_cast_fp16")]; tensor var_1324 = const()[name = tensor("op_1324"), val = tensor([1, 8, -1, 8])]; tensor x1_10_cast_fp16 = reshape(shape = var_1324, x = x0_12_cast_fp16)[name = tensor("x1_10_cast_fp16")]; tensor var_1328_begin_0 = const()[name = tensor("op_1328_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1328_end_0 = const()[name = tensor("op_1328_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_1328_end_mask_0 = const()[name = tensor("op_1328_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1328_cast_fp16 = slice_by_index(begin = var_1328_begin_0, end = var_1328_end_0, end_mask = var_1328_end_mask_0, x = x1_10_cast_fp16)[name = tensor("op_1328_cast_fp16")]; tensor var_1329 = const()[name = tensor("op_1329"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_10_cast_fp16 = reshape(shape = var_1329, x = var_1328_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_76_perm_0 = const()[name = tensor("transpose_76_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_77_perm_0 = const()[name = tensor("transpose_77_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_77 = transpose(perm = transpose_77_perm_0, x = k_10_cast_fp16)[name = tensor("transpose_216")]; tensor transpose_76 = transpose(perm = transpose_76_perm_0, x = var_1312_cast_fp16)[name = tensor("transpose_217")]; 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_76, y = transpose_77)[name = tensor("matrix_ac_10_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_10_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_10_end_0, end_mask = matrix_bd0_10_end_mask_0, x = matrix_bd_10_cast_fp16)[name = tensor("matrix_bd0_10_cast_fp16")]; tensor var_1338_cast_fp16 = add(x = matrix_ac_10_cast_fp16, y = matrix_bd0_10_cast_fp16)[name = tensor("op_1338_cast_fp16")]; tensor _inversed_scores_10_y_0_to_fp16 = const()[name = tensor("_inversed_scores_10_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_10_cast_fp16 = mul(x = var_1338_cast_fp16, y = _inversed_scores_10_y_0_to_fp16)[name = tensor("_inversed_scores_10_cast_fp16")]; tensor scores0_10_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_10_cast_fp16, cond = mask0_4)[name = tensor("scores0_10_cast_fp16")]; tensor var_1344_cast_fp16 = softmax(axis = var_47, x = scores0_10_cast_fp16)[name = tensor("op_1344_cast_fp16")]; tensor input0_59_cast_fp16 = select(a = var_26_to_fp16, b = var_1344_cast_fp16, cond = mask0_4)[name = tensor("input0_59_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 value_12_cast_fp16 = transpose(perm = value_12_perm_0, x = v_10_cast_fp16)[name = tensor("transpose_215")]; tensor x2_10_cast_fp16 = matmul(transpose_x = x2_10_transpose_x_0, transpose_y = x2_10_transpose_y_0, x = input0_59_cast_fp16, y = value_12_cast_fp16)[name = tensor("x2_10_cast_fp16")]; tensor var_1348_perm_0 = const()[name = tensor("op_1348_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_1349 = const()[name = tensor("op_1349"), val = tensor([1, -1, 512])]; tensor var_1348_cast_fp16 = transpose(perm = var_1348_perm_0, x = x2_10_cast_fp16)[name = tensor("transpose_214")]; tensor input1_30_cast_fp16 = reshape(shape = var_1349, x = var_1348_cast_fp16)[name = tensor("input1_30_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(29897664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30159872))), name = tensor("encoder_layers_4_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_30_cast_fp16)[name = tensor("linear_43_cast_fp16")]; tensor input0_61_cast_fp16 = add(x = input_61_cast_fp16, y = linear_43_cast_fp16)[name = tensor("input0_61_cast_fp16")]; tensor x_95_axes_0 = const()[name = tensor("x_95_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(30160448)))]; 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(30161536)))]; tensor x_95_cast_fp16 = layer_norm(axes = x_95_axes_0, beta = encoder_layers_4_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_4_norm_conv_weight_to_fp16, x = input0_61_cast_fp16)[name = tensor("x_95_cast_fp16")]; tensor input_65_perm_0 = const()[name = tensor("input_65_perm_0"), val = tensor([0, 2, 1])]; tensor input0_63_pad_type_0 = const()[name = tensor("input0_63_pad_type_0"), val = tensor("valid")]; tensor input0_63_strides_0 = const()[name = tensor("input0_63_strides_0"), val = tensor([1])]; tensor input0_63_pad_0 = const()[name = tensor("input0_63_pad_0"), val = tensor([0, 0])]; tensor input0_63_dilations_0 = const()[name = tensor("input0_63_dilations_0"), val = tensor([1])]; tensor input0_63_groups_0 = const()[name = tensor("input0_63_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(30162624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30686976))), name = tensor("encoder_layers_4_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_65_cast_fp16 = transpose(perm = input_65_perm_0, x = x_95_cast_fp16)[name = tensor("transpose_213")]; tensor input0_63_cast_fp16 = conv(dilations = input0_63_dilations_0, groups = input0_63_groups_0, pad = input0_63_pad_0, pad_type = input0_63_pad_type_0, strides = input0_63_strides_0, weight = encoder_layers_4_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_65_cast_fp16)[name = tensor("input0_63_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_63_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_65_cast_fp16 = select(a = var_26_to_fp16, b = x_97_cast_fp16, cond = var_546)[name = tensor("input0_65_cast_fp16")]; tensor new_x0_10_interleave_0 = const()[name = tensor("new_x0_10_interleave_0"), val = tensor(false)]; tensor new_x0_10_cast_fp16 = concat(axis = var_47, interleave = new_x0_10_interleave_0, values = (cache8_1_cast_fp16, input0_65_cast_fp16))[name = tensor("new_x0_10_cast_fp16")]; tensor next_cache_10_begin_0 = const()[name = tensor("next_cache_10_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_10_end_0 = const()[name = tensor("next_cache_10_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_10_end_mask_0 = const()[name = tensor("next_cache_10_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_10_cast_fp16 = slice_by_index(begin = next_cache_10_begin_0, end = next_cache_10_end_0, end_mask = next_cache_10_end_mask_0, x = new_x0_10_cast_fp16)[name = tensor("next_cache_10_cast_fp16")]; tensor var_1390_begin_0 = const()[name = tensor("op_1390_begin_0"), val = tensor([0, 0, 4])]; tensor var_1390_end_0 = const()[name = tensor("op_1390_end_0"), val = tensor([1, 512, 12])]; tensor var_1390_end_mask_0 = const()[name = tensor("op_1390_end_mask_0"), val = tensor([true, true, true])]; tensor var_1390_cast_fp16 = slice_by_index(begin = var_1390_begin_0, end = var_1390_end_0, end_mask = var_1390_end_mask_0, x = next_cache_10_cast_fp16)[name = tensor("op_1390_cast_fp16")]; tensor x_99_pad_type_0 = const()[name = tensor("x_99_pad_type_0"), val = tensor("valid")]; tensor x_99_groups_0 = const()[name = tensor("x_99_groups_0"), val = tensor(512)]; 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 encoder_layers_4_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30687552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30692224))), name = tensor("encoder_layers_4_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; 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_4_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_10_cast_fp16)[name = tensor("x_99_cast_fp16")]; tensor input1_32_perm_0 = const()[name = tensor("input1_32_perm_0"), val = tensor([0, 2, 1])]; tensor x_101_axes_0 = const()[name = tensor("x_101_axes_0"), val = tensor([-1])]; tensor encoder_layers_4_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_4_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30692800)))]; tensor encoder_layers_4_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_4_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30693888)))]; tensor input1_32_cast_fp16 = transpose(perm = input1_32_perm_0, x = x_99_cast_fp16)[name = tensor("transpose_212")]; tensor x_101_cast_fp16 = layer_norm(axes = x_101_axes_0, beta = encoder_layers_4_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_4_conv_batch_norm_weight_to_fp16, x = input1_32_cast_fp16)[name = tensor("x_101_cast_fp16")]; tensor input2_20_perm_0 = const()[name = tensor("input2_20_perm_0"), val = tensor([0, 2, 1])]; tensor input2_20_cast_fp16 = transpose(perm = input2_20_perm_0, x = x_101_cast_fp16)[name = tensor("transpose_211")]; tensor var_1405_cast_fp16 = silu(x = input2_20_cast_fp16)[name = tensor("op_1405_cast_fp16")]; tensor x_103_pad_type_0 = const()[name = tensor("x_103_pad_type_0"), val = tensor("valid")]; tensor x_103_strides_0 = const()[name = tensor("x_103_strides_0"), val = tensor([1])]; tensor x_103_pad_0 = const()[name = tensor("x_103_pad_0"), val = tensor([0, 0])]; tensor x_103_dilations_0 = const()[name = tensor("x_103_dilations_0"), val = tensor([1])]; tensor x_103_groups_0 = const()[name = tensor("x_103_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(30694976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30957184))), name = tensor("encoder_layers_4_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_103_cast_fp16 = conv(dilations = x_103_dilations_0, groups = x_103_groups_0, pad = x_103_pad_0, pad_type = x_103_pad_type_0, strides = x_103_strides_0, weight = encoder_layers_4_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1405_cast_fp16)[name = tensor("x_103_cast_fp16")]; tensor input3_12_perm_0 = const()[name = tensor("input3_12_perm_0"), val = tensor([0, 2, 1])]; tensor input3_12_cast_fp16 = transpose(perm = input3_12_perm_0, x = x_103_cast_fp16)[name = tensor("transpose_210")]; tensor input1_34_cast_fp16 = add(x = input0_61_cast_fp16, y = input3_12_cast_fp16)[name = tensor("input1_34_cast_fp16")]; tensor input0_67_axes_0 = const()[name = tensor("input0_67_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(30957760)))]; 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(30958848)))]; tensor input0_67_cast_fp16 = layer_norm(axes = input0_67_axes_0, beta = encoder_layers_4_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_4_norm_feed_forward2_weight_to_fp16, x = input1_34_cast_fp16)[name = tensor("input0_67_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(30959936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32008576))), name = tensor("encoder_layers_4_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_67_cast_fp16)[name = tensor("linear_44_cast_fp16")]; tensor var_1426_cast_fp16 = silu(x = linear_44_cast_fp16)[name = tensor("op_1426_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(32009152))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33057792))), name = tensor("encoder_layers_4_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1426_cast_fp16)[name = tensor("linear_45_cast_fp16")]; tensor var_1431_to_fp16 = const()[name = tensor("op_1431_to_fp16"), val = tensor(0x1p-1)]; tensor var_1432_cast_fp16 = mul(x = linear_45_cast_fp16, y = var_1431_to_fp16)[name = tensor("op_1432_cast_fp16")]; tensor input2_22_cast_fp16 = add(x = input1_34_cast_fp16, y = var_1432_cast_fp16)[name = tensor("input2_22_cast_fp16")]; tensor input0_69_axes_0 = const()[name = tensor("input0_69_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(33058368)))]; 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(33059456)))]; tensor input0_69_cast_fp16 = layer_norm(axes = input0_69_axes_0, beta = encoder_layers_4_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_4_norm_out_weight_to_fp16, x = input2_22_cast_fp16)[name = tensor("input0_69_cast_fp16")]; tensor cache9_1_begin_0 = const()[name = tensor("cache9_1_begin_0"), val = tensor([5, 0, 0, 0])]; tensor cache9_1_end_0 = const()[name = tensor("cache9_1_end_0"), val = tensor([6, 1, 70, 512])]; tensor cache9_1_end_mask_0 = const()[name = tensor("cache9_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache9_1_squeeze_mask_0 = const()[name = tensor("cache9_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache9_1_cast_fp16 = slice_by_index(begin = cache9_1_begin_0, end = cache9_1_end_0, end_mask = cache9_1_end_mask_0, squeeze_mask = cache9_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache9_1_cast_fp16")]; tensor cache10_1_begin_0 = const()[name = tensor("cache10_1_begin_0"), val = tensor([5, 0, 0, 0])]; tensor cache10_1_end_0 = const()[name = tensor("cache10_1_end_0"), val = tensor([6, 1, 512, 8])]; tensor cache10_1_end_mask_0 = const()[name = tensor("cache10_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache10_1_squeeze_mask_0 = const()[name = tensor("cache10_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache10_1_cast_fp16 = slice_by_index(begin = cache10_1_begin_0, end = cache10_1_end_0, end_mask = cache10_1_end_mask_0, squeeze_mask = cache10_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache10_1_cast_fp16")]; tensor input_69_axes_0 = const()[name = tensor("input_69_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(33060544)))]; 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(33061632)))]; tensor input_69_cast_fp16 = layer_norm(axes = input_69_axes_0, beta = encoder_layers_5_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_5_norm_feed_forward1_weight_to_fp16, x = input0_69_cast_fp16)[name = tensor("input_69_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(33062720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(34111360))), name = tensor("encoder_layers_5_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_69_cast_fp16)[name = tensor("linear_46_cast_fp16")]; tensor var_1461_cast_fp16 = silu(x = linear_46_cast_fp16)[name = tensor("op_1461_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(34111936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35160576))), name = tensor("encoder_layers_5_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1461_cast_fp16)[name = tensor("linear_47_cast_fp16")]; tensor var_1466_to_fp16 = const()[name = tensor("op_1466_to_fp16"), val = tensor(0x1p-1)]; tensor var_1467_cast_fp16 = mul(x = linear_47_cast_fp16, y = var_1466_to_fp16)[name = tensor("op_1467_cast_fp16")]; tensor input_73_cast_fp16 = add(x = input0_69_cast_fp16, y = var_1467_cast_fp16)[name = tensor("input_73_cast_fp16")]; tensor key_12_axes_0 = const()[name = tensor("key_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(35161152)))]; 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(35162240)))]; tensor key_12_cast_fp16 = layer_norm(axes = key_12_axes_0, beta = encoder_layers_5_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_5_norm_self_att_weight_to_fp16, x = input_73_cast_fp16)[name = tensor("key_12_cast_fp16")]; tensor input_75_interleave_0 = const()[name = tensor("input_75_interleave_0"), val = tensor(false)]; tensor input_75_cast_fp16 = concat(axis = var_55, interleave = input_75_interleave_0, values = (cache9_1_cast_fp16, key_12_cast_fp16))[name = tensor("input_75_cast_fp16")]; tensor var_1489_begin_0 = const()[name = tensor("op_1489_begin_0"), val = tensor([0, 4, 0])]; tensor var_1489_end_0 = const()[name = tensor("op_1489_end_0"), val = tensor([1, 70, 512])]; tensor var_1489_end_mask_0 = const()[name = tensor("op_1489_end_mask_0"), val = tensor([true, true, true])]; tensor var_1489_cast_fp16 = slice_by_index(begin = var_1489_begin_0, end = var_1489_end_0, end_mask = var_1489_end_mask_0, x = cache9_1_cast_fp16)[name = tensor("op_1489_cast_fp16")]; tensor var_1492_begin_0 = const()[name = tensor("op_1492_begin_0"), val = tensor([0, 0, 0])]; tensor var_1492_end_0 = const()[name = tensor("op_1492_end_0"), val = tensor([1, 4, 512])]; tensor var_1492_end_mask_0 = const()[name = tensor("op_1492_end_mask_0"), val = tensor([true, false, true])]; tensor var_1492_cast_fp16 = slice_by_index(begin = var_1492_begin_0, end = var_1492_end_0, end_mask = var_1492_end_mask_0, x = key_12_cast_fp16)[name = tensor("op_1492_cast_fp16")]; tensor var_1495_interleave_0 = const()[name = tensor("op_1495_interleave_0"), val = tensor(false)]; tensor var_1495_cast_fp16 = concat(axis = var_55, interleave = var_1495_interleave_0, values = (var_1489_cast_fp16, var_1492_cast_fp16))[name = tensor("op_1495_cast_fp16")]; 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(35163328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35425536))), name = tensor("encoder_layers_5_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_12_cast_fp16)[name = tensor("linear_48_cast_fp16")]; tensor var_1499 = const()[name = tensor("op_1499"), val = tensor([1, -1, 8, 64])]; tensor q_12_cast_fp16 = reshape(shape = var_1499, 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(35426112))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35688320))), name = tensor("encoder_layers_5_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_75_cast_fp16)[name = tensor("linear_49_cast_fp16")]; tensor var_1503 = const()[name = tensor("op_1503"), val = tensor([1, -1, 8, 64])]; tensor k_12_cast_fp16 = reshape(shape = var_1503, 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(35688896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35951104))), name = tensor("encoder_layers_5_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_75_cast_fp16)[name = tensor("linear_50_cast_fp16")]; tensor var_1507 = const()[name = tensor("op_1507"), val = tensor([1, -1, 8, 64])]; tensor v_12_cast_fp16 = reshape(shape = var_1507, x = linear_50_cast_fp16)[name = tensor("v_12_cast_fp16")]; tensor value_14_perm_0 = const()[name = tensor("value_14_perm_0"), val = tensor([0, 2, -3, -1])]; 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(35951680)))]; tensor var_1519_cast_fp16 = add(x = q_12_cast_fp16, y = encoder_layers_5_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1519_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(35952768)))]; tensor var_1521_cast_fp16 = add(x = q_12_cast_fp16, y = encoder_layers_5_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1521_cast_fp16")]; tensor q_with_bias_v_12_perm_0 = const()[name = tensor("q_with_bias_v_12_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_111_transpose_x_0 = const()[name = tensor("x_111_transpose_x_0"), val = tensor(false)]; tensor x_111_transpose_y_0 = const()[name = tensor("x_111_transpose_y_0"), val = tensor(false)]; tensor op_1523_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35953856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36033280))), name = tensor("op_1523_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_12_cast_fp16 = transpose(perm = q_with_bias_v_12_perm_0, x = var_1521_cast_fp16)[name = tensor("transpose_209")]; tensor x_111_cast_fp16 = matmul(transpose_x = x_111_transpose_x_0, transpose_y = x_111_transpose_y_0, x = q_with_bias_v_12_cast_fp16, y = op_1523_to_fp16_palettized)[name = tensor("x_111_cast_fp16")]; 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_144_to_fp16 = const()[name = tensor("const_144_to_fp16"), val = tensor(0x0p+0)]; tensor x0_14_cast_fp16 = pad(constant_val = const_144_to_fp16, mode = x0_14_mode_0, pad = x0_14_pad_0, x = x_111_cast_fp16)[name = tensor("x0_14_cast_fp16")]; tensor var_1531 = const()[name = tensor("op_1531"), val = tensor([1, 8, -1, 8])]; tensor x1_12_cast_fp16 = reshape(shape = var_1531, x = x0_14_cast_fp16)[name = tensor("x1_12_cast_fp16")]; tensor var_1535_begin_0 = const()[name = tensor("op_1535_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1535_end_0 = const()[name = tensor("op_1535_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_1535_end_mask_0 = const()[name = tensor("op_1535_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1535_cast_fp16 = slice_by_index(begin = var_1535_begin_0, end = var_1535_end_0, end_mask = var_1535_end_mask_0, x = x1_12_cast_fp16)[name = tensor("op_1535_cast_fp16")]; tensor var_1536 = const()[name = tensor("op_1536"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_12_cast_fp16 = reshape(shape = var_1536, x = var_1535_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_78_perm_0 = const()[name = tensor("transpose_78_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_79_perm_0 = const()[name = tensor("transpose_79_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_79 = transpose(perm = transpose_79_perm_0, x = k_12_cast_fp16)[name = tensor("transpose_207")]; tensor transpose_78 = transpose(perm = transpose_78_perm_0, x = var_1519_cast_fp16)[name = tensor("transpose_208")]; 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_78, y = transpose_79)[name = tensor("matrix_ac_12_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_12_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_12_end_0, end_mask = matrix_bd0_12_end_mask_0, x = matrix_bd_12_cast_fp16)[name = tensor("matrix_bd0_12_cast_fp16")]; tensor var_1545_cast_fp16 = add(x = matrix_ac_12_cast_fp16, y = matrix_bd0_12_cast_fp16)[name = tensor("op_1545_cast_fp16")]; tensor _inversed_scores_12_y_0_to_fp16 = const()[name = tensor("_inversed_scores_12_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_12_cast_fp16 = mul(x = var_1545_cast_fp16, y = _inversed_scores_12_y_0_to_fp16)[name = tensor("_inversed_scores_12_cast_fp16")]; tensor scores0_12_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_12_cast_fp16, cond = mask0_4)[name = tensor("scores0_12_cast_fp16")]; tensor var_1551_cast_fp16 = softmax(axis = var_47, x = scores0_12_cast_fp16)[name = tensor("op_1551_cast_fp16")]; tensor input0_71_cast_fp16 = select(a = var_26_to_fp16, b = var_1551_cast_fp16, cond = mask0_4)[name = tensor("input0_71_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 value_14_cast_fp16 = transpose(perm = value_14_perm_0, x = v_12_cast_fp16)[name = tensor("transpose_206")]; tensor x2_12_cast_fp16 = matmul(transpose_x = x2_12_transpose_x_0, transpose_y = x2_12_transpose_y_0, x = input0_71_cast_fp16, y = value_14_cast_fp16)[name = tensor("x2_12_cast_fp16")]; tensor var_1555_perm_0 = const()[name = tensor("op_1555_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_1556 = const()[name = tensor("op_1556"), val = tensor([1, -1, 512])]; tensor var_1555_cast_fp16 = transpose(perm = var_1555_perm_0, x = x2_12_cast_fp16)[name = tensor("transpose_205")]; tensor input1_36_cast_fp16 = reshape(shape = var_1556, x = var_1555_cast_fp16)[name = tensor("input1_36_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(36033856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36296064))), name = tensor("encoder_layers_5_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_36_cast_fp16)[name = tensor("linear_52_cast_fp16")]; tensor input0_73_cast_fp16 = add(x = input_73_cast_fp16, y = linear_52_cast_fp16)[name = tensor("input0_73_cast_fp16")]; tensor x_115_axes_0 = const()[name = tensor("x_115_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(36296640)))]; 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(36297728)))]; tensor x_115_cast_fp16 = layer_norm(axes = x_115_axes_0, beta = encoder_layers_5_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_5_norm_conv_weight_to_fp16, x = input0_73_cast_fp16)[name = tensor("x_115_cast_fp16")]; tensor input_77_perm_0 = const()[name = tensor("input_77_perm_0"), val = tensor([0, 2, 1])]; tensor input0_75_pad_type_0 = const()[name = tensor("input0_75_pad_type_0"), val = tensor("valid")]; tensor input0_75_strides_0 = const()[name = tensor("input0_75_strides_0"), val = tensor([1])]; tensor input0_75_pad_0 = const()[name = tensor("input0_75_pad_0"), val = tensor([0, 0])]; tensor input0_75_dilations_0 = const()[name = tensor("input0_75_dilations_0"), val = tensor([1])]; tensor input0_75_groups_0 = const()[name = tensor("input0_75_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(36298816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36823168))), name = tensor("encoder_layers_5_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_77_cast_fp16 = transpose(perm = input_77_perm_0, x = x_115_cast_fp16)[name = tensor("transpose_204")]; tensor input0_75_cast_fp16 = conv(dilations = input0_75_dilations_0, groups = input0_75_groups_0, pad = input0_75_pad_0, pad_type = input0_75_pad_type_0, strides = input0_75_strides_0, weight = encoder_layers_5_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_77_cast_fp16)[name = tensor("input0_75_cast_fp16")]; tensor x_117_split_num_splits_0 = const()[name = tensor("x_117_split_num_splits_0"), val = tensor(2)]; tensor x_117_split_axis_0 = const()[name = tensor("x_117_split_axis_0"), val = tensor(1)]; tensor x_117_split_cast_fp16_0, tensor x_117_split_cast_fp16_1 = split(axis = x_117_split_axis_0, num_splits = x_117_split_num_splits_0, x = input0_75_cast_fp16)[name = tensor("x_117_split_cast_fp16")]; tensor x_117_split_1_sigmoid_cast_fp16 = sigmoid(x = x_117_split_cast_fp16_1)[name = tensor("x_117_split_1_sigmoid_cast_fp16")]; tensor x_117_cast_fp16 = mul(x = x_117_split_cast_fp16_0, y = x_117_split_1_sigmoid_cast_fp16)[name = tensor("x_117_cast_fp16")]; tensor input0_77_cast_fp16 = select(a = var_26_to_fp16, b = x_117_cast_fp16, cond = var_546)[name = tensor("input0_77_cast_fp16")]; tensor new_x0_12_interleave_0 = const()[name = tensor("new_x0_12_interleave_0"), val = tensor(false)]; tensor new_x0_12_cast_fp16 = concat(axis = var_47, interleave = new_x0_12_interleave_0, values = (cache10_1_cast_fp16, input0_77_cast_fp16))[name = tensor("new_x0_12_cast_fp16")]; tensor next_cache_12_begin_0 = const()[name = tensor("next_cache_12_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_12_end_0 = const()[name = tensor("next_cache_12_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_12_end_mask_0 = const()[name = tensor("next_cache_12_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_12_cast_fp16 = slice_by_index(begin = next_cache_12_begin_0, end = next_cache_12_end_0, end_mask = next_cache_12_end_mask_0, x = new_x0_12_cast_fp16)[name = tensor("next_cache_12_cast_fp16")]; tensor var_1597_begin_0 = const()[name = tensor("op_1597_begin_0"), val = tensor([0, 0, 4])]; tensor var_1597_end_0 = const()[name = tensor("op_1597_end_0"), val = tensor([1, 512, 12])]; tensor var_1597_end_mask_0 = const()[name = tensor("op_1597_end_mask_0"), val = tensor([true, true, true])]; tensor var_1597_cast_fp16 = slice_by_index(begin = var_1597_begin_0, end = var_1597_end_0, end_mask = var_1597_end_mask_0, x = next_cache_12_cast_fp16)[name = tensor("op_1597_cast_fp16")]; tensor x_119_pad_type_0 = const()[name = tensor("x_119_pad_type_0"), val = tensor("valid")]; tensor x_119_groups_0 = const()[name = tensor("x_119_groups_0"), val = tensor(512)]; tensor x_119_strides_0 = const()[name = tensor("x_119_strides_0"), val = tensor([1])]; tensor x_119_pad_0 = const()[name = tensor("x_119_pad_0"), val = tensor([0, 0])]; tensor x_119_dilations_0 = const()[name = tensor("x_119_dilations_0"), val = tensor([1])]; tensor encoder_layers_5_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36823744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36828416))), name = tensor("encoder_layers_5_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_119_cast_fp16 = conv(dilations = x_119_dilations_0, groups = x_119_groups_0, pad = x_119_pad_0, pad_type = x_119_pad_type_0, strides = x_119_strides_0, weight = encoder_layers_5_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_12_cast_fp16)[name = tensor("x_119_cast_fp16")]; tensor input1_38_perm_0 = const()[name = tensor("input1_38_perm_0"), val = tensor([0, 2, 1])]; tensor x_121_axes_0 = const()[name = tensor("x_121_axes_0"), val = tensor([-1])]; tensor encoder_layers_5_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_5_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36828992)))]; tensor encoder_layers_5_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_5_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36830080)))]; tensor input1_38_cast_fp16 = transpose(perm = input1_38_perm_0, x = x_119_cast_fp16)[name = tensor("transpose_203")]; tensor x_121_cast_fp16 = layer_norm(axes = x_121_axes_0, beta = encoder_layers_5_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_5_conv_batch_norm_weight_to_fp16, x = input1_38_cast_fp16)[name = tensor("x_121_cast_fp16")]; tensor input2_24_perm_0 = const()[name = tensor("input2_24_perm_0"), val = tensor([0, 2, 1])]; tensor input2_24_cast_fp16 = transpose(perm = input2_24_perm_0, x = x_121_cast_fp16)[name = tensor("transpose_202")]; tensor var_1612_cast_fp16 = silu(x = input2_24_cast_fp16)[name = tensor("op_1612_cast_fp16")]; tensor x_123_pad_type_0 = const()[name = tensor("x_123_pad_type_0"), val = tensor("valid")]; tensor x_123_strides_0 = const()[name = tensor("x_123_strides_0"), val = tensor([1])]; tensor x_123_pad_0 = const()[name = tensor("x_123_pad_0"), val = tensor([0, 0])]; tensor x_123_dilations_0 = const()[name = tensor("x_123_dilations_0"), val = tensor([1])]; tensor x_123_groups_0 = const()[name = tensor("x_123_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(36831168))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(37093376))), name = tensor("encoder_layers_5_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_123_cast_fp16 = conv(dilations = x_123_dilations_0, groups = x_123_groups_0, pad = x_123_pad_0, pad_type = x_123_pad_type_0, strides = x_123_strides_0, weight = encoder_layers_5_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1612_cast_fp16)[name = tensor("x_123_cast_fp16")]; tensor input3_14_perm_0 = const()[name = tensor("input3_14_perm_0"), val = tensor([0, 2, 1])]; tensor input3_14_cast_fp16 = transpose(perm = input3_14_perm_0, x = x_123_cast_fp16)[name = tensor("transpose_201")]; tensor input1_40_cast_fp16 = add(x = input0_73_cast_fp16, y = input3_14_cast_fp16)[name = tensor("input1_40_cast_fp16")]; tensor input0_79_axes_0 = const()[name = tensor("input0_79_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(37093952)))]; 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(37095040)))]; tensor input0_79_cast_fp16 = layer_norm(axes = input0_79_axes_0, beta = encoder_layers_5_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_5_norm_feed_forward2_weight_to_fp16, x = input1_40_cast_fp16)[name = tensor("input0_79_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(37096128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38144768))), name = tensor("encoder_layers_5_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_79_cast_fp16)[name = tensor("linear_53_cast_fp16")]; tensor var_1633_cast_fp16 = silu(x = linear_53_cast_fp16)[name = tensor("op_1633_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(38145344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(39193984))), name = tensor("encoder_layers_5_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1633_cast_fp16)[name = tensor("linear_54_cast_fp16")]; tensor var_1638_to_fp16 = const()[name = tensor("op_1638_to_fp16"), val = tensor(0x1p-1)]; tensor var_1639_cast_fp16 = mul(x = linear_54_cast_fp16, y = var_1638_to_fp16)[name = tensor("op_1639_cast_fp16")]; tensor input2_26_cast_fp16 = add(x = input1_40_cast_fp16, y = var_1639_cast_fp16)[name = tensor("input2_26_cast_fp16")]; tensor input0_81_axes_0 = const()[name = tensor("input0_81_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(39194560)))]; 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(39195648)))]; tensor input0_81_cast_fp16 = layer_norm(axes = input0_81_axes_0, beta = encoder_layers_5_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_5_norm_out_weight_to_fp16, x = input2_26_cast_fp16)[name = tensor("input0_81_cast_fp16")]; tensor cache11_1_begin_0 = const()[name = tensor("cache11_1_begin_0"), val = tensor([6, 0, 0, 0])]; tensor cache11_1_end_0 = const()[name = tensor("cache11_1_end_0"), val = tensor([7, 1, 70, 512])]; tensor cache11_1_end_mask_0 = const()[name = tensor("cache11_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache11_1_squeeze_mask_0 = const()[name = tensor("cache11_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache11_1_cast_fp16 = slice_by_index(begin = cache11_1_begin_0, end = cache11_1_end_0, end_mask = cache11_1_end_mask_0, squeeze_mask = cache11_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache11_1_cast_fp16")]; tensor cache12_1_begin_0 = const()[name = tensor("cache12_1_begin_0"), val = tensor([6, 0, 0, 0])]; tensor cache12_1_end_0 = const()[name = tensor("cache12_1_end_0"), val = tensor([7, 1, 512, 8])]; tensor cache12_1_end_mask_0 = const()[name = tensor("cache12_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache12_1_squeeze_mask_0 = const()[name = tensor("cache12_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache12_1_cast_fp16 = slice_by_index(begin = cache12_1_begin_0, end = cache12_1_end_0, end_mask = cache12_1_end_mask_0, squeeze_mask = cache12_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache12_1_cast_fp16")]; tensor input_81_axes_0 = const()[name = tensor("input_81_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(39196736)))]; 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(39197824)))]; tensor input_81_cast_fp16 = layer_norm(axes = input_81_axes_0, beta = encoder_layers_6_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_6_norm_feed_forward1_weight_to_fp16, x = input0_81_cast_fp16)[name = tensor("input_81_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(39198912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40247552))), name = tensor("encoder_layers_6_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_81_cast_fp16)[name = tensor("linear_55_cast_fp16")]; tensor var_1668_cast_fp16 = silu(x = linear_55_cast_fp16)[name = tensor("op_1668_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(40248128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41296768))), name = tensor("encoder_layers_6_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1668_cast_fp16)[name = tensor("linear_56_cast_fp16")]; tensor var_1673_to_fp16 = const()[name = tensor("op_1673_to_fp16"), val = tensor(0x1p-1)]; tensor var_1674_cast_fp16 = mul(x = linear_56_cast_fp16, y = var_1673_to_fp16)[name = tensor("op_1674_cast_fp16")]; tensor input_85_cast_fp16 = add(x = input0_81_cast_fp16, y = var_1674_cast_fp16)[name = tensor("input_85_cast_fp16")]; tensor key_14_axes_0 = const()[name = tensor("key_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(41297344)))]; 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(41298432)))]; tensor key_14_cast_fp16 = layer_norm(axes = key_14_axes_0, beta = encoder_layers_6_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_6_norm_self_att_weight_to_fp16, x = input_85_cast_fp16)[name = tensor("key_14_cast_fp16")]; tensor input_87_interleave_0 = const()[name = tensor("input_87_interleave_0"), val = tensor(false)]; tensor input_87_cast_fp16 = concat(axis = var_55, interleave = input_87_interleave_0, values = (cache11_1_cast_fp16, key_14_cast_fp16))[name = tensor("input_87_cast_fp16")]; tensor var_1696_begin_0 = const()[name = tensor("op_1696_begin_0"), val = tensor([0, 4, 0])]; tensor var_1696_end_0 = const()[name = tensor("op_1696_end_0"), val = tensor([1, 70, 512])]; tensor var_1696_end_mask_0 = const()[name = tensor("op_1696_end_mask_0"), val = tensor([true, true, true])]; tensor var_1696_cast_fp16 = slice_by_index(begin = var_1696_begin_0, end = var_1696_end_0, end_mask = var_1696_end_mask_0, x = cache11_1_cast_fp16)[name = tensor("op_1696_cast_fp16")]; tensor var_1699_begin_0 = const()[name = tensor("op_1699_begin_0"), val = tensor([0, 0, 0])]; tensor var_1699_end_0 = const()[name = tensor("op_1699_end_0"), val = tensor([1, 4, 512])]; tensor var_1699_end_mask_0 = const()[name = tensor("op_1699_end_mask_0"), val = tensor([true, false, true])]; tensor var_1699_cast_fp16 = slice_by_index(begin = var_1699_begin_0, end = var_1699_end_0, end_mask = var_1699_end_mask_0, x = key_14_cast_fp16)[name = tensor("op_1699_cast_fp16")]; tensor var_1702_interleave_0 = const()[name = tensor("op_1702_interleave_0"), val = tensor(false)]; tensor var_1702_cast_fp16 = concat(axis = var_55, interleave = var_1702_interleave_0, values = (var_1696_cast_fp16, var_1699_cast_fp16))[name = tensor("op_1702_cast_fp16")]; 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(41299520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41561728))), name = tensor("encoder_layers_6_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_14_cast_fp16)[name = tensor("linear_57_cast_fp16")]; tensor var_1706 = const()[name = tensor("op_1706"), val = tensor([1, -1, 8, 64])]; tensor q_14_cast_fp16 = reshape(shape = var_1706, 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(41562304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41824512))), name = tensor("encoder_layers_6_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_87_cast_fp16)[name = tensor("linear_58_cast_fp16")]; tensor var_1710 = const()[name = tensor("op_1710"), val = tensor([1, -1, 8, 64])]; tensor k_14_cast_fp16 = reshape(shape = var_1710, 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(41825088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42087296))), name = tensor("encoder_layers_6_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_87_cast_fp16)[name = tensor("linear_59_cast_fp16")]; tensor var_1714 = const()[name = tensor("op_1714"), val = tensor([1, -1, 8, 64])]; tensor v_14_cast_fp16 = reshape(shape = var_1714, x = linear_59_cast_fp16)[name = tensor("v_14_cast_fp16")]; tensor value_16_perm_0 = const()[name = tensor("value_16_perm_0"), val = tensor([0, 2, -3, -1])]; 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(42087872)))]; tensor var_1726_cast_fp16 = add(x = q_14_cast_fp16, y = encoder_layers_6_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1726_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(42088960)))]; tensor var_1728_cast_fp16 = add(x = q_14_cast_fp16, y = encoder_layers_6_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1728_cast_fp16")]; tensor q_with_bias_v_14_perm_0 = const()[name = tensor("q_with_bias_v_14_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_131_transpose_x_0 = const()[name = tensor("x_131_transpose_x_0"), val = tensor(false)]; tensor x_131_transpose_y_0 = const()[name = tensor("x_131_transpose_y_0"), val = tensor(false)]; tensor op_1730_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42090048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42169472))), name = tensor("op_1730_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_14_cast_fp16 = transpose(perm = q_with_bias_v_14_perm_0, x = var_1728_cast_fp16)[name = tensor("transpose_200")]; tensor x_131_cast_fp16 = matmul(transpose_x = x_131_transpose_x_0, transpose_y = x_131_transpose_y_0, x = q_with_bias_v_14_cast_fp16, y = op_1730_to_fp16_palettized)[name = tensor("x_131_cast_fp16")]; 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_157_to_fp16 = const()[name = tensor("const_157_to_fp16"), val = tensor(0x0p+0)]; tensor x0_16_cast_fp16 = pad(constant_val = const_157_to_fp16, mode = x0_16_mode_0, pad = x0_16_pad_0, x = x_131_cast_fp16)[name = tensor("x0_16_cast_fp16")]; tensor var_1738 = const()[name = tensor("op_1738"), val = tensor([1, 8, -1, 8])]; tensor x1_14_cast_fp16 = reshape(shape = var_1738, x = x0_16_cast_fp16)[name = tensor("x1_14_cast_fp16")]; tensor var_1742_begin_0 = const()[name = tensor("op_1742_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1742_end_0 = const()[name = tensor("op_1742_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_1742_end_mask_0 = const()[name = tensor("op_1742_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1742_cast_fp16 = slice_by_index(begin = var_1742_begin_0, end = var_1742_end_0, end_mask = var_1742_end_mask_0, x = x1_14_cast_fp16)[name = tensor("op_1742_cast_fp16")]; tensor var_1743 = const()[name = tensor("op_1743"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_14_cast_fp16 = reshape(shape = var_1743, x = var_1742_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_80_perm_0 = const()[name = tensor("transpose_80_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_81_perm_0 = const()[name = tensor("transpose_81_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_81 = transpose(perm = transpose_81_perm_0, x = k_14_cast_fp16)[name = tensor("transpose_198")]; tensor transpose_80 = transpose(perm = transpose_80_perm_0, x = var_1726_cast_fp16)[name = tensor("transpose_199")]; 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_80, y = transpose_81)[name = tensor("matrix_ac_14_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_14_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_14_end_0, end_mask = matrix_bd0_14_end_mask_0, x = matrix_bd_14_cast_fp16)[name = tensor("matrix_bd0_14_cast_fp16")]; tensor var_1752_cast_fp16 = add(x = matrix_ac_14_cast_fp16, y = matrix_bd0_14_cast_fp16)[name = tensor("op_1752_cast_fp16")]; tensor _inversed_scores_14_y_0_to_fp16 = const()[name = tensor("_inversed_scores_14_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_14_cast_fp16 = mul(x = var_1752_cast_fp16, y = _inversed_scores_14_y_0_to_fp16)[name = tensor("_inversed_scores_14_cast_fp16")]; tensor scores0_14_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_14_cast_fp16, cond = mask0_4)[name = tensor("scores0_14_cast_fp16")]; tensor var_1758_cast_fp16 = softmax(axis = var_47, x = scores0_14_cast_fp16)[name = tensor("op_1758_cast_fp16")]; tensor input0_83_cast_fp16 = select(a = var_26_to_fp16, b = var_1758_cast_fp16, cond = mask0_4)[name = tensor("input0_83_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 value_16_cast_fp16 = transpose(perm = value_16_perm_0, x = v_14_cast_fp16)[name = tensor("transpose_197")]; tensor x2_14_cast_fp16 = matmul(transpose_x = x2_14_transpose_x_0, transpose_y = x2_14_transpose_y_0, x = input0_83_cast_fp16, y = value_16_cast_fp16)[name = tensor("x2_14_cast_fp16")]; tensor var_1762_perm_0 = const()[name = tensor("op_1762_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_1763 = const()[name = tensor("op_1763"), val = tensor([1, -1, 512])]; tensor var_1762_cast_fp16 = transpose(perm = var_1762_perm_0, x = x2_14_cast_fp16)[name = tensor("transpose_196")]; tensor input1_42_cast_fp16 = reshape(shape = var_1763, x = var_1762_cast_fp16)[name = tensor("input1_42_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(42170048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42432256))), name = tensor("encoder_layers_6_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_42_cast_fp16)[name = tensor("linear_61_cast_fp16")]; tensor input0_85_cast_fp16 = add(x = input_85_cast_fp16, y = linear_61_cast_fp16)[name = tensor("input0_85_cast_fp16")]; tensor x_135_axes_0 = const()[name = tensor("x_135_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(42432832)))]; 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(42433920)))]; tensor x_135_cast_fp16 = layer_norm(axes = x_135_axes_0, beta = encoder_layers_6_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_6_norm_conv_weight_to_fp16, x = input0_85_cast_fp16)[name = tensor("x_135_cast_fp16")]; tensor input_89_perm_0 = const()[name = tensor("input_89_perm_0"), val = tensor([0, 2, 1])]; tensor input0_87_pad_type_0 = const()[name = tensor("input0_87_pad_type_0"), val = tensor("valid")]; tensor input0_87_strides_0 = const()[name = tensor("input0_87_strides_0"), val = tensor([1])]; tensor input0_87_pad_0 = const()[name = tensor("input0_87_pad_0"), val = tensor([0, 0])]; tensor input0_87_dilations_0 = const()[name = tensor("input0_87_dilations_0"), val = tensor([1])]; tensor input0_87_groups_0 = const()[name = tensor("input0_87_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(42435008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42959360))), name = tensor("encoder_layers_6_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_89_cast_fp16 = transpose(perm = input_89_perm_0, x = x_135_cast_fp16)[name = tensor("transpose_195")]; tensor input0_87_cast_fp16 = conv(dilations = input0_87_dilations_0, groups = input0_87_groups_0, pad = input0_87_pad_0, pad_type = input0_87_pad_type_0, strides = input0_87_strides_0, weight = encoder_layers_6_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_89_cast_fp16)[name = tensor("input0_87_cast_fp16")]; tensor x_137_split_num_splits_0 = const()[name = tensor("x_137_split_num_splits_0"), val = tensor(2)]; tensor x_137_split_axis_0 = const()[name = tensor("x_137_split_axis_0"), val = tensor(1)]; tensor x_137_split_cast_fp16_0, tensor x_137_split_cast_fp16_1 = split(axis = x_137_split_axis_0, num_splits = x_137_split_num_splits_0, x = input0_87_cast_fp16)[name = tensor("x_137_split_cast_fp16")]; tensor x_137_split_1_sigmoid_cast_fp16 = sigmoid(x = x_137_split_cast_fp16_1)[name = tensor("x_137_split_1_sigmoid_cast_fp16")]; tensor x_137_cast_fp16 = mul(x = x_137_split_cast_fp16_0, y = x_137_split_1_sigmoid_cast_fp16)[name = tensor("x_137_cast_fp16")]; tensor input0_89_cast_fp16 = select(a = var_26_to_fp16, b = x_137_cast_fp16, cond = var_546)[name = tensor("input0_89_cast_fp16")]; tensor new_x0_14_interleave_0 = const()[name = tensor("new_x0_14_interleave_0"), val = tensor(false)]; tensor new_x0_14_cast_fp16 = concat(axis = var_47, interleave = new_x0_14_interleave_0, values = (cache12_1_cast_fp16, input0_89_cast_fp16))[name = tensor("new_x0_14_cast_fp16")]; tensor next_cache_14_begin_0 = const()[name = tensor("next_cache_14_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_14_end_0 = const()[name = tensor("next_cache_14_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_14_end_mask_0 = const()[name = tensor("next_cache_14_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_14_cast_fp16 = slice_by_index(begin = next_cache_14_begin_0, end = next_cache_14_end_0, end_mask = next_cache_14_end_mask_0, x = new_x0_14_cast_fp16)[name = tensor("next_cache_14_cast_fp16")]; tensor var_1804_begin_0 = const()[name = tensor("op_1804_begin_0"), val = tensor([0, 0, 4])]; tensor var_1804_end_0 = const()[name = tensor("op_1804_end_0"), val = tensor([1, 512, 12])]; tensor var_1804_end_mask_0 = const()[name = tensor("op_1804_end_mask_0"), val = tensor([true, true, true])]; tensor var_1804_cast_fp16 = slice_by_index(begin = var_1804_begin_0, end = var_1804_end_0, end_mask = var_1804_end_mask_0, x = next_cache_14_cast_fp16)[name = tensor("op_1804_cast_fp16")]; tensor x_139_pad_type_0 = const()[name = tensor("x_139_pad_type_0"), val = tensor("valid")]; tensor x_139_groups_0 = const()[name = tensor("x_139_groups_0"), val = tensor(512)]; tensor x_139_strides_0 = const()[name = tensor("x_139_strides_0"), val = tensor([1])]; tensor x_139_pad_0 = const()[name = tensor("x_139_pad_0"), val = tensor([0, 0])]; tensor x_139_dilations_0 = const()[name = tensor("x_139_dilations_0"), val = tensor([1])]; tensor encoder_layers_6_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42959936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42964608))), name = tensor("encoder_layers_6_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_139_cast_fp16 = conv(dilations = x_139_dilations_0, groups = x_139_groups_0, pad = x_139_pad_0, pad_type = x_139_pad_type_0, strides = x_139_strides_0, weight = encoder_layers_6_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_14_cast_fp16)[name = tensor("x_139_cast_fp16")]; tensor input1_44_perm_0 = const()[name = tensor("input1_44_perm_0"), val = tensor([0, 2, 1])]; tensor x_141_axes_0 = const()[name = tensor("x_141_axes_0"), val = tensor([-1])]; tensor encoder_layers_6_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_6_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42965184)))]; tensor encoder_layers_6_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_6_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(42966272)))]; tensor input1_44_cast_fp16 = transpose(perm = input1_44_perm_0, x = x_139_cast_fp16)[name = tensor("transpose_194")]; tensor x_141_cast_fp16 = layer_norm(axes = x_141_axes_0, beta = encoder_layers_6_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_6_conv_batch_norm_weight_to_fp16, x = input1_44_cast_fp16)[name = tensor("x_141_cast_fp16")]; tensor input2_28_perm_0 = const()[name = tensor("input2_28_perm_0"), val = tensor([0, 2, 1])]; tensor input2_28_cast_fp16 = transpose(perm = input2_28_perm_0, x = x_141_cast_fp16)[name = tensor("transpose_193")]; tensor var_1819_cast_fp16 = silu(x = input2_28_cast_fp16)[name = tensor("op_1819_cast_fp16")]; tensor x_143_pad_type_0 = const()[name = tensor("x_143_pad_type_0"), val = tensor("valid")]; tensor x_143_strides_0 = const()[name = tensor("x_143_strides_0"), val = tensor([1])]; tensor x_143_pad_0 = const()[name = tensor("x_143_pad_0"), val = tensor([0, 0])]; tensor x_143_dilations_0 = const()[name = tensor("x_143_dilations_0"), val = tensor([1])]; tensor x_143_groups_0 = const()[name = tensor("x_143_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(42967360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43229568))), name = tensor("encoder_layers_6_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_143_cast_fp16 = conv(dilations = x_143_dilations_0, groups = x_143_groups_0, pad = x_143_pad_0, pad_type = x_143_pad_type_0, strides = x_143_strides_0, weight = encoder_layers_6_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_1819_cast_fp16)[name = tensor("x_143_cast_fp16")]; tensor input3_16_perm_0 = const()[name = tensor("input3_16_perm_0"), val = tensor([0, 2, 1])]; tensor input3_16_cast_fp16 = transpose(perm = input3_16_perm_0, x = x_143_cast_fp16)[name = tensor("transpose_192")]; tensor input1_46_cast_fp16 = add(x = input0_85_cast_fp16, y = input3_16_cast_fp16)[name = tensor("input1_46_cast_fp16")]; tensor input0_91_axes_0 = const()[name = tensor("input0_91_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(43230144)))]; 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(43231232)))]; tensor input0_91_cast_fp16 = layer_norm(axes = input0_91_axes_0, beta = encoder_layers_6_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_6_norm_feed_forward2_weight_to_fp16, x = input1_46_cast_fp16)[name = tensor("input0_91_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(43232320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44280960))), name = tensor("encoder_layers_6_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_91_cast_fp16)[name = tensor("linear_62_cast_fp16")]; tensor var_1840_cast_fp16 = silu(x = linear_62_cast_fp16)[name = tensor("op_1840_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(44281536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45330176))), name = tensor("encoder_layers_6_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1840_cast_fp16)[name = tensor("linear_63_cast_fp16")]; tensor var_1845_to_fp16 = const()[name = tensor("op_1845_to_fp16"), val = tensor(0x1p-1)]; tensor var_1846_cast_fp16 = mul(x = linear_63_cast_fp16, y = var_1845_to_fp16)[name = tensor("op_1846_cast_fp16")]; tensor input2_30_cast_fp16 = add(x = input1_46_cast_fp16, y = var_1846_cast_fp16)[name = tensor("input2_30_cast_fp16")]; tensor input0_93_axes_0 = const()[name = tensor("input0_93_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(45330752)))]; 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(45331840)))]; tensor input0_93_cast_fp16 = layer_norm(axes = input0_93_axes_0, beta = encoder_layers_6_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_6_norm_out_weight_to_fp16, x = input2_30_cast_fp16)[name = tensor("input0_93_cast_fp16")]; tensor cache13_1_begin_0 = const()[name = tensor("cache13_1_begin_0"), val = tensor([7, 0, 0, 0])]; tensor cache13_1_end_0 = const()[name = tensor("cache13_1_end_0"), val = tensor([8, 1, 70, 512])]; tensor cache13_1_end_mask_0 = const()[name = tensor("cache13_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache13_1_squeeze_mask_0 = const()[name = tensor("cache13_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache13_1_cast_fp16 = slice_by_index(begin = cache13_1_begin_0, end = cache13_1_end_0, end_mask = cache13_1_end_mask_0, squeeze_mask = cache13_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache13_1_cast_fp16")]; tensor cache14_1_begin_0 = const()[name = tensor("cache14_1_begin_0"), val = tensor([7, 0, 0, 0])]; tensor cache14_1_end_0 = const()[name = tensor("cache14_1_end_0"), val = tensor([8, 1, 512, 8])]; tensor cache14_1_end_mask_0 = const()[name = tensor("cache14_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache14_1_squeeze_mask_0 = const()[name = tensor("cache14_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache14_1_cast_fp16 = slice_by_index(begin = cache14_1_begin_0, end = cache14_1_end_0, end_mask = cache14_1_end_mask_0, squeeze_mask = cache14_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache14_1_cast_fp16")]; tensor input_93_axes_0 = const()[name = tensor("input_93_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(45332928)))]; 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(45334016)))]; tensor input_93_cast_fp16 = layer_norm(axes = input_93_axes_0, beta = encoder_layers_7_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_7_norm_feed_forward1_weight_to_fp16, x = input0_93_cast_fp16)[name = tensor("input_93_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(45335104))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46383744))), name = tensor("encoder_layers_7_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_93_cast_fp16)[name = tensor("linear_64_cast_fp16")]; tensor var_1875_cast_fp16 = silu(x = linear_64_cast_fp16)[name = tensor("op_1875_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(46384320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47432960))), name = tensor("encoder_layers_7_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_1875_cast_fp16)[name = tensor("linear_65_cast_fp16")]; tensor var_1880_to_fp16 = const()[name = tensor("op_1880_to_fp16"), val = tensor(0x1p-1)]; tensor var_1881_cast_fp16 = mul(x = linear_65_cast_fp16, y = var_1880_to_fp16)[name = tensor("op_1881_cast_fp16")]; tensor input_97_cast_fp16 = add(x = input0_93_cast_fp16, y = var_1881_cast_fp16)[name = tensor("input_97_cast_fp16")]; tensor key_16_axes_0 = const()[name = tensor("key_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(47433536)))]; 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(47434624)))]; tensor key_16_cast_fp16 = layer_norm(axes = key_16_axes_0, beta = encoder_layers_7_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_7_norm_self_att_weight_to_fp16, x = input_97_cast_fp16)[name = tensor("key_16_cast_fp16")]; tensor input_99_interleave_0 = const()[name = tensor("input_99_interleave_0"), val = tensor(false)]; tensor input_99_cast_fp16 = concat(axis = var_55, interleave = input_99_interleave_0, values = (cache13_1_cast_fp16, key_16_cast_fp16))[name = tensor("input_99_cast_fp16")]; tensor var_1903_begin_0 = const()[name = tensor("op_1903_begin_0"), val = tensor([0, 4, 0])]; tensor var_1903_end_0 = const()[name = tensor("op_1903_end_0"), val = tensor([1, 70, 512])]; tensor var_1903_end_mask_0 = const()[name = tensor("op_1903_end_mask_0"), val = tensor([true, true, true])]; tensor var_1903_cast_fp16 = slice_by_index(begin = var_1903_begin_0, end = var_1903_end_0, end_mask = var_1903_end_mask_0, x = cache13_1_cast_fp16)[name = tensor("op_1903_cast_fp16")]; tensor var_1906_begin_0 = const()[name = tensor("op_1906_begin_0"), val = tensor([0, 0, 0])]; tensor var_1906_end_0 = const()[name = tensor("op_1906_end_0"), val = tensor([1, 4, 512])]; tensor var_1906_end_mask_0 = const()[name = tensor("op_1906_end_mask_0"), val = tensor([true, false, true])]; tensor var_1906_cast_fp16 = slice_by_index(begin = var_1906_begin_0, end = var_1906_end_0, end_mask = var_1906_end_mask_0, x = key_16_cast_fp16)[name = tensor("op_1906_cast_fp16")]; tensor var_1909_interleave_0 = const()[name = tensor("op_1909_interleave_0"), val = tensor(false)]; tensor var_1909_cast_fp16 = concat(axis = var_55, interleave = var_1909_interleave_0, values = (var_1903_cast_fp16, var_1906_cast_fp16))[name = tensor("op_1909_cast_fp16")]; 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(47435712))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47697920))), name = tensor("encoder_layers_7_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_16_cast_fp16)[name = tensor("linear_66_cast_fp16")]; tensor var_1913 = const()[name = tensor("op_1913"), val = tensor([1, -1, 8, 64])]; tensor q_16_cast_fp16 = reshape(shape = var_1913, 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(47698496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(47960704))), name = tensor("encoder_layers_7_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_99_cast_fp16)[name = tensor("linear_67_cast_fp16")]; tensor var_1917 = const()[name = tensor("op_1917"), val = tensor([1, -1, 8, 64])]; tensor k_16_cast_fp16 = reshape(shape = var_1917, 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(47961280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48223488))), name = tensor("encoder_layers_7_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_99_cast_fp16)[name = tensor("linear_68_cast_fp16")]; tensor var_1921 = const()[name = tensor("op_1921"), val = tensor([1, -1, 8, 64])]; tensor v_16_cast_fp16 = reshape(shape = var_1921, x = linear_68_cast_fp16)[name = tensor("v_16_cast_fp16")]; tensor value_18_perm_0 = const()[name = tensor("value_18_perm_0"), val = tensor([0, 2, -3, -1])]; 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(48224064)))]; tensor var_1933_cast_fp16 = add(x = q_16_cast_fp16, y = encoder_layers_7_self_attn_pos_bias_u_to_fp16)[name = tensor("op_1933_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(48225152)))]; tensor var_1935_cast_fp16 = add(x = q_16_cast_fp16, y = encoder_layers_7_self_attn_pos_bias_v_to_fp16)[name = tensor("op_1935_cast_fp16")]; tensor q_with_bias_v_16_perm_0 = const()[name = tensor("q_with_bias_v_16_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_151_transpose_x_0 = const()[name = tensor("x_151_transpose_x_0"), val = tensor(false)]; tensor x_151_transpose_y_0 = const()[name = tensor("x_151_transpose_y_0"), val = tensor(false)]; tensor op_1937_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48226240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48305664))), name = tensor("op_1937_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_16_cast_fp16 = transpose(perm = q_with_bias_v_16_perm_0, x = var_1935_cast_fp16)[name = tensor("transpose_191")]; tensor x_151_cast_fp16 = matmul(transpose_x = x_151_transpose_x_0, transpose_y = x_151_transpose_y_0, x = q_with_bias_v_16_cast_fp16, y = op_1937_to_fp16_palettized)[name = tensor("x_151_cast_fp16")]; 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_170_to_fp16 = const()[name = tensor("const_170_to_fp16"), val = tensor(0x0p+0)]; tensor x0_18_cast_fp16 = pad(constant_val = const_170_to_fp16, mode = x0_18_mode_0, pad = x0_18_pad_0, x = x_151_cast_fp16)[name = tensor("x0_18_cast_fp16")]; tensor var_1945 = const()[name = tensor("op_1945"), val = tensor([1, 8, -1, 8])]; tensor x1_16_cast_fp16 = reshape(shape = var_1945, x = x0_18_cast_fp16)[name = tensor("x1_16_cast_fp16")]; tensor var_1949_begin_0 = const()[name = tensor("op_1949_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_1949_end_0 = const()[name = tensor("op_1949_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_1949_end_mask_0 = const()[name = tensor("op_1949_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_1949_cast_fp16 = slice_by_index(begin = var_1949_begin_0, end = var_1949_end_0, end_mask = var_1949_end_mask_0, x = x1_16_cast_fp16)[name = tensor("op_1949_cast_fp16")]; tensor var_1950 = const()[name = tensor("op_1950"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_16_cast_fp16 = reshape(shape = var_1950, x = var_1949_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_82_perm_0 = const()[name = tensor("transpose_82_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_83_perm_0 = const()[name = tensor("transpose_83_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_83 = transpose(perm = transpose_83_perm_0, x = k_16_cast_fp16)[name = tensor("transpose_189")]; tensor transpose_82 = transpose(perm = transpose_82_perm_0, x = var_1933_cast_fp16)[name = tensor("transpose_190")]; 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_82, y = transpose_83)[name = tensor("matrix_ac_16_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_16_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_16_end_0, end_mask = matrix_bd0_16_end_mask_0, x = matrix_bd_16_cast_fp16)[name = tensor("matrix_bd0_16_cast_fp16")]; tensor var_1959_cast_fp16 = add(x = matrix_ac_16_cast_fp16, y = matrix_bd0_16_cast_fp16)[name = tensor("op_1959_cast_fp16")]; tensor _inversed_scores_16_y_0_to_fp16 = const()[name = tensor("_inversed_scores_16_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_16_cast_fp16 = mul(x = var_1959_cast_fp16, y = _inversed_scores_16_y_0_to_fp16)[name = tensor("_inversed_scores_16_cast_fp16")]; tensor scores0_16_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_16_cast_fp16, cond = mask0_4)[name = tensor("scores0_16_cast_fp16")]; tensor var_1965_cast_fp16 = softmax(axis = var_47, x = scores0_16_cast_fp16)[name = tensor("op_1965_cast_fp16")]; tensor input0_95_cast_fp16 = select(a = var_26_to_fp16, b = var_1965_cast_fp16, cond = mask0_4)[name = tensor("input0_95_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 value_18_cast_fp16 = transpose(perm = value_18_perm_0, x = v_16_cast_fp16)[name = tensor("transpose_188")]; tensor x2_16_cast_fp16 = matmul(transpose_x = x2_16_transpose_x_0, transpose_y = x2_16_transpose_y_0, x = input0_95_cast_fp16, y = value_18_cast_fp16)[name = tensor("x2_16_cast_fp16")]; tensor var_1969_perm_0 = const()[name = tensor("op_1969_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_1970 = const()[name = tensor("op_1970"), val = tensor([1, -1, 512])]; tensor var_1969_cast_fp16 = transpose(perm = var_1969_perm_0, x = x2_16_cast_fp16)[name = tensor("transpose_187")]; tensor input1_48_cast_fp16 = reshape(shape = var_1970, x = var_1969_cast_fp16)[name = tensor("input1_48_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(48306240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48568448))), name = tensor("encoder_layers_7_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_48_cast_fp16)[name = tensor("linear_70_cast_fp16")]; tensor input0_97_cast_fp16 = add(x = input_97_cast_fp16, y = linear_70_cast_fp16)[name = tensor("input0_97_cast_fp16")]; tensor x_155_axes_0 = const()[name = tensor("x_155_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(48569024)))]; 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(48570112)))]; tensor x_155_cast_fp16 = layer_norm(axes = x_155_axes_0, beta = encoder_layers_7_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_7_norm_conv_weight_to_fp16, x = input0_97_cast_fp16)[name = tensor("x_155_cast_fp16")]; tensor input_101_perm_0 = const()[name = tensor("input_101_perm_0"), val = tensor([0, 2, 1])]; tensor input0_99_pad_type_0 = const()[name = tensor("input0_99_pad_type_0"), val = tensor("valid")]; tensor input0_99_strides_0 = const()[name = tensor("input0_99_strides_0"), val = tensor([1])]; tensor input0_99_pad_0 = const()[name = tensor("input0_99_pad_0"), val = tensor([0, 0])]; tensor input0_99_dilations_0 = const()[name = tensor("input0_99_dilations_0"), val = tensor([1])]; tensor input0_99_groups_0 = const()[name = tensor("input0_99_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(48571200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49095552))), name = tensor("encoder_layers_7_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_101_cast_fp16 = transpose(perm = input_101_perm_0, x = x_155_cast_fp16)[name = tensor("transpose_186")]; tensor input0_99_cast_fp16 = conv(dilations = input0_99_dilations_0, groups = input0_99_groups_0, pad = input0_99_pad_0, pad_type = input0_99_pad_type_0, strides = input0_99_strides_0, weight = encoder_layers_7_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_101_cast_fp16)[name = tensor("input0_99_cast_fp16")]; tensor x_157_split_num_splits_0 = const()[name = tensor("x_157_split_num_splits_0"), val = tensor(2)]; tensor x_157_split_axis_0 = const()[name = tensor("x_157_split_axis_0"), val = tensor(1)]; tensor x_157_split_cast_fp16_0, tensor x_157_split_cast_fp16_1 = split(axis = x_157_split_axis_0, num_splits = x_157_split_num_splits_0, x = input0_99_cast_fp16)[name = tensor("x_157_split_cast_fp16")]; tensor x_157_split_1_sigmoid_cast_fp16 = sigmoid(x = x_157_split_cast_fp16_1)[name = tensor("x_157_split_1_sigmoid_cast_fp16")]; tensor x_157_cast_fp16 = mul(x = x_157_split_cast_fp16_0, y = x_157_split_1_sigmoid_cast_fp16)[name = tensor("x_157_cast_fp16")]; tensor input0_101_cast_fp16 = select(a = var_26_to_fp16, b = x_157_cast_fp16, cond = var_546)[name = tensor("input0_101_cast_fp16")]; tensor new_x0_16_interleave_0 = const()[name = tensor("new_x0_16_interleave_0"), val = tensor(false)]; tensor new_x0_16_cast_fp16 = concat(axis = var_47, interleave = new_x0_16_interleave_0, values = (cache14_1_cast_fp16, input0_101_cast_fp16))[name = tensor("new_x0_16_cast_fp16")]; tensor next_cache_16_begin_0 = const()[name = tensor("next_cache_16_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_16_end_0 = const()[name = tensor("next_cache_16_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_16_end_mask_0 = const()[name = tensor("next_cache_16_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_16_cast_fp16 = slice_by_index(begin = next_cache_16_begin_0, end = next_cache_16_end_0, end_mask = next_cache_16_end_mask_0, x = new_x0_16_cast_fp16)[name = tensor("next_cache_16_cast_fp16")]; tensor var_2011_begin_0 = const()[name = tensor("op_2011_begin_0"), val = tensor([0, 0, 4])]; tensor var_2011_end_0 = const()[name = tensor("op_2011_end_0"), val = tensor([1, 512, 12])]; tensor var_2011_end_mask_0 = const()[name = tensor("op_2011_end_mask_0"), val = tensor([true, true, true])]; tensor var_2011_cast_fp16 = slice_by_index(begin = var_2011_begin_0, end = var_2011_end_0, end_mask = var_2011_end_mask_0, x = next_cache_16_cast_fp16)[name = tensor("op_2011_cast_fp16")]; tensor x_159_pad_type_0 = const()[name = tensor("x_159_pad_type_0"), val = tensor("valid")]; tensor x_159_groups_0 = const()[name = tensor("x_159_groups_0"), val = tensor(512)]; tensor x_159_strides_0 = const()[name = tensor("x_159_strides_0"), val = tensor([1])]; tensor x_159_pad_0 = const()[name = tensor("x_159_pad_0"), val = tensor([0, 0])]; tensor x_159_dilations_0 = const()[name = tensor("x_159_dilations_0"), val = tensor([1])]; tensor encoder_layers_7_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49096128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49100800))), name = tensor("encoder_layers_7_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_159_cast_fp16 = conv(dilations = x_159_dilations_0, groups = x_159_groups_0, pad = x_159_pad_0, pad_type = x_159_pad_type_0, strides = x_159_strides_0, weight = encoder_layers_7_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_16_cast_fp16)[name = tensor("x_159_cast_fp16")]; tensor input1_50_perm_0 = const()[name = tensor("input1_50_perm_0"), val = tensor([0, 2, 1])]; tensor x_161_axes_0 = const()[name = tensor("x_161_axes_0"), val = tensor([-1])]; tensor encoder_layers_7_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_7_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49101376)))]; tensor encoder_layers_7_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_7_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49102464)))]; tensor input1_50_cast_fp16 = transpose(perm = input1_50_perm_0, x = x_159_cast_fp16)[name = tensor("transpose_185")]; tensor x_161_cast_fp16 = layer_norm(axes = x_161_axes_0, beta = encoder_layers_7_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_7_conv_batch_norm_weight_to_fp16, x = input1_50_cast_fp16)[name = tensor("x_161_cast_fp16")]; tensor input2_32_perm_0 = const()[name = tensor("input2_32_perm_0"), val = tensor([0, 2, 1])]; tensor input2_32_cast_fp16 = transpose(perm = input2_32_perm_0, x = x_161_cast_fp16)[name = tensor("transpose_184")]; tensor var_2026_cast_fp16 = silu(x = input2_32_cast_fp16)[name = tensor("op_2026_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_7_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49103552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49365760))), name = tensor("encoder_layers_7_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 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_7_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2026_cast_fp16)[name = tensor("x_163_cast_fp16")]; tensor input3_18_perm_0 = const()[name = tensor("input3_18_perm_0"), val = tensor([0, 2, 1])]; tensor input3_18_cast_fp16 = transpose(perm = input3_18_perm_0, x = x_163_cast_fp16)[name = tensor("transpose_183")]; tensor input1_52_cast_fp16 = add(x = input0_97_cast_fp16, y = input3_18_cast_fp16)[name = tensor("input1_52_cast_fp16")]; tensor input0_103_axes_0 = const()[name = tensor("input0_103_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(49366336)))]; 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(49367424)))]; tensor input0_103_cast_fp16 = layer_norm(axes = input0_103_axes_0, beta = encoder_layers_7_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_7_norm_feed_forward2_weight_to_fp16, x = input1_52_cast_fp16)[name = tensor("input0_103_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(49368512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50417152))), name = tensor("encoder_layers_7_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_103_cast_fp16)[name = tensor("linear_71_cast_fp16")]; tensor var_2047_cast_fp16 = silu(x = linear_71_cast_fp16)[name = tensor("op_2047_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(50417728))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51466368))), name = tensor("encoder_layers_7_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2047_cast_fp16)[name = tensor("linear_72_cast_fp16")]; tensor var_2052_to_fp16 = const()[name = tensor("op_2052_to_fp16"), val = tensor(0x1p-1)]; tensor var_2053_cast_fp16 = mul(x = linear_72_cast_fp16, y = var_2052_to_fp16)[name = tensor("op_2053_cast_fp16")]; tensor input2_34_cast_fp16 = add(x = input1_52_cast_fp16, y = var_2053_cast_fp16)[name = tensor("input2_34_cast_fp16")]; tensor input0_105_axes_0 = const()[name = tensor("input0_105_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(51466944)))]; 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(51468032)))]; tensor input0_105_cast_fp16 = layer_norm(axes = input0_105_axes_0, beta = encoder_layers_7_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_7_norm_out_weight_to_fp16, x = input2_34_cast_fp16)[name = tensor("input0_105_cast_fp16")]; tensor cache15_1_begin_0 = const()[name = tensor("cache15_1_begin_0"), val = tensor([8, 0, 0, 0])]; tensor cache15_1_end_0 = const()[name = tensor("cache15_1_end_0"), val = tensor([9, 1, 70, 512])]; tensor cache15_1_end_mask_0 = const()[name = tensor("cache15_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache15_1_squeeze_mask_0 = const()[name = tensor("cache15_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache15_1_cast_fp16 = slice_by_index(begin = cache15_1_begin_0, end = cache15_1_end_0, end_mask = cache15_1_end_mask_0, squeeze_mask = cache15_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache15_1_cast_fp16")]; tensor cache16_1_begin_0 = const()[name = tensor("cache16_1_begin_0"), val = tensor([8, 0, 0, 0])]; tensor cache16_1_end_0 = const()[name = tensor("cache16_1_end_0"), val = tensor([9, 1, 512, 8])]; tensor cache16_1_end_mask_0 = const()[name = tensor("cache16_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache16_1_squeeze_mask_0 = const()[name = tensor("cache16_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache16_1_cast_fp16 = slice_by_index(begin = cache16_1_begin_0, end = cache16_1_end_0, end_mask = cache16_1_end_mask_0, squeeze_mask = cache16_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache16_1_cast_fp16")]; tensor input_105_axes_0 = const()[name = tensor("input_105_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(51469120)))]; 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(51470208)))]; tensor input_105_cast_fp16 = layer_norm(axes = input_105_axes_0, beta = encoder_layers_8_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_8_norm_feed_forward1_weight_to_fp16, x = input0_105_cast_fp16)[name = tensor("input_105_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(51471296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52519936))), name = tensor("encoder_layers_8_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_105_cast_fp16)[name = tensor("linear_73_cast_fp16")]; tensor var_2082_cast_fp16 = silu(x = linear_73_cast_fp16)[name = tensor("op_2082_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(52520512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53569152))), name = tensor("encoder_layers_8_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2082_cast_fp16)[name = tensor("linear_74_cast_fp16")]; tensor var_2087_to_fp16 = const()[name = tensor("op_2087_to_fp16"), val = tensor(0x1p-1)]; tensor var_2088_cast_fp16 = mul(x = linear_74_cast_fp16, y = var_2087_to_fp16)[name = tensor("op_2088_cast_fp16")]; tensor input_109_cast_fp16 = add(x = input0_105_cast_fp16, y = var_2088_cast_fp16)[name = tensor("input_109_cast_fp16")]; tensor key_18_axes_0 = const()[name = tensor("key_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(53569728)))]; 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(53570816)))]; tensor key_18_cast_fp16 = layer_norm(axes = key_18_axes_0, beta = encoder_layers_8_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_8_norm_self_att_weight_to_fp16, x = input_109_cast_fp16)[name = tensor("key_18_cast_fp16")]; tensor input_111_interleave_0 = const()[name = tensor("input_111_interleave_0"), val = tensor(false)]; tensor input_111_cast_fp16 = concat(axis = var_55, interleave = input_111_interleave_0, values = (cache15_1_cast_fp16, key_18_cast_fp16))[name = tensor("input_111_cast_fp16")]; tensor var_2110_begin_0 = const()[name = tensor("op_2110_begin_0"), val = tensor([0, 4, 0])]; tensor var_2110_end_0 = const()[name = tensor("op_2110_end_0"), val = tensor([1, 70, 512])]; tensor var_2110_end_mask_0 = const()[name = tensor("op_2110_end_mask_0"), val = tensor([true, true, true])]; tensor var_2110_cast_fp16 = slice_by_index(begin = var_2110_begin_0, end = var_2110_end_0, end_mask = var_2110_end_mask_0, x = cache15_1_cast_fp16)[name = tensor("op_2110_cast_fp16")]; tensor var_2113_begin_0 = const()[name = tensor("op_2113_begin_0"), val = tensor([0, 0, 0])]; tensor var_2113_end_0 = const()[name = tensor("op_2113_end_0"), val = tensor([1, 4, 512])]; tensor var_2113_end_mask_0 = const()[name = tensor("op_2113_end_mask_0"), val = tensor([true, false, true])]; tensor var_2113_cast_fp16 = slice_by_index(begin = var_2113_begin_0, end = var_2113_end_0, end_mask = var_2113_end_mask_0, x = key_18_cast_fp16)[name = tensor("op_2113_cast_fp16")]; tensor var_2116_interleave_0 = const()[name = tensor("op_2116_interleave_0"), val = tensor(false)]; tensor var_2116_cast_fp16 = concat(axis = var_55, interleave = var_2116_interleave_0, values = (var_2110_cast_fp16, var_2113_cast_fp16))[name = tensor("op_2116_cast_fp16")]; 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(53571904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53834112))), name = tensor("encoder_layers_8_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_18_cast_fp16)[name = tensor("linear_75_cast_fp16")]; tensor var_2120 = const()[name = tensor("op_2120"), val = tensor([1, -1, 8, 64])]; tensor q_18_cast_fp16 = reshape(shape = var_2120, 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(53834688))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54096896))), name = tensor("encoder_layers_8_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_111_cast_fp16)[name = tensor("linear_76_cast_fp16")]; tensor var_2124 = const()[name = tensor("op_2124"), val = tensor([1, -1, 8, 64])]; tensor k_18_cast_fp16 = reshape(shape = var_2124, 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(54097472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54359680))), name = tensor("encoder_layers_8_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_111_cast_fp16)[name = tensor("linear_77_cast_fp16")]; tensor var_2128 = const()[name = tensor("op_2128"), val = tensor([1, -1, 8, 64])]; tensor v_18_cast_fp16 = reshape(shape = var_2128, x = linear_77_cast_fp16)[name = tensor("v_18_cast_fp16")]; tensor value_20_perm_0 = const()[name = tensor("value_20_perm_0"), val = tensor([0, 2, -3, -1])]; 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(54360256)))]; tensor var_2140_cast_fp16 = add(x = q_18_cast_fp16, y = encoder_layers_8_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2140_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(54361344)))]; tensor var_2142_cast_fp16 = add(x = q_18_cast_fp16, y = encoder_layers_8_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2142_cast_fp16")]; tensor q_with_bias_v_18_perm_0 = const()[name = tensor("q_with_bias_v_18_perm_0"), val = tensor([0, 2, -3, -1])]; 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 op_2144_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54362432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54441856))), name = tensor("op_2144_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_18_cast_fp16 = transpose(perm = q_with_bias_v_18_perm_0, x = var_2142_cast_fp16)[name = tensor("transpose_182")]; tensor x_171_cast_fp16 = matmul(transpose_x = x_171_transpose_x_0, transpose_y = x_171_transpose_y_0, x = q_with_bias_v_18_cast_fp16, y = op_2144_to_fp16_palettized)[name = tensor("x_171_cast_fp16")]; 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_183_to_fp16 = const()[name = tensor("const_183_to_fp16"), val = tensor(0x0p+0)]; tensor x0_20_cast_fp16 = pad(constant_val = const_183_to_fp16, mode = x0_20_mode_0, pad = x0_20_pad_0, x = x_171_cast_fp16)[name = tensor("x0_20_cast_fp16")]; tensor var_2152 = const()[name = tensor("op_2152"), val = tensor([1, 8, -1, 8])]; tensor x1_18_cast_fp16 = reshape(shape = var_2152, x = x0_20_cast_fp16)[name = tensor("x1_18_cast_fp16")]; tensor var_2156_begin_0 = const()[name = tensor("op_2156_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2156_end_0 = const()[name = tensor("op_2156_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_2156_end_mask_0 = const()[name = tensor("op_2156_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2156_cast_fp16 = slice_by_index(begin = var_2156_begin_0, end = var_2156_end_0, end_mask = var_2156_end_mask_0, x = x1_18_cast_fp16)[name = tensor("op_2156_cast_fp16")]; tensor var_2157 = const()[name = tensor("op_2157"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_18_cast_fp16 = reshape(shape = var_2157, x = var_2156_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_84_perm_0 = const()[name = tensor("transpose_84_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_85_perm_0 = const()[name = tensor("transpose_85_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_85 = transpose(perm = transpose_85_perm_0, x = k_18_cast_fp16)[name = tensor("transpose_180")]; tensor transpose_84 = transpose(perm = transpose_84_perm_0, x = var_2140_cast_fp16)[name = tensor("transpose_181")]; 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_84, y = transpose_85)[name = tensor("matrix_ac_18_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_18_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_18_end_0, end_mask = matrix_bd0_18_end_mask_0, x = matrix_bd_18_cast_fp16)[name = tensor("matrix_bd0_18_cast_fp16")]; tensor var_2166_cast_fp16 = add(x = matrix_ac_18_cast_fp16, y = matrix_bd0_18_cast_fp16)[name = tensor("op_2166_cast_fp16")]; tensor _inversed_scores_18_y_0_to_fp16 = const()[name = tensor("_inversed_scores_18_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_18_cast_fp16 = mul(x = var_2166_cast_fp16, y = _inversed_scores_18_y_0_to_fp16)[name = tensor("_inversed_scores_18_cast_fp16")]; tensor scores0_18_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_18_cast_fp16, cond = mask0_4)[name = tensor("scores0_18_cast_fp16")]; tensor var_2172_cast_fp16 = softmax(axis = var_47, x = scores0_18_cast_fp16)[name = tensor("op_2172_cast_fp16")]; tensor input0_107_cast_fp16 = select(a = var_26_to_fp16, b = var_2172_cast_fp16, cond = mask0_4)[name = tensor("input0_107_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 value_20_cast_fp16 = transpose(perm = value_20_perm_0, x = v_18_cast_fp16)[name = tensor("transpose_179")]; tensor x2_18_cast_fp16 = matmul(transpose_x = x2_18_transpose_x_0, transpose_y = x2_18_transpose_y_0, x = input0_107_cast_fp16, y = value_20_cast_fp16)[name = tensor("x2_18_cast_fp16")]; tensor var_2176_perm_0 = const()[name = tensor("op_2176_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_2177 = const()[name = tensor("op_2177"), val = tensor([1, -1, 512])]; tensor var_2176_cast_fp16 = transpose(perm = var_2176_perm_0, x = x2_18_cast_fp16)[name = tensor("transpose_178")]; tensor input1_54_cast_fp16 = reshape(shape = var_2177, x = var_2176_cast_fp16)[name = tensor("input1_54_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(54442432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54704640))), name = tensor("encoder_layers_8_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_54_cast_fp16)[name = tensor("linear_79_cast_fp16")]; tensor input0_109_cast_fp16 = add(x = input_109_cast_fp16, y = linear_79_cast_fp16)[name = tensor("input0_109_cast_fp16")]; tensor x_175_axes_0 = const()[name = tensor("x_175_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(54705216)))]; 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(54706304)))]; tensor x_175_cast_fp16 = layer_norm(axes = x_175_axes_0, beta = encoder_layers_8_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_8_norm_conv_weight_to_fp16, x = input0_109_cast_fp16)[name = tensor("x_175_cast_fp16")]; tensor input_113_perm_0 = const()[name = tensor("input_113_perm_0"), val = tensor([0, 2, 1])]; tensor input0_111_pad_type_0 = const()[name = tensor("input0_111_pad_type_0"), val = tensor("valid")]; tensor input0_111_strides_0 = const()[name = tensor("input0_111_strides_0"), val = tensor([1])]; tensor input0_111_pad_0 = const()[name = tensor("input0_111_pad_0"), val = tensor([0, 0])]; tensor input0_111_dilations_0 = const()[name = tensor("input0_111_dilations_0"), val = tensor([1])]; tensor input0_111_groups_0 = const()[name = tensor("input0_111_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(54707392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55231744))), name = tensor("encoder_layers_8_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_113_cast_fp16 = transpose(perm = input_113_perm_0, x = x_175_cast_fp16)[name = tensor("transpose_177")]; tensor input0_111_cast_fp16 = conv(dilations = input0_111_dilations_0, groups = input0_111_groups_0, pad = input0_111_pad_0, pad_type = input0_111_pad_type_0, strides = input0_111_strides_0, weight = encoder_layers_8_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_113_cast_fp16)[name = tensor("input0_111_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_111_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_113_cast_fp16 = select(a = var_26_to_fp16, b = x_177_cast_fp16, cond = var_546)[name = tensor("input0_113_cast_fp16")]; tensor new_x0_18_interleave_0 = const()[name = tensor("new_x0_18_interleave_0"), val = tensor(false)]; tensor new_x0_18_cast_fp16 = concat(axis = var_47, interleave = new_x0_18_interleave_0, values = (cache16_1_cast_fp16, input0_113_cast_fp16))[name = tensor("new_x0_18_cast_fp16")]; tensor next_cache_18_begin_0 = const()[name = tensor("next_cache_18_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_18_end_0 = const()[name = tensor("next_cache_18_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_18_end_mask_0 = const()[name = tensor("next_cache_18_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_18_cast_fp16 = slice_by_index(begin = next_cache_18_begin_0, end = next_cache_18_end_0, end_mask = next_cache_18_end_mask_0, x = new_x0_18_cast_fp16)[name = tensor("next_cache_18_cast_fp16")]; tensor var_2218_begin_0 = const()[name = tensor("op_2218_begin_0"), val = tensor([0, 0, 4])]; tensor var_2218_end_0 = const()[name = tensor("op_2218_end_0"), val = tensor([1, 512, 12])]; tensor var_2218_end_mask_0 = const()[name = tensor("op_2218_end_mask_0"), val = tensor([true, true, true])]; tensor var_2218_cast_fp16 = slice_by_index(begin = var_2218_begin_0, end = var_2218_end_0, end_mask = var_2218_end_mask_0, x = next_cache_18_cast_fp16)[name = tensor("op_2218_cast_fp16")]; tensor x_179_pad_type_0 = const()[name = tensor("x_179_pad_type_0"), val = tensor("valid")]; tensor x_179_groups_0 = const()[name = tensor("x_179_groups_0"), val = tensor(512)]; 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 encoder_layers_8_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55232320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55236992))), name = tensor("encoder_layers_8_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; 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_8_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_18_cast_fp16)[name = tensor("x_179_cast_fp16")]; tensor input1_56_perm_0 = const()[name = tensor("input1_56_perm_0"), val = tensor([0, 2, 1])]; tensor x_181_axes_0 = const()[name = tensor("x_181_axes_0"), val = tensor([-1])]; tensor encoder_layers_8_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_8_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55237568)))]; tensor encoder_layers_8_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_8_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55238656)))]; tensor input1_56_cast_fp16 = transpose(perm = input1_56_perm_0, x = x_179_cast_fp16)[name = tensor("transpose_176")]; tensor x_181_cast_fp16 = layer_norm(axes = x_181_axes_0, beta = encoder_layers_8_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_8_conv_batch_norm_weight_to_fp16, x = input1_56_cast_fp16)[name = tensor("x_181_cast_fp16")]; tensor input2_36_perm_0 = const()[name = tensor("input2_36_perm_0"), val = tensor([0, 2, 1])]; tensor input2_36_cast_fp16 = transpose(perm = input2_36_perm_0, x = x_181_cast_fp16)[name = tensor("transpose_175")]; tensor var_2233_cast_fp16 = silu(x = input2_36_cast_fp16)[name = tensor("op_2233_cast_fp16")]; tensor x_183_pad_type_0 = const()[name = tensor("x_183_pad_type_0"), val = tensor("valid")]; tensor x_183_strides_0 = const()[name = tensor("x_183_strides_0"), val = tensor([1])]; tensor x_183_pad_0 = const()[name = tensor("x_183_pad_0"), val = tensor([0, 0])]; tensor x_183_dilations_0 = const()[name = tensor("x_183_dilations_0"), val = tensor([1])]; tensor x_183_groups_0 = const()[name = tensor("x_183_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(55239744))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55501952))), name = tensor("encoder_layers_8_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_183_cast_fp16 = conv(dilations = x_183_dilations_0, groups = x_183_groups_0, pad = x_183_pad_0, pad_type = x_183_pad_type_0, strides = x_183_strides_0, weight = encoder_layers_8_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2233_cast_fp16)[name = tensor("x_183_cast_fp16")]; tensor input3_20_perm_0 = const()[name = tensor("input3_20_perm_0"), val = tensor([0, 2, 1])]; tensor input3_20_cast_fp16 = transpose(perm = input3_20_perm_0, x = x_183_cast_fp16)[name = tensor("transpose_174")]; tensor input1_58_cast_fp16 = add(x = input0_109_cast_fp16, y = input3_20_cast_fp16)[name = tensor("input1_58_cast_fp16")]; tensor input0_115_axes_0 = const()[name = tensor("input0_115_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(55502528)))]; 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(55503616)))]; tensor input0_115_cast_fp16 = layer_norm(axes = input0_115_axes_0, beta = encoder_layers_8_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_8_norm_feed_forward2_weight_to_fp16, x = input1_58_cast_fp16)[name = tensor("input0_115_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(55504704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56553344))), name = tensor("encoder_layers_8_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_115_cast_fp16)[name = tensor("linear_80_cast_fp16")]; tensor var_2254_cast_fp16 = silu(x = linear_80_cast_fp16)[name = tensor("op_2254_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(56553920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57602560))), name = tensor("encoder_layers_8_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2254_cast_fp16)[name = tensor("linear_81_cast_fp16")]; tensor var_2259_to_fp16 = const()[name = tensor("op_2259_to_fp16"), val = tensor(0x1p-1)]; tensor var_2260_cast_fp16 = mul(x = linear_81_cast_fp16, y = var_2259_to_fp16)[name = tensor("op_2260_cast_fp16")]; tensor input2_38_cast_fp16 = add(x = input1_58_cast_fp16, y = var_2260_cast_fp16)[name = tensor("input2_38_cast_fp16")]; tensor input0_117_axes_0 = const()[name = tensor("input0_117_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(57603136)))]; 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(57604224)))]; tensor input0_117_cast_fp16 = layer_norm(axes = input0_117_axes_0, beta = encoder_layers_8_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_8_norm_out_weight_to_fp16, x = input2_38_cast_fp16)[name = tensor("input0_117_cast_fp16")]; tensor cache17_1_begin_0 = const()[name = tensor("cache17_1_begin_0"), val = tensor([9, 0, 0, 0])]; tensor cache17_1_end_0 = const()[name = tensor("cache17_1_end_0"), val = tensor([10, 1, 70, 512])]; tensor cache17_1_end_mask_0 = const()[name = tensor("cache17_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache17_1_squeeze_mask_0 = const()[name = tensor("cache17_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache17_1_cast_fp16 = slice_by_index(begin = cache17_1_begin_0, end = cache17_1_end_0, end_mask = cache17_1_end_mask_0, squeeze_mask = cache17_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache17_1_cast_fp16")]; tensor cache18_1_begin_0 = const()[name = tensor("cache18_1_begin_0"), val = tensor([9, 0, 0, 0])]; tensor cache18_1_end_0 = const()[name = tensor("cache18_1_end_0"), val = tensor([10, 1, 512, 8])]; tensor cache18_1_end_mask_0 = const()[name = tensor("cache18_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache18_1_squeeze_mask_0 = const()[name = tensor("cache18_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache18_1_cast_fp16 = slice_by_index(begin = cache18_1_begin_0, end = cache18_1_end_0, end_mask = cache18_1_end_mask_0, squeeze_mask = cache18_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache18_1_cast_fp16")]; tensor input_117_axes_0 = const()[name = tensor("input_117_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(57605312)))]; 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(57606400)))]; tensor input_117_cast_fp16 = layer_norm(axes = input_117_axes_0, beta = encoder_layers_9_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_9_norm_feed_forward1_weight_to_fp16, x = input0_117_cast_fp16)[name = tensor("input_117_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(57607488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(58656128))), name = tensor("encoder_layers_9_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_117_cast_fp16)[name = tensor("linear_82_cast_fp16")]; tensor var_2289_cast_fp16 = silu(x = linear_82_cast_fp16)[name = tensor("op_2289_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(58656704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59705344))), name = tensor("encoder_layers_9_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2289_cast_fp16)[name = tensor("linear_83_cast_fp16")]; tensor var_2294_to_fp16 = const()[name = tensor("op_2294_to_fp16"), val = tensor(0x1p-1)]; tensor var_2295_cast_fp16 = mul(x = linear_83_cast_fp16, y = var_2294_to_fp16)[name = tensor("op_2295_cast_fp16")]; tensor input_121_cast_fp16 = add(x = input0_117_cast_fp16, y = var_2295_cast_fp16)[name = tensor("input_121_cast_fp16")]; tensor key_20_axes_0 = const()[name = tensor("key_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(59705920)))]; 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(59707008)))]; tensor key_20_cast_fp16 = layer_norm(axes = key_20_axes_0, beta = encoder_layers_9_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_9_norm_self_att_weight_to_fp16, x = input_121_cast_fp16)[name = tensor("key_20_cast_fp16")]; tensor input_123_interleave_0 = const()[name = tensor("input_123_interleave_0"), val = tensor(false)]; tensor input_123_cast_fp16 = concat(axis = var_55, interleave = input_123_interleave_0, values = (cache17_1_cast_fp16, key_20_cast_fp16))[name = tensor("input_123_cast_fp16")]; tensor var_2317_begin_0 = const()[name = tensor("op_2317_begin_0"), val = tensor([0, 4, 0])]; tensor var_2317_end_0 = const()[name = tensor("op_2317_end_0"), val = tensor([1, 70, 512])]; tensor var_2317_end_mask_0 = const()[name = tensor("op_2317_end_mask_0"), val = tensor([true, true, true])]; tensor var_2317_cast_fp16 = slice_by_index(begin = var_2317_begin_0, end = var_2317_end_0, end_mask = var_2317_end_mask_0, x = cache17_1_cast_fp16)[name = tensor("op_2317_cast_fp16")]; tensor var_2320_begin_0 = const()[name = tensor("op_2320_begin_0"), val = tensor([0, 0, 0])]; tensor var_2320_end_0 = const()[name = tensor("op_2320_end_0"), val = tensor([1, 4, 512])]; tensor var_2320_end_mask_0 = const()[name = tensor("op_2320_end_mask_0"), val = tensor([true, false, true])]; tensor var_2320_cast_fp16 = slice_by_index(begin = var_2320_begin_0, end = var_2320_end_0, end_mask = var_2320_end_mask_0, x = key_20_cast_fp16)[name = tensor("op_2320_cast_fp16")]; tensor var_2323_interleave_0 = const()[name = tensor("op_2323_interleave_0"), val = tensor(false)]; tensor var_2323_cast_fp16 = concat(axis = var_55, interleave = var_2323_interleave_0, values = (var_2317_cast_fp16, var_2320_cast_fp16))[name = tensor("op_2323_cast_fp16")]; 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(59708096))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59970304))), name = tensor("encoder_layers_9_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_20_cast_fp16)[name = tensor("linear_84_cast_fp16")]; tensor var_2327 = const()[name = tensor("op_2327"), val = tensor([1, -1, 8, 64])]; tensor q_20_cast_fp16 = reshape(shape = var_2327, 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(59970880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60233088))), name = tensor("encoder_layers_9_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_123_cast_fp16)[name = tensor("linear_85_cast_fp16")]; tensor var_2331 = const()[name = tensor("op_2331"), val = tensor([1, -1, 8, 64])]; tensor k_20_cast_fp16 = reshape(shape = var_2331, 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(60233664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60495872))), name = tensor("encoder_layers_9_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_123_cast_fp16)[name = tensor("linear_86_cast_fp16")]; tensor var_2335 = const()[name = tensor("op_2335"), val = tensor([1, -1, 8, 64])]; tensor v_20_cast_fp16 = reshape(shape = var_2335, x = linear_86_cast_fp16)[name = tensor("v_20_cast_fp16")]; tensor value_22_perm_0 = const()[name = tensor("value_22_perm_0"), val = tensor([0, 2, -3, -1])]; 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(60496448)))]; tensor var_2347_cast_fp16 = add(x = q_20_cast_fp16, y = encoder_layers_9_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2347_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(60497536)))]; tensor var_2349_cast_fp16 = add(x = q_20_cast_fp16, y = encoder_layers_9_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2349_cast_fp16")]; tensor q_with_bias_v_20_perm_0 = const()[name = tensor("q_with_bias_v_20_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_191_transpose_x_0 = const()[name = tensor("x_191_transpose_x_0"), val = tensor(false)]; tensor x_191_transpose_y_0 = const()[name = tensor("x_191_transpose_y_0"), val = tensor(false)]; tensor op_2351_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60498624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60578048))), name = tensor("op_2351_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_20_cast_fp16 = transpose(perm = q_with_bias_v_20_perm_0, x = var_2349_cast_fp16)[name = tensor("transpose_173")]; tensor x_191_cast_fp16 = matmul(transpose_x = x_191_transpose_x_0, transpose_y = x_191_transpose_y_0, x = q_with_bias_v_20_cast_fp16, y = op_2351_to_fp16_palettized)[name = tensor("x_191_cast_fp16")]; 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_196_to_fp16 = const()[name = tensor("const_196_to_fp16"), val = tensor(0x0p+0)]; tensor x0_22_cast_fp16 = pad(constant_val = const_196_to_fp16, mode = x0_22_mode_0, pad = x0_22_pad_0, x = x_191_cast_fp16)[name = tensor("x0_22_cast_fp16")]; tensor var_2359 = const()[name = tensor("op_2359"), val = tensor([1, 8, -1, 8])]; tensor x1_20_cast_fp16 = reshape(shape = var_2359, x = x0_22_cast_fp16)[name = tensor("x1_20_cast_fp16")]; tensor var_2363_begin_0 = const()[name = tensor("op_2363_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2363_end_0 = const()[name = tensor("op_2363_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_2363_end_mask_0 = const()[name = tensor("op_2363_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2363_cast_fp16 = slice_by_index(begin = var_2363_begin_0, end = var_2363_end_0, end_mask = var_2363_end_mask_0, x = x1_20_cast_fp16)[name = tensor("op_2363_cast_fp16")]; tensor var_2364 = const()[name = tensor("op_2364"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_20_cast_fp16 = reshape(shape = var_2364, x = var_2363_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_86_perm_0 = const()[name = tensor("transpose_86_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_87_perm_0 = const()[name = tensor("transpose_87_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_87 = transpose(perm = transpose_87_perm_0, x = k_20_cast_fp16)[name = tensor("transpose_171")]; tensor transpose_86 = transpose(perm = transpose_86_perm_0, x = var_2347_cast_fp16)[name = tensor("transpose_172")]; 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_86, y = transpose_87)[name = tensor("matrix_ac_20_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_20_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_20_end_0, end_mask = matrix_bd0_20_end_mask_0, x = matrix_bd_20_cast_fp16)[name = tensor("matrix_bd0_20_cast_fp16")]; tensor var_2373_cast_fp16 = add(x = matrix_ac_20_cast_fp16, y = matrix_bd0_20_cast_fp16)[name = tensor("op_2373_cast_fp16")]; tensor _inversed_scores_20_y_0_to_fp16 = const()[name = tensor("_inversed_scores_20_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_20_cast_fp16 = mul(x = var_2373_cast_fp16, y = _inversed_scores_20_y_0_to_fp16)[name = tensor("_inversed_scores_20_cast_fp16")]; tensor scores0_20_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_20_cast_fp16, cond = mask0_4)[name = tensor("scores0_20_cast_fp16")]; tensor var_2379_cast_fp16 = softmax(axis = var_47, x = scores0_20_cast_fp16)[name = tensor("op_2379_cast_fp16")]; tensor input0_119_cast_fp16 = select(a = var_26_to_fp16, b = var_2379_cast_fp16, cond = mask0_4)[name = tensor("input0_119_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 value_22_cast_fp16 = transpose(perm = value_22_perm_0, x = v_20_cast_fp16)[name = tensor("transpose_170")]; tensor x2_20_cast_fp16 = matmul(transpose_x = x2_20_transpose_x_0, transpose_y = x2_20_transpose_y_0, x = input0_119_cast_fp16, y = value_22_cast_fp16)[name = tensor("x2_20_cast_fp16")]; tensor var_2383_perm_0 = const()[name = tensor("op_2383_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_2384 = const()[name = tensor("op_2384"), val = tensor([1, -1, 512])]; tensor var_2383_cast_fp16 = transpose(perm = var_2383_perm_0, x = x2_20_cast_fp16)[name = tensor("transpose_169")]; tensor input1_60_cast_fp16 = reshape(shape = var_2384, x = var_2383_cast_fp16)[name = tensor("input1_60_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(60578624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60840832))), name = tensor("encoder_layers_9_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_60_cast_fp16)[name = tensor("linear_88_cast_fp16")]; tensor input0_121_cast_fp16 = add(x = input_121_cast_fp16, y = linear_88_cast_fp16)[name = tensor("input0_121_cast_fp16")]; tensor x_195_axes_0 = const()[name = tensor("x_195_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(60841408)))]; 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(60842496)))]; tensor x_195_cast_fp16 = layer_norm(axes = x_195_axes_0, beta = encoder_layers_9_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_9_norm_conv_weight_to_fp16, x = input0_121_cast_fp16)[name = tensor("x_195_cast_fp16")]; tensor input_125_perm_0 = const()[name = tensor("input_125_perm_0"), val = tensor([0, 2, 1])]; tensor input0_123_pad_type_0 = const()[name = tensor("input0_123_pad_type_0"), val = tensor("valid")]; tensor input0_123_strides_0 = const()[name = tensor("input0_123_strides_0"), val = tensor([1])]; tensor input0_123_pad_0 = const()[name = tensor("input0_123_pad_0"), val = tensor([0, 0])]; tensor input0_123_dilations_0 = const()[name = tensor("input0_123_dilations_0"), val = tensor([1])]; tensor input0_123_groups_0 = const()[name = tensor("input0_123_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(60843584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61367936))), name = tensor("encoder_layers_9_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_125_cast_fp16 = transpose(perm = input_125_perm_0, x = x_195_cast_fp16)[name = tensor("transpose_168")]; tensor input0_123_cast_fp16 = conv(dilations = input0_123_dilations_0, groups = input0_123_groups_0, pad = input0_123_pad_0, pad_type = input0_123_pad_type_0, strides = input0_123_strides_0, weight = encoder_layers_9_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_125_cast_fp16)[name = tensor("input0_123_cast_fp16")]; tensor x_197_split_num_splits_0 = const()[name = tensor("x_197_split_num_splits_0"), val = tensor(2)]; tensor x_197_split_axis_0 = const()[name = tensor("x_197_split_axis_0"), val = tensor(1)]; tensor x_197_split_cast_fp16_0, tensor x_197_split_cast_fp16_1 = split(axis = x_197_split_axis_0, num_splits = x_197_split_num_splits_0, x = input0_123_cast_fp16)[name = tensor("x_197_split_cast_fp16")]; tensor x_197_split_1_sigmoid_cast_fp16 = sigmoid(x = x_197_split_cast_fp16_1)[name = tensor("x_197_split_1_sigmoid_cast_fp16")]; tensor x_197_cast_fp16 = mul(x = x_197_split_cast_fp16_0, y = x_197_split_1_sigmoid_cast_fp16)[name = tensor("x_197_cast_fp16")]; tensor input0_125_cast_fp16 = select(a = var_26_to_fp16, b = x_197_cast_fp16, cond = var_546)[name = tensor("input0_125_cast_fp16")]; tensor new_x0_20_interleave_0 = const()[name = tensor("new_x0_20_interleave_0"), val = tensor(false)]; tensor new_x0_20_cast_fp16 = concat(axis = var_47, interleave = new_x0_20_interleave_0, values = (cache18_1_cast_fp16, input0_125_cast_fp16))[name = tensor("new_x0_20_cast_fp16")]; tensor next_cache_20_begin_0 = const()[name = tensor("next_cache_20_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_20_end_0 = const()[name = tensor("next_cache_20_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_20_end_mask_0 = const()[name = tensor("next_cache_20_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_20_cast_fp16 = slice_by_index(begin = next_cache_20_begin_0, end = next_cache_20_end_0, end_mask = next_cache_20_end_mask_0, x = new_x0_20_cast_fp16)[name = tensor("next_cache_20_cast_fp16")]; tensor var_2425_begin_0 = const()[name = tensor("op_2425_begin_0"), val = tensor([0, 0, 4])]; tensor var_2425_end_0 = const()[name = tensor("op_2425_end_0"), val = tensor([1, 512, 12])]; tensor var_2425_end_mask_0 = const()[name = tensor("op_2425_end_mask_0"), val = tensor([true, true, true])]; tensor var_2425_cast_fp16 = slice_by_index(begin = var_2425_begin_0, end = var_2425_end_0, end_mask = var_2425_end_mask_0, x = next_cache_20_cast_fp16)[name = tensor("op_2425_cast_fp16")]; tensor x_199_pad_type_0 = const()[name = tensor("x_199_pad_type_0"), val = tensor("valid")]; tensor x_199_groups_0 = const()[name = tensor("x_199_groups_0"), val = tensor(512)]; tensor x_199_strides_0 = const()[name = tensor("x_199_strides_0"), val = tensor([1])]; tensor x_199_pad_0 = const()[name = tensor("x_199_pad_0"), val = tensor([0, 0])]; tensor x_199_dilations_0 = const()[name = tensor("x_199_dilations_0"), val = tensor([1])]; tensor encoder_layers_9_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61368512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61373184))), name = tensor("encoder_layers_9_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_199_cast_fp16 = conv(dilations = x_199_dilations_0, groups = x_199_groups_0, pad = x_199_pad_0, pad_type = x_199_pad_type_0, strides = x_199_strides_0, weight = encoder_layers_9_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_20_cast_fp16)[name = tensor("x_199_cast_fp16")]; tensor input1_62_perm_0 = const()[name = tensor("input1_62_perm_0"), val = tensor([0, 2, 1])]; tensor x_201_axes_0 = const()[name = tensor("x_201_axes_0"), val = tensor([-1])]; tensor encoder_layers_9_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_9_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61373760)))]; tensor encoder_layers_9_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_9_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61374848)))]; tensor input1_62_cast_fp16 = transpose(perm = input1_62_perm_0, x = x_199_cast_fp16)[name = tensor("transpose_167")]; tensor x_201_cast_fp16 = layer_norm(axes = x_201_axes_0, beta = encoder_layers_9_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_9_conv_batch_norm_weight_to_fp16, x = input1_62_cast_fp16)[name = tensor("x_201_cast_fp16")]; tensor input2_40_perm_0 = const()[name = tensor("input2_40_perm_0"), val = tensor([0, 2, 1])]; tensor input2_40_cast_fp16 = transpose(perm = input2_40_perm_0, x = x_201_cast_fp16)[name = tensor("transpose_166")]; tensor var_2440_cast_fp16 = silu(x = input2_40_cast_fp16)[name = tensor("op_2440_cast_fp16")]; tensor x_203_pad_type_0 = const()[name = tensor("x_203_pad_type_0"), val = tensor("valid")]; tensor x_203_strides_0 = const()[name = tensor("x_203_strides_0"), val = tensor([1])]; tensor x_203_pad_0 = const()[name = tensor("x_203_pad_0"), val = tensor([0, 0])]; tensor x_203_dilations_0 = const()[name = tensor("x_203_dilations_0"), val = tensor([1])]; tensor x_203_groups_0 = const()[name = tensor("x_203_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(61375936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61638144))), name = tensor("encoder_layers_9_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_203_cast_fp16 = conv(dilations = x_203_dilations_0, groups = x_203_groups_0, pad = x_203_pad_0, pad_type = x_203_pad_type_0, strides = x_203_strides_0, weight = encoder_layers_9_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2440_cast_fp16)[name = tensor("x_203_cast_fp16")]; tensor input3_22_perm_0 = const()[name = tensor("input3_22_perm_0"), val = tensor([0, 2, 1])]; tensor input3_22_cast_fp16 = transpose(perm = input3_22_perm_0, x = x_203_cast_fp16)[name = tensor("transpose_165")]; tensor input1_64_cast_fp16 = add(x = input0_121_cast_fp16, y = input3_22_cast_fp16)[name = tensor("input1_64_cast_fp16")]; tensor input0_127_axes_0 = const()[name = tensor("input0_127_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(61638720)))]; 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(61639808)))]; tensor input0_127_cast_fp16 = layer_norm(axes = input0_127_axes_0, beta = encoder_layers_9_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_9_norm_feed_forward2_weight_to_fp16, x = input1_64_cast_fp16)[name = tensor("input0_127_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(61640896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62689536))), name = tensor("encoder_layers_9_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_127_cast_fp16)[name = tensor("linear_89_cast_fp16")]; tensor var_2461_cast_fp16 = silu(x = linear_89_cast_fp16)[name = tensor("op_2461_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(62690112))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(63738752))), name = tensor("encoder_layers_9_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2461_cast_fp16)[name = tensor("linear_90_cast_fp16")]; tensor var_2466_to_fp16 = const()[name = tensor("op_2466_to_fp16"), val = tensor(0x1p-1)]; tensor var_2467_cast_fp16 = mul(x = linear_90_cast_fp16, y = var_2466_to_fp16)[name = tensor("op_2467_cast_fp16")]; tensor input2_42_cast_fp16 = add(x = input1_64_cast_fp16, y = var_2467_cast_fp16)[name = tensor("input2_42_cast_fp16")]; tensor input0_129_axes_0 = const()[name = tensor("input0_129_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(63739328)))]; 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(63740416)))]; tensor input0_129_cast_fp16 = layer_norm(axes = input0_129_axes_0, beta = encoder_layers_9_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_9_norm_out_weight_to_fp16, x = input2_42_cast_fp16)[name = tensor("input0_129_cast_fp16")]; tensor cache19_1_begin_0 = const()[name = tensor("cache19_1_begin_0"), val = tensor([10, 0, 0, 0])]; tensor cache19_1_end_0 = const()[name = tensor("cache19_1_end_0"), val = tensor([11, 1, 70, 512])]; tensor cache19_1_end_mask_0 = const()[name = tensor("cache19_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache19_1_squeeze_mask_0 = const()[name = tensor("cache19_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache19_1_cast_fp16 = slice_by_index(begin = cache19_1_begin_0, end = cache19_1_end_0, end_mask = cache19_1_end_mask_0, squeeze_mask = cache19_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache19_1_cast_fp16")]; tensor cache20_1_begin_0 = const()[name = tensor("cache20_1_begin_0"), val = tensor([10, 0, 0, 0])]; tensor cache20_1_end_0 = const()[name = tensor("cache20_1_end_0"), val = tensor([11, 1, 512, 8])]; tensor cache20_1_end_mask_0 = const()[name = tensor("cache20_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache20_1_squeeze_mask_0 = const()[name = tensor("cache20_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache20_1_cast_fp16 = slice_by_index(begin = cache20_1_begin_0, end = cache20_1_end_0, end_mask = cache20_1_end_mask_0, squeeze_mask = cache20_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache20_1_cast_fp16")]; tensor input_129_axes_0 = const()[name = tensor("input_129_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(63741504)))]; 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(63742592)))]; tensor input_129_cast_fp16 = layer_norm(axes = input_129_axes_0, beta = encoder_layers_10_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_10_norm_feed_forward1_weight_to_fp16, x = input0_129_cast_fp16)[name = tensor("input_129_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(63743680))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64792320))), name = tensor("encoder_layers_10_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_129_cast_fp16)[name = tensor("linear_91_cast_fp16")]; tensor var_2496_cast_fp16 = silu(x = linear_91_cast_fp16)[name = tensor("op_2496_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(64792896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65841536))), name = tensor("encoder_layers_10_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2496_cast_fp16)[name = tensor("linear_92_cast_fp16")]; tensor var_2501_to_fp16 = const()[name = tensor("op_2501_to_fp16"), val = tensor(0x1p-1)]; tensor var_2502_cast_fp16 = mul(x = linear_92_cast_fp16, y = var_2501_to_fp16)[name = tensor("op_2502_cast_fp16")]; tensor input_133_cast_fp16 = add(x = input0_129_cast_fp16, y = var_2502_cast_fp16)[name = tensor("input_133_cast_fp16")]; tensor key_22_axes_0 = const()[name = tensor("key_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(65842112)))]; 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(65843200)))]; tensor key_22_cast_fp16 = layer_norm(axes = key_22_axes_0, beta = encoder_layers_10_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_10_norm_self_att_weight_to_fp16, x = input_133_cast_fp16)[name = tensor("key_22_cast_fp16")]; tensor input_135_interleave_0 = const()[name = tensor("input_135_interleave_0"), val = tensor(false)]; tensor input_135_cast_fp16 = concat(axis = var_55, interleave = input_135_interleave_0, values = (cache19_1_cast_fp16, key_22_cast_fp16))[name = tensor("input_135_cast_fp16")]; tensor var_2524_begin_0 = const()[name = tensor("op_2524_begin_0"), val = tensor([0, 4, 0])]; tensor var_2524_end_0 = const()[name = tensor("op_2524_end_0"), val = tensor([1, 70, 512])]; tensor var_2524_end_mask_0 = const()[name = tensor("op_2524_end_mask_0"), val = tensor([true, true, true])]; tensor var_2524_cast_fp16 = slice_by_index(begin = var_2524_begin_0, end = var_2524_end_0, end_mask = var_2524_end_mask_0, x = cache19_1_cast_fp16)[name = tensor("op_2524_cast_fp16")]; tensor var_2527_begin_0 = const()[name = tensor("op_2527_begin_0"), val = tensor([0, 0, 0])]; tensor var_2527_end_0 = const()[name = tensor("op_2527_end_0"), val = tensor([1, 4, 512])]; tensor var_2527_end_mask_0 = const()[name = tensor("op_2527_end_mask_0"), val = tensor([true, false, true])]; tensor var_2527_cast_fp16 = slice_by_index(begin = var_2527_begin_0, end = var_2527_end_0, end_mask = var_2527_end_mask_0, x = key_22_cast_fp16)[name = tensor("op_2527_cast_fp16")]; tensor var_2530_interleave_0 = const()[name = tensor("op_2530_interleave_0"), val = tensor(false)]; tensor var_2530_cast_fp16 = concat(axis = var_55, interleave = var_2530_interleave_0, values = (var_2524_cast_fp16, var_2527_cast_fp16))[name = tensor("op_2530_cast_fp16")]; 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(65844288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66106496))), name = tensor("encoder_layers_10_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_22_cast_fp16)[name = tensor("linear_93_cast_fp16")]; tensor var_2534 = const()[name = tensor("op_2534"), val = tensor([1, -1, 8, 64])]; tensor q_22_cast_fp16 = reshape(shape = var_2534, 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(66107072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66369280))), name = tensor("encoder_layers_10_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_135_cast_fp16)[name = tensor("linear_94_cast_fp16")]; tensor var_2538 = const()[name = tensor("op_2538"), val = tensor([1, -1, 8, 64])]; tensor k_22_cast_fp16 = reshape(shape = var_2538, 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(66369856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66632064))), name = tensor("encoder_layers_10_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_135_cast_fp16)[name = tensor("linear_95_cast_fp16")]; tensor var_2542 = const()[name = tensor("op_2542"), val = tensor([1, -1, 8, 64])]; tensor v_22_cast_fp16 = reshape(shape = var_2542, x = linear_95_cast_fp16)[name = tensor("v_22_cast_fp16")]; tensor value_24_perm_0 = const()[name = tensor("value_24_perm_0"), val = tensor([0, 2, -3, -1])]; 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(66632640)))]; tensor var_2554_cast_fp16 = add(x = q_22_cast_fp16, y = encoder_layers_10_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2554_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(66633728)))]; tensor var_2556_cast_fp16 = add(x = q_22_cast_fp16, y = encoder_layers_10_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2556_cast_fp16")]; tensor q_with_bias_v_22_perm_0 = const()[name = tensor("q_with_bias_v_22_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_211_transpose_x_0 = const()[name = tensor("x_211_transpose_x_0"), val = tensor(false)]; tensor x_211_transpose_y_0 = const()[name = tensor("x_211_transpose_y_0"), val = tensor(false)]; tensor op_2558_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66634816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66714240))), name = tensor("op_2558_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_22_cast_fp16 = transpose(perm = q_with_bias_v_22_perm_0, x = var_2556_cast_fp16)[name = tensor("transpose_164")]; tensor x_211_cast_fp16 = matmul(transpose_x = x_211_transpose_x_0, transpose_y = x_211_transpose_y_0, x = q_with_bias_v_22_cast_fp16, y = op_2558_to_fp16_palettized)[name = tensor("x_211_cast_fp16")]; 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_209_to_fp16 = const()[name = tensor("const_209_to_fp16"), val = tensor(0x0p+0)]; tensor x0_24_cast_fp16 = pad(constant_val = const_209_to_fp16, mode = x0_24_mode_0, pad = x0_24_pad_0, x = x_211_cast_fp16)[name = tensor("x0_24_cast_fp16")]; tensor var_2566 = const()[name = tensor("op_2566"), val = tensor([1, 8, -1, 8])]; tensor x1_22_cast_fp16 = reshape(shape = var_2566, x = x0_24_cast_fp16)[name = tensor("x1_22_cast_fp16")]; tensor var_2570_begin_0 = const()[name = tensor("op_2570_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2570_end_0 = const()[name = tensor("op_2570_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_2570_end_mask_0 = const()[name = tensor("op_2570_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2570_cast_fp16 = slice_by_index(begin = var_2570_begin_0, end = var_2570_end_0, end_mask = var_2570_end_mask_0, x = x1_22_cast_fp16)[name = tensor("op_2570_cast_fp16")]; tensor var_2571 = const()[name = tensor("op_2571"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_22_cast_fp16 = reshape(shape = var_2571, x = var_2570_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_88_perm_0 = const()[name = tensor("transpose_88_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_89_perm_0 = const()[name = tensor("transpose_89_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_89 = transpose(perm = transpose_89_perm_0, x = k_22_cast_fp16)[name = tensor("transpose_162")]; tensor transpose_88 = transpose(perm = transpose_88_perm_0, x = var_2554_cast_fp16)[name = tensor("transpose_163")]; 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_88, y = transpose_89)[name = tensor("matrix_ac_22_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_22_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_22_end_0, end_mask = matrix_bd0_22_end_mask_0, x = matrix_bd_22_cast_fp16)[name = tensor("matrix_bd0_22_cast_fp16")]; tensor var_2580_cast_fp16 = add(x = matrix_ac_22_cast_fp16, y = matrix_bd0_22_cast_fp16)[name = tensor("op_2580_cast_fp16")]; tensor _inversed_scores_22_y_0_to_fp16 = const()[name = tensor("_inversed_scores_22_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_22_cast_fp16 = mul(x = var_2580_cast_fp16, y = _inversed_scores_22_y_0_to_fp16)[name = tensor("_inversed_scores_22_cast_fp16")]; tensor scores0_22_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_22_cast_fp16, cond = mask0_4)[name = tensor("scores0_22_cast_fp16")]; tensor var_2586_cast_fp16 = softmax(axis = var_47, x = scores0_22_cast_fp16)[name = tensor("op_2586_cast_fp16")]; tensor input0_131_cast_fp16 = select(a = var_26_to_fp16, b = var_2586_cast_fp16, cond = mask0_4)[name = tensor("input0_131_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 value_24_cast_fp16 = transpose(perm = value_24_perm_0, x = v_22_cast_fp16)[name = tensor("transpose_161")]; tensor x2_22_cast_fp16 = matmul(transpose_x = x2_22_transpose_x_0, transpose_y = x2_22_transpose_y_0, x = input0_131_cast_fp16, y = value_24_cast_fp16)[name = tensor("x2_22_cast_fp16")]; tensor var_2590_perm_0 = const()[name = tensor("op_2590_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_2591 = const()[name = tensor("op_2591"), val = tensor([1, -1, 512])]; tensor var_2590_cast_fp16 = transpose(perm = var_2590_perm_0, x = x2_22_cast_fp16)[name = tensor("transpose_160")]; tensor input1_66_cast_fp16 = reshape(shape = var_2591, x = var_2590_cast_fp16)[name = tensor("input1_66_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(66714816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66977024))), name = tensor("encoder_layers_10_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_66_cast_fp16)[name = tensor("linear_97_cast_fp16")]; tensor input0_133_cast_fp16 = add(x = input_133_cast_fp16, y = linear_97_cast_fp16)[name = tensor("input0_133_cast_fp16")]; tensor x_215_axes_0 = const()[name = tensor("x_215_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(66977600)))]; 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(66978688)))]; tensor x_215_cast_fp16 = layer_norm(axes = x_215_axes_0, beta = encoder_layers_10_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_10_norm_conv_weight_to_fp16, x = input0_133_cast_fp16)[name = tensor("x_215_cast_fp16")]; tensor input_137_perm_0 = const()[name = tensor("input_137_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_10_conv_pointwise_conv1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(66979776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67504128))), name = tensor("encoder_layers_10_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_137_cast_fp16 = transpose(perm = input_137_perm_0, x = x_215_cast_fp16)[name = tensor("transpose_159")]; 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_10_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_137_cast_fp16)[name = tensor("input0_135_cast_fp16")]; tensor x_217_split_num_splits_0 = const()[name = tensor("x_217_split_num_splits_0"), val = tensor(2)]; tensor x_217_split_axis_0 = const()[name = tensor("x_217_split_axis_0"), val = tensor(1)]; tensor x_217_split_cast_fp16_0, tensor x_217_split_cast_fp16_1 = split(axis = x_217_split_axis_0, num_splits = x_217_split_num_splits_0, x = input0_135_cast_fp16)[name = tensor("x_217_split_cast_fp16")]; tensor x_217_split_1_sigmoid_cast_fp16 = sigmoid(x = x_217_split_cast_fp16_1)[name = tensor("x_217_split_1_sigmoid_cast_fp16")]; tensor x_217_cast_fp16 = mul(x = x_217_split_cast_fp16_0, y = x_217_split_1_sigmoid_cast_fp16)[name = tensor("x_217_cast_fp16")]; tensor input0_137_cast_fp16 = select(a = var_26_to_fp16, b = x_217_cast_fp16, cond = var_546)[name = tensor("input0_137_cast_fp16")]; tensor new_x0_22_interleave_0 = const()[name = tensor("new_x0_22_interleave_0"), val = tensor(false)]; tensor new_x0_22_cast_fp16 = concat(axis = var_47, interleave = new_x0_22_interleave_0, values = (cache20_1_cast_fp16, input0_137_cast_fp16))[name = tensor("new_x0_22_cast_fp16")]; tensor next_cache_22_begin_0 = const()[name = tensor("next_cache_22_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_22_end_0 = const()[name = tensor("next_cache_22_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_22_end_mask_0 = const()[name = tensor("next_cache_22_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_22_cast_fp16 = slice_by_index(begin = next_cache_22_begin_0, end = next_cache_22_end_0, end_mask = next_cache_22_end_mask_0, x = new_x0_22_cast_fp16)[name = tensor("next_cache_22_cast_fp16")]; tensor var_2632_begin_0 = const()[name = tensor("op_2632_begin_0"), val = tensor([0, 0, 4])]; tensor var_2632_end_0 = const()[name = tensor("op_2632_end_0"), val = tensor([1, 512, 12])]; tensor var_2632_end_mask_0 = const()[name = tensor("op_2632_end_mask_0"), val = tensor([true, true, true])]; tensor var_2632_cast_fp16 = slice_by_index(begin = var_2632_begin_0, end = var_2632_end_0, end_mask = var_2632_end_mask_0, x = next_cache_22_cast_fp16)[name = tensor("op_2632_cast_fp16")]; tensor x_219_pad_type_0 = const()[name = tensor("x_219_pad_type_0"), val = tensor("valid")]; tensor x_219_groups_0 = const()[name = tensor("x_219_groups_0"), val = tensor(512)]; tensor x_219_strides_0 = const()[name = tensor("x_219_strides_0"), val = tensor([1])]; tensor x_219_pad_0 = const()[name = tensor("x_219_pad_0"), val = tensor([0, 0])]; tensor x_219_dilations_0 = const()[name = tensor("x_219_dilations_0"), val = tensor([1])]; tensor encoder_layers_10_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67504704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67509376))), name = tensor("encoder_layers_10_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_219_cast_fp16 = conv(dilations = x_219_dilations_0, groups = x_219_groups_0, pad = x_219_pad_0, pad_type = x_219_pad_type_0, strides = x_219_strides_0, weight = encoder_layers_10_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_22_cast_fp16)[name = tensor("x_219_cast_fp16")]; tensor input1_68_perm_0 = const()[name = tensor("input1_68_perm_0"), val = tensor([0, 2, 1])]; tensor x_221_axes_0 = const()[name = tensor("x_221_axes_0"), val = tensor([-1])]; tensor encoder_layers_10_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_10_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67509952)))]; tensor encoder_layers_10_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_10_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67511040)))]; tensor input1_68_cast_fp16 = transpose(perm = input1_68_perm_0, x = x_219_cast_fp16)[name = tensor("transpose_158")]; tensor x_221_cast_fp16 = layer_norm(axes = x_221_axes_0, beta = encoder_layers_10_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_10_conv_batch_norm_weight_to_fp16, x = input1_68_cast_fp16)[name = tensor("x_221_cast_fp16")]; tensor input2_44_perm_0 = const()[name = tensor("input2_44_perm_0"), val = tensor([0, 2, 1])]; tensor input2_44_cast_fp16 = transpose(perm = input2_44_perm_0, x = x_221_cast_fp16)[name = tensor("transpose_157")]; tensor var_2647_cast_fp16 = silu(x = input2_44_cast_fp16)[name = tensor("op_2647_cast_fp16")]; tensor x_223_pad_type_0 = const()[name = tensor("x_223_pad_type_0"), val = tensor("valid")]; tensor x_223_strides_0 = const()[name = tensor("x_223_strides_0"), val = tensor([1])]; tensor x_223_pad_0 = const()[name = tensor("x_223_pad_0"), val = tensor([0, 0])]; tensor x_223_dilations_0 = const()[name = tensor("x_223_dilations_0"), val = tensor([1])]; tensor x_223_groups_0 = const()[name = tensor("x_223_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(67512128))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67774336))), name = tensor("encoder_layers_10_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_223_cast_fp16 = conv(dilations = x_223_dilations_0, groups = x_223_groups_0, pad = x_223_pad_0, pad_type = x_223_pad_type_0, strides = x_223_strides_0, weight = encoder_layers_10_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2647_cast_fp16)[name = tensor("x_223_cast_fp16")]; tensor input3_24_perm_0 = const()[name = tensor("input3_24_perm_0"), val = tensor([0, 2, 1])]; tensor input3_24_cast_fp16 = transpose(perm = input3_24_perm_0, x = x_223_cast_fp16)[name = tensor("transpose_156")]; tensor input1_70_cast_fp16 = add(x = input0_133_cast_fp16, y = input3_24_cast_fp16)[name = tensor("input1_70_cast_fp16")]; tensor input0_139_axes_0 = const()[name = tensor("input0_139_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(67774912)))]; 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(67776000)))]; tensor input0_139_cast_fp16 = layer_norm(axes = input0_139_axes_0, beta = encoder_layers_10_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_10_norm_feed_forward2_weight_to_fp16, x = input1_70_cast_fp16)[name = tensor("input0_139_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(67777088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(68825728))), name = tensor("encoder_layers_10_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_139_cast_fp16)[name = tensor("linear_98_cast_fp16")]; tensor var_2668_cast_fp16 = silu(x = linear_98_cast_fp16)[name = tensor("op_2668_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(68826304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69874944))), name = tensor("encoder_layers_10_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2668_cast_fp16)[name = tensor("linear_99_cast_fp16")]; tensor var_2673_to_fp16 = const()[name = tensor("op_2673_to_fp16"), val = tensor(0x1p-1)]; tensor var_2674_cast_fp16 = mul(x = linear_99_cast_fp16, y = var_2673_to_fp16)[name = tensor("op_2674_cast_fp16")]; tensor input2_46_cast_fp16 = add(x = input1_70_cast_fp16, y = var_2674_cast_fp16)[name = tensor("input2_46_cast_fp16")]; tensor input0_141_axes_0 = const()[name = tensor("input0_141_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(69875520)))]; 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(69876608)))]; tensor input0_141_cast_fp16 = layer_norm(axes = input0_141_axes_0, beta = encoder_layers_10_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_10_norm_out_weight_to_fp16, x = input2_46_cast_fp16)[name = tensor("input0_141_cast_fp16")]; tensor cache21_1_begin_0 = const()[name = tensor("cache21_1_begin_0"), val = tensor([11, 0, 0, 0])]; tensor cache21_1_end_0 = const()[name = tensor("cache21_1_end_0"), val = tensor([12, 1, 70, 512])]; tensor cache21_1_end_mask_0 = const()[name = tensor("cache21_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache21_1_squeeze_mask_0 = const()[name = tensor("cache21_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache21_1_cast_fp16 = slice_by_index(begin = cache21_1_begin_0, end = cache21_1_end_0, end_mask = cache21_1_end_mask_0, squeeze_mask = cache21_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache21_1_cast_fp16")]; tensor cache22_1_begin_0 = const()[name = tensor("cache22_1_begin_0"), val = tensor([11, 0, 0, 0])]; tensor cache22_1_end_0 = const()[name = tensor("cache22_1_end_0"), val = tensor([12, 1, 512, 8])]; tensor cache22_1_end_mask_0 = const()[name = tensor("cache22_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache22_1_squeeze_mask_0 = const()[name = tensor("cache22_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache22_1_cast_fp16 = slice_by_index(begin = cache22_1_begin_0, end = cache22_1_end_0, end_mask = cache22_1_end_mask_0, squeeze_mask = cache22_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache22_1_cast_fp16")]; tensor input_141_axes_0 = const()[name = tensor("input_141_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(69877696)))]; 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(69878784)))]; tensor input_141_cast_fp16 = layer_norm(axes = input_141_axes_0, beta = encoder_layers_11_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_11_norm_feed_forward1_weight_to_fp16, x = input0_141_cast_fp16)[name = tensor("input_141_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(69879872))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70928512))), name = tensor("encoder_layers_11_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_141_cast_fp16)[name = tensor("linear_100_cast_fp16")]; tensor var_2703_cast_fp16 = silu(x = linear_100_cast_fp16)[name = tensor("op_2703_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(70929088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(71977728))), name = tensor("encoder_layers_11_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2703_cast_fp16)[name = tensor("linear_101_cast_fp16")]; tensor var_2708_to_fp16 = const()[name = tensor("op_2708_to_fp16"), val = tensor(0x1p-1)]; tensor var_2709_cast_fp16 = mul(x = linear_101_cast_fp16, y = var_2708_to_fp16)[name = tensor("op_2709_cast_fp16")]; tensor input_145_cast_fp16 = add(x = input0_141_cast_fp16, y = var_2709_cast_fp16)[name = tensor("input_145_cast_fp16")]; tensor key_24_axes_0 = const()[name = tensor("key_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(71978304)))]; 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(71979392)))]; tensor key_24_cast_fp16 = layer_norm(axes = key_24_axes_0, beta = encoder_layers_11_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_11_norm_self_att_weight_to_fp16, x = input_145_cast_fp16)[name = tensor("key_24_cast_fp16")]; tensor input_147_interleave_0 = const()[name = tensor("input_147_interleave_0"), val = tensor(false)]; tensor input_147_cast_fp16 = concat(axis = var_55, interleave = input_147_interleave_0, values = (cache21_1_cast_fp16, key_24_cast_fp16))[name = tensor("input_147_cast_fp16")]; tensor var_2731_begin_0 = const()[name = tensor("op_2731_begin_0"), val = tensor([0, 4, 0])]; tensor var_2731_end_0 = const()[name = tensor("op_2731_end_0"), val = tensor([1, 70, 512])]; tensor var_2731_end_mask_0 = const()[name = tensor("op_2731_end_mask_0"), val = tensor([true, true, true])]; tensor var_2731_cast_fp16 = slice_by_index(begin = var_2731_begin_0, end = var_2731_end_0, end_mask = var_2731_end_mask_0, x = cache21_1_cast_fp16)[name = tensor("op_2731_cast_fp16")]; tensor var_2734_begin_0 = const()[name = tensor("op_2734_begin_0"), val = tensor([0, 0, 0])]; tensor var_2734_end_0 = const()[name = tensor("op_2734_end_0"), val = tensor([1, 4, 512])]; tensor var_2734_end_mask_0 = const()[name = tensor("op_2734_end_mask_0"), val = tensor([true, false, true])]; tensor var_2734_cast_fp16 = slice_by_index(begin = var_2734_begin_0, end = var_2734_end_0, end_mask = var_2734_end_mask_0, x = key_24_cast_fp16)[name = tensor("op_2734_cast_fp16")]; tensor var_2737_interleave_0 = const()[name = tensor("op_2737_interleave_0"), val = tensor(false)]; tensor var_2737_cast_fp16 = concat(axis = var_55, interleave = var_2737_interleave_0, values = (var_2731_cast_fp16, var_2734_cast_fp16))[name = tensor("op_2737_cast_fp16")]; 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(71980480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72242688))), name = tensor("encoder_layers_11_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_24_cast_fp16)[name = tensor("linear_102_cast_fp16")]; tensor var_2741 = const()[name = tensor("op_2741"), val = tensor([1, -1, 8, 64])]; tensor q_24_cast_fp16 = reshape(shape = var_2741, 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(72243264))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72505472))), name = tensor("encoder_layers_11_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_147_cast_fp16)[name = tensor("linear_103_cast_fp16")]; tensor var_2745 = const()[name = tensor("op_2745"), val = tensor([1, -1, 8, 64])]; tensor k_24_cast_fp16 = reshape(shape = var_2745, 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(72506048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72768256))), name = tensor("encoder_layers_11_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_147_cast_fp16)[name = tensor("linear_104_cast_fp16")]; tensor var_2749 = const()[name = tensor("op_2749"), val = tensor([1, -1, 8, 64])]; tensor v_24_cast_fp16 = reshape(shape = var_2749, x = linear_104_cast_fp16)[name = tensor("v_24_cast_fp16")]; tensor value_26_perm_0 = const()[name = tensor("value_26_perm_0"), val = tensor([0, 2, -3, -1])]; 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(72768832)))]; tensor var_2761_cast_fp16 = add(x = q_24_cast_fp16, y = encoder_layers_11_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2761_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(72769920)))]; tensor var_2763_cast_fp16 = add(x = q_24_cast_fp16, y = encoder_layers_11_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2763_cast_fp16")]; tensor q_with_bias_v_24_perm_0 = const()[name = tensor("q_with_bias_v_24_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_231_transpose_x_0 = const()[name = tensor("x_231_transpose_x_0"), val = tensor(false)]; tensor x_231_transpose_y_0 = const()[name = tensor("x_231_transpose_y_0"), val = tensor(false)]; tensor op_2765_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72771008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72850432))), name = tensor("op_2765_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_24_cast_fp16 = transpose(perm = q_with_bias_v_24_perm_0, x = var_2763_cast_fp16)[name = tensor("transpose_155")]; tensor x_231_cast_fp16 = matmul(transpose_x = x_231_transpose_x_0, transpose_y = x_231_transpose_y_0, x = q_with_bias_v_24_cast_fp16, y = op_2765_to_fp16_palettized)[name = tensor("x_231_cast_fp16")]; 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_222_to_fp16 = const()[name = tensor("const_222_to_fp16"), val = tensor(0x0p+0)]; tensor x0_26_cast_fp16 = pad(constant_val = const_222_to_fp16, mode = x0_26_mode_0, pad = x0_26_pad_0, x = x_231_cast_fp16)[name = tensor("x0_26_cast_fp16")]; tensor var_2773 = const()[name = tensor("op_2773"), val = tensor([1, 8, -1, 8])]; tensor x1_24_cast_fp16 = reshape(shape = var_2773, x = x0_26_cast_fp16)[name = tensor("x1_24_cast_fp16")]; tensor var_2777_begin_0 = const()[name = tensor("op_2777_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2777_end_0 = const()[name = tensor("op_2777_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_2777_end_mask_0 = const()[name = tensor("op_2777_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2777_cast_fp16 = slice_by_index(begin = var_2777_begin_0, end = var_2777_end_0, end_mask = var_2777_end_mask_0, x = x1_24_cast_fp16)[name = tensor("op_2777_cast_fp16")]; tensor var_2778 = const()[name = tensor("op_2778"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_24_cast_fp16 = reshape(shape = var_2778, x = var_2777_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_90_perm_0 = const()[name = tensor("transpose_90_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_91_perm_0 = const()[name = tensor("transpose_91_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_91 = transpose(perm = transpose_91_perm_0, x = k_24_cast_fp16)[name = tensor("transpose_153")]; tensor transpose_90 = transpose(perm = transpose_90_perm_0, x = var_2761_cast_fp16)[name = tensor("transpose_154")]; 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_90, y = transpose_91)[name = tensor("matrix_ac_24_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_24_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_24_end_0, end_mask = matrix_bd0_24_end_mask_0, x = matrix_bd_24_cast_fp16)[name = tensor("matrix_bd0_24_cast_fp16")]; tensor var_2787_cast_fp16 = add(x = matrix_ac_24_cast_fp16, y = matrix_bd0_24_cast_fp16)[name = tensor("op_2787_cast_fp16")]; tensor _inversed_scores_24_y_0_to_fp16 = const()[name = tensor("_inversed_scores_24_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_24_cast_fp16 = mul(x = var_2787_cast_fp16, y = _inversed_scores_24_y_0_to_fp16)[name = tensor("_inversed_scores_24_cast_fp16")]; tensor scores0_24_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_24_cast_fp16, cond = mask0_4)[name = tensor("scores0_24_cast_fp16")]; tensor var_2793_cast_fp16 = softmax(axis = var_47, x = scores0_24_cast_fp16)[name = tensor("op_2793_cast_fp16")]; tensor input0_143_cast_fp16 = select(a = var_26_to_fp16, b = var_2793_cast_fp16, cond = mask0_4)[name = tensor("input0_143_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 value_26_cast_fp16 = transpose(perm = value_26_perm_0, x = v_24_cast_fp16)[name = tensor("transpose_152")]; tensor x2_24_cast_fp16 = matmul(transpose_x = x2_24_transpose_x_0, transpose_y = x2_24_transpose_y_0, x = input0_143_cast_fp16, y = value_26_cast_fp16)[name = tensor("x2_24_cast_fp16")]; tensor var_2797_perm_0 = const()[name = tensor("op_2797_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_2798 = const()[name = tensor("op_2798"), val = tensor([1, -1, 512])]; tensor var_2797_cast_fp16 = transpose(perm = var_2797_perm_0, x = x2_24_cast_fp16)[name = tensor("transpose_151")]; tensor input1_72_cast_fp16 = reshape(shape = var_2798, x = var_2797_cast_fp16)[name = tensor("input1_72_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(72851008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73113216))), name = tensor("encoder_layers_11_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_72_cast_fp16)[name = tensor("linear_106_cast_fp16")]; tensor input0_145_cast_fp16 = add(x = input_145_cast_fp16, y = linear_106_cast_fp16)[name = tensor("input0_145_cast_fp16")]; tensor x_235_axes_0 = const()[name = tensor("x_235_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(73113792)))]; 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(73114880)))]; tensor x_235_cast_fp16 = layer_norm(axes = x_235_axes_0, beta = encoder_layers_11_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_11_norm_conv_weight_to_fp16, x = input0_145_cast_fp16)[name = tensor("x_235_cast_fp16")]; tensor input_149_perm_0 = const()[name = tensor("input_149_perm_0"), val = tensor([0, 2, 1])]; tensor input0_147_pad_type_0 = const()[name = tensor("input0_147_pad_type_0"), val = tensor("valid")]; tensor input0_147_strides_0 = const()[name = tensor("input0_147_strides_0"), val = tensor([1])]; tensor input0_147_pad_0 = const()[name = tensor("input0_147_pad_0"), val = tensor([0, 0])]; tensor input0_147_dilations_0 = const()[name = tensor("input0_147_dilations_0"), val = tensor([1])]; tensor input0_147_groups_0 = const()[name = tensor("input0_147_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(73115968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73640320))), name = tensor("encoder_layers_11_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_149_cast_fp16 = transpose(perm = input_149_perm_0, x = x_235_cast_fp16)[name = tensor("transpose_150")]; tensor input0_147_cast_fp16 = conv(dilations = input0_147_dilations_0, groups = input0_147_groups_0, pad = input0_147_pad_0, pad_type = input0_147_pad_type_0, strides = input0_147_strides_0, weight = encoder_layers_11_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_149_cast_fp16)[name = tensor("input0_147_cast_fp16")]; tensor x_237_split_num_splits_0 = const()[name = tensor("x_237_split_num_splits_0"), val = tensor(2)]; tensor x_237_split_axis_0 = const()[name = tensor("x_237_split_axis_0"), val = tensor(1)]; tensor x_237_split_cast_fp16_0, tensor x_237_split_cast_fp16_1 = split(axis = x_237_split_axis_0, num_splits = x_237_split_num_splits_0, x = input0_147_cast_fp16)[name = tensor("x_237_split_cast_fp16")]; tensor x_237_split_1_sigmoid_cast_fp16 = sigmoid(x = x_237_split_cast_fp16_1)[name = tensor("x_237_split_1_sigmoid_cast_fp16")]; tensor x_237_cast_fp16 = mul(x = x_237_split_cast_fp16_0, y = x_237_split_1_sigmoid_cast_fp16)[name = tensor("x_237_cast_fp16")]; tensor input0_149_cast_fp16 = select(a = var_26_to_fp16, b = x_237_cast_fp16, cond = var_546)[name = tensor("input0_149_cast_fp16")]; tensor new_x0_24_interleave_0 = const()[name = tensor("new_x0_24_interleave_0"), val = tensor(false)]; tensor new_x0_24_cast_fp16 = concat(axis = var_47, interleave = new_x0_24_interleave_0, values = (cache22_1_cast_fp16, input0_149_cast_fp16))[name = tensor("new_x0_24_cast_fp16")]; tensor next_cache_24_begin_0 = const()[name = tensor("next_cache_24_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_24_end_0 = const()[name = tensor("next_cache_24_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_24_end_mask_0 = const()[name = tensor("next_cache_24_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_24_cast_fp16 = slice_by_index(begin = next_cache_24_begin_0, end = next_cache_24_end_0, end_mask = next_cache_24_end_mask_0, x = new_x0_24_cast_fp16)[name = tensor("next_cache_24_cast_fp16")]; tensor var_2839_begin_0 = const()[name = tensor("op_2839_begin_0"), val = tensor([0, 0, 4])]; tensor var_2839_end_0 = const()[name = tensor("op_2839_end_0"), val = tensor([1, 512, 12])]; tensor var_2839_end_mask_0 = const()[name = tensor("op_2839_end_mask_0"), val = tensor([true, true, true])]; tensor var_2839_cast_fp16 = slice_by_index(begin = var_2839_begin_0, end = var_2839_end_0, end_mask = var_2839_end_mask_0, x = next_cache_24_cast_fp16)[name = tensor("op_2839_cast_fp16")]; tensor x_239_pad_type_0 = const()[name = tensor("x_239_pad_type_0"), val = tensor("valid")]; tensor x_239_groups_0 = const()[name = tensor("x_239_groups_0"), val = tensor(512)]; tensor x_239_strides_0 = const()[name = tensor("x_239_strides_0"), val = tensor([1])]; tensor x_239_pad_0 = const()[name = tensor("x_239_pad_0"), val = tensor([0, 0])]; tensor x_239_dilations_0 = const()[name = tensor("x_239_dilations_0"), val = tensor([1])]; tensor encoder_layers_11_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73640896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73645568))), name = tensor("encoder_layers_11_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_239_cast_fp16 = conv(dilations = x_239_dilations_0, groups = x_239_groups_0, pad = x_239_pad_0, pad_type = x_239_pad_type_0, strides = x_239_strides_0, weight = encoder_layers_11_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_24_cast_fp16)[name = tensor("x_239_cast_fp16")]; tensor input1_74_perm_0 = const()[name = tensor("input1_74_perm_0"), val = tensor([0, 2, 1])]; tensor x_241_axes_0 = const()[name = tensor("x_241_axes_0"), val = tensor([-1])]; tensor encoder_layers_11_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_11_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73646144)))]; tensor encoder_layers_11_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_11_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73647232)))]; tensor input1_74_cast_fp16 = transpose(perm = input1_74_perm_0, x = x_239_cast_fp16)[name = tensor("transpose_149")]; tensor x_241_cast_fp16 = layer_norm(axes = x_241_axes_0, beta = encoder_layers_11_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_11_conv_batch_norm_weight_to_fp16, x = input1_74_cast_fp16)[name = tensor("x_241_cast_fp16")]; tensor input2_48_perm_0 = const()[name = tensor("input2_48_perm_0"), val = tensor([0, 2, 1])]; tensor input2_48_cast_fp16 = transpose(perm = input2_48_perm_0, x = x_241_cast_fp16)[name = tensor("transpose_148")]; tensor var_2854_cast_fp16 = silu(x = input2_48_cast_fp16)[name = tensor("op_2854_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_11_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73648320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73910528))), name = tensor("encoder_layers_11_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 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_11_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_2854_cast_fp16)[name = tensor("x_243_cast_fp16")]; tensor input3_26_perm_0 = const()[name = tensor("input3_26_perm_0"), val = tensor([0, 2, 1])]; tensor input3_26_cast_fp16 = transpose(perm = input3_26_perm_0, x = x_243_cast_fp16)[name = tensor("transpose_147")]; tensor input1_76_cast_fp16 = add(x = input0_145_cast_fp16, y = input3_26_cast_fp16)[name = tensor("input1_76_cast_fp16")]; tensor input0_151_axes_0 = const()[name = tensor("input0_151_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(73911104)))]; 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(73912192)))]; tensor input0_151_cast_fp16 = layer_norm(axes = input0_151_axes_0, beta = encoder_layers_11_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_11_norm_feed_forward2_weight_to_fp16, x = input1_76_cast_fp16)[name = tensor("input0_151_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(73913280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74961920))), name = tensor("encoder_layers_11_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_151_cast_fp16)[name = tensor("linear_107_cast_fp16")]; tensor var_2875_cast_fp16 = silu(x = linear_107_cast_fp16)[name = tensor("op_2875_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(74962496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(76011136))), name = tensor("encoder_layers_11_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2875_cast_fp16)[name = tensor("linear_108_cast_fp16")]; tensor var_2880_to_fp16 = const()[name = tensor("op_2880_to_fp16"), val = tensor(0x1p-1)]; tensor var_2881_cast_fp16 = mul(x = linear_108_cast_fp16, y = var_2880_to_fp16)[name = tensor("op_2881_cast_fp16")]; tensor input2_50_cast_fp16 = add(x = input1_76_cast_fp16, y = var_2881_cast_fp16)[name = tensor("input2_50_cast_fp16")]; tensor input0_153_axes_0 = const()[name = tensor("input0_153_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(76011712)))]; 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(76012800)))]; tensor input0_153_cast_fp16 = layer_norm(axes = input0_153_axes_0, beta = encoder_layers_11_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_11_norm_out_weight_to_fp16, x = input2_50_cast_fp16)[name = tensor("input0_153_cast_fp16")]; tensor cache23_1_begin_0 = const()[name = tensor("cache23_1_begin_0"), val = tensor([12, 0, 0, 0])]; tensor cache23_1_end_0 = const()[name = tensor("cache23_1_end_0"), val = tensor([13, 1, 70, 512])]; tensor cache23_1_end_mask_0 = const()[name = tensor("cache23_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache23_1_squeeze_mask_0 = const()[name = tensor("cache23_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache23_1_cast_fp16 = slice_by_index(begin = cache23_1_begin_0, end = cache23_1_end_0, end_mask = cache23_1_end_mask_0, squeeze_mask = cache23_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache23_1_cast_fp16")]; tensor cache24_1_begin_0 = const()[name = tensor("cache24_1_begin_0"), val = tensor([12, 0, 0, 0])]; tensor cache24_1_end_0 = const()[name = tensor("cache24_1_end_0"), val = tensor([13, 1, 512, 8])]; tensor cache24_1_end_mask_0 = const()[name = tensor("cache24_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache24_1_squeeze_mask_0 = const()[name = tensor("cache24_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache24_1_cast_fp16 = slice_by_index(begin = cache24_1_begin_0, end = cache24_1_end_0, end_mask = cache24_1_end_mask_0, squeeze_mask = cache24_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache24_1_cast_fp16")]; tensor input_153_axes_0 = const()[name = tensor("input_153_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(76013888)))]; 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(76014976)))]; tensor input_153_cast_fp16 = layer_norm(axes = input_153_axes_0, beta = encoder_layers_12_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_12_norm_feed_forward1_weight_to_fp16, x = input0_153_cast_fp16)[name = tensor("input_153_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(76016064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77064704))), name = tensor("encoder_layers_12_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_153_cast_fp16)[name = tensor("linear_109_cast_fp16")]; tensor var_2910_cast_fp16 = silu(x = linear_109_cast_fp16)[name = tensor("op_2910_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(77065280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78113920))), name = tensor("encoder_layers_12_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_2910_cast_fp16)[name = tensor("linear_110_cast_fp16")]; tensor var_2915_to_fp16 = const()[name = tensor("op_2915_to_fp16"), val = tensor(0x1p-1)]; tensor var_2916_cast_fp16 = mul(x = linear_110_cast_fp16, y = var_2915_to_fp16)[name = tensor("op_2916_cast_fp16")]; tensor input_157_cast_fp16 = add(x = input0_153_cast_fp16, y = var_2916_cast_fp16)[name = tensor("input_157_cast_fp16")]; tensor key_26_axes_0 = const()[name = tensor("key_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(78114496)))]; 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(78115584)))]; tensor key_26_cast_fp16 = layer_norm(axes = key_26_axes_0, beta = encoder_layers_12_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_12_norm_self_att_weight_to_fp16, x = input_157_cast_fp16)[name = tensor("key_26_cast_fp16")]; tensor input_159_interleave_0 = const()[name = tensor("input_159_interleave_0"), val = tensor(false)]; tensor input_159_cast_fp16 = concat(axis = var_55, interleave = input_159_interleave_0, values = (cache23_1_cast_fp16, key_26_cast_fp16))[name = tensor("input_159_cast_fp16")]; tensor var_2938_begin_0 = const()[name = tensor("op_2938_begin_0"), val = tensor([0, 4, 0])]; tensor var_2938_end_0 = const()[name = tensor("op_2938_end_0"), val = tensor([1, 70, 512])]; tensor var_2938_end_mask_0 = const()[name = tensor("op_2938_end_mask_0"), val = tensor([true, true, true])]; tensor var_2938_cast_fp16 = slice_by_index(begin = var_2938_begin_0, end = var_2938_end_0, end_mask = var_2938_end_mask_0, x = cache23_1_cast_fp16)[name = tensor("op_2938_cast_fp16")]; tensor var_2941_begin_0 = const()[name = tensor("op_2941_begin_0"), val = tensor([0, 0, 0])]; tensor var_2941_end_0 = const()[name = tensor("op_2941_end_0"), val = tensor([1, 4, 512])]; tensor var_2941_end_mask_0 = const()[name = tensor("op_2941_end_mask_0"), val = tensor([true, false, true])]; tensor var_2941_cast_fp16 = slice_by_index(begin = var_2941_begin_0, end = var_2941_end_0, end_mask = var_2941_end_mask_0, x = key_26_cast_fp16)[name = tensor("op_2941_cast_fp16")]; tensor var_2944_interleave_0 = const()[name = tensor("op_2944_interleave_0"), val = tensor(false)]; tensor var_2944_cast_fp16 = concat(axis = var_55, interleave = var_2944_interleave_0, values = (var_2938_cast_fp16, var_2941_cast_fp16))[name = tensor("op_2944_cast_fp16")]; 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(78116672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78378880))), name = tensor("encoder_layers_12_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_26_cast_fp16)[name = tensor("linear_111_cast_fp16")]; tensor var_2948 = const()[name = tensor("op_2948"), val = tensor([1, -1, 8, 64])]; tensor q_26_cast_fp16 = reshape(shape = var_2948, 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(78379456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78641664))), name = tensor("encoder_layers_12_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_159_cast_fp16)[name = tensor("linear_112_cast_fp16")]; tensor var_2952 = const()[name = tensor("op_2952"), val = tensor([1, -1, 8, 64])]; tensor k_26_cast_fp16 = reshape(shape = var_2952, 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(78642240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78904448))), name = tensor("encoder_layers_12_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_159_cast_fp16)[name = tensor("linear_113_cast_fp16")]; tensor var_2956 = const()[name = tensor("op_2956"), val = tensor([1, -1, 8, 64])]; tensor v_26_cast_fp16 = reshape(shape = var_2956, x = linear_113_cast_fp16)[name = tensor("v_26_cast_fp16")]; tensor value_28_perm_0 = const()[name = tensor("value_28_perm_0"), val = tensor([0, 2, -3, -1])]; 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(78905024)))]; tensor var_2968_cast_fp16 = add(x = q_26_cast_fp16, y = encoder_layers_12_self_attn_pos_bias_u_to_fp16)[name = tensor("op_2968_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(78906112)))]; tensor var_2970_cast_fp16 = add(x = q_26_cast_fp16, y = encoder_layers_12_self_attn_pos_bias_v_to_fp16)[name = tensor("op_2970_cast_fp16")]; tensor q_with_bias_v_26_perm_0 = const()[name = tensor("q_with_bias_v_26_perm_0"), val = tensor([0, 2, -3, -1])]; 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 op_2972_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78907200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78986624))), name = tensor("op_2972_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_26_cast_fp16 = transpose(perm = q_with_bias_v_26_perm_0, x = var_2970_cast_fp16)[name = tensor("transpose_146")]; tensor x_251_cast_fp16 = matmul(transpose_x = x_251_transpose_x_0, transpose_y = x_251_transpose_y_0, x = q_with_bias_v_26_cast_fp16, y = op_2972_to_fp16_palettized)[name = tensor("x_251_cast_fp16")]; 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_235_to_fp16 = const()[name = tensor("const_235_to_fp16"), val = tensor(0x0p+0)]; tensor x0_28_cast_fp16 = pad(constant_val = const_235_to_fp16, mode = x0_28_mode_0, pad = x0_28_pad_0, x = x_251_cast_fp16)[name = tensor("x0_28_cast_fp16")]; tensor var_2980 = const()[name = tensor("op_2980"), val = tensor([1, 8, -1, 8])]; tensor x1_26_cast_fp16 = reshape(shape = var_2980, x = x0_28_cast_fp16)[name = tensor("x1_26_cast_fp16")]; tensor var_2984_begin_0 = const()[name = tensor("op_2984_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_2984_end_0 = const()[name = tensor("op_2984_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_2984_end_mask_0 = const()[name = tensor("op_2984_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_2984_cast_fp16 = slice_by_index(begin = var_2984_begin_0, end = var_2984_end_0, end_mask = var_2984_end_mask_0, x = x1_26_cast_fp16)[name = tensor("op_2984_cast_fp16")]; tensor var_2985 = const()[name = tensor("op_2985"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_26_cast_fp16 = reshape(shape = var_2985, x = var_2984_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_92_perm_0 = const()[name = tensor("transpose_92_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_93_perm_0 = const()[name = tensor("transpose_93_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_93 = transpose(perm = transpose_93_perm_0, x = k_26_cast_fp16)[name = tensor("transpose_144")]; tensor transpose_92 = transpose(perm = transpose_92_perm_0, x = var_2968_cast_fp16)[name = tensor("transpose_145")]; 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_92, y = transpose_93)[name = tensor("matrix_ac_26_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_26_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_26_end_0, end_mask = matrix_bd0_26_end_mask_0, x = matrix_bd_26_cast_fp16)[name = tensor("matrix_bd0_26_cast_fp16")]; tensor var_2994_cast_fp16 = add(x = matrix_ac_26_cast_fp16, y = matrix_bd0_26_cast_fp16)[name = tensor("op_2994_cast_fp16")]; tensor _inversed_scores_26_y_0_to_fp16 = const()[name = tensor("_inversed_scores_26_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_26_cast_fp16 = mul(x = var_2994_cast_fp16, y = _inversed_scores_26_y_0_to_fp16)[name = tensor("_inversed_scores_26_cast_fp16")]; tensor scores0_26_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_26_cast_fp16, cond = mask0_4)[name = tensor("scores0_26_cast_fp16")]; tensor var_3000_cast_fp16 = softmax(axis = var_47, x = scores0_26_cast_fp16)[name = tensor("op_3000_cast_fp16")]; tensor input0_155_cast_fp16 = select(a = var_26_to_fp16, b = var_3000_cast_fp16, cond = mask0_4)[name = tensor("input0_155_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 value_28_cast_fp16 = transpose(perm = value_28_perm_0, x = v_26_cast_fp16)[name = tensor("transpose_143")]; tensor x2_26_cast_fp16 = matmul(transpose_x = x2_26_transpose_x_0, transpose_y = x2_26_transpose_y_0, x = input0_155_cast_fp16, y = value_28_cast_fp16)[name = tensor("x2_26_cast_fp16")]; tensor var_3004_perm_0 = const()[name = tensor("op_3004_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_3005 = const()[name = tensor("op_3005"), val = tensor([1, -1, 512])]; tensor var_3004_cast_fp16 = transpose(perm = var_3004_perm_0, x = x2_26_cast_fp16)[name = tensor("transpose_142")]; tensor input1_78_cast_fp16 = reshape(shape = var_3005, x = var_3004_cast_fp16)[name = tensor("input1_78_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(78987200))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79249408))), name = tensor("encoder_layers_12_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_78_cast_fp16)[name = tensor("linear_115_cast_fp16")]; tensor input0_157_cast_fp16 = add(x = input_157_cast_fp16, y = linear_115_cast_fp16)[name = tensor("input0_157_cast_fp16")]; tensor x_255_axes_0 = const()[name = tensor("x_255_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(79249984)))]; 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(79251072)))]; tensor x_255_cast_fp16 = layer_norm(axes = x_255_axes_0, beta = encoder_layers_12_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_12_norm_conv_weight_to_fp16, x = input0_157_cast_fp16)[name = tensor("x_255_cast_fp16")]; tensor input_161_perm_0 = const()[name = tensor("input_161_perm_0"), val = tensor([0, 2, 1])]; tensor input0_159_pad_type_0 = const()[name = tensor("input0_159_pad_type_0"), val = tensor("valid")]; tensor input0_159_strides_0 = const()[name = tensor("input0_159_strides_0"), val = tensor([1])]; tensor input0_159_pad_0 = const()[name = tensor("input0_159_pad_0"), val = tensor([0, 0])]; tensor input0_159_dilations_0 = const()[name = tensor("input0_159_dilations_0"), val = tensor([1])]; tensor input0_159_groups_0 = const()[name = tensor("input0_159_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(79252160))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79776512))), name = tensor("encoder_layers_12_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_161_cast_fp16 = transpose(perm = input_161_perm_0, x = x_255_cast_fp16)[name = tensor("transpose_141")]; tensor input0_159_cast_fp16 = conv(dilations = input0_159_dilations_0, groups = input0_159_groups_0, pad = input0_159_pad_0, pad_type = input0_159_pad_type_0, strides = input0_159_strides_0, weight = encoder_layers_12_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_161_cast_fp16)[name = tensor("input0_159_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_159_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_161_cast_fp16 = select(a = var_26_to_fp16, b = x_257_cast_fp16, cond = var_546)[name = tensor("input0_161_cast_fp16")]; tensor new_x0_26_interleave_0 = const()[name = tensor("new_x0_26_interleave_0"), val = tensor(false)]; tensor new_x0_26_cast_fp16 = concat(axis = var_47, interleave = new_x0_26_interleave_0, values = (cache24_1_cast_fp16, input0_161_cast_fp16))[name = tensor("new_x0_26_cast_fp16")]; tensor next_cache_26_begin_0 = const()[name = tensor("next_cache_26_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_26_end_0 = const()[name = tensor("next_cache_26_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_26_end_mask_0 = const()[name = tensor("next_cache_26_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_26_cast_fp16 = slice_by_index(begin = next_cache_26_begin_0, end = next_cache_26_end_0, end_mask = next_cache_26_end_mask_0, x = new_x0_26_cast_fp16)[name = tensor("next_cache_26_cast_fp16")]; tensor var_3046_begin_0 = const()[name = tensor("op_3046_begin_0"), val = tensor([0, 0, 4])]; tensor var_3046_end_0 = const()[name = tensor("op_3046_end_0"), val = tensor([1, 512, 12])]; tensor var_3046_end_mask_0 = const()[name = tensor("op_3046_end_mask_0"), val = tensor([true, true, true])]; tensor var_3046_cast_fp16 = slice_by_index(begin = var_3046_begin_0, end = var_3046_end_0, end_mask = var_3046_end_mask_0, x = next_cache_26_cast_fp16)[name = tensor("op_3046_cast_fp16")]; tensor x_259_pad_type_0 = const()[name = tensor("x_259_pad_type_0"), val = tensor("valid")]; tensor x_259_groups_0 = const()[name = tensor("x_259_groups_0"), val = tensor(512)]; 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 encoder_layers_12_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79777088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79781760))), name = tensor("encoder_layers_12_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; 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_12_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_26_cast_fp16)[name = tensor("x_259_cast_fp16")]; tensor input1_80_perm_0 = const()[name = tensor("input1_80_perm_0"), val = tensor([0, 2, 1])]; tensor x_261_axes_0 = const()[name = tensor("x_261_axes_0"), val = tensor([-1])]; tensor encoder_layers_12_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_12_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79782336)))]; tensor encoder_layers_12_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_12_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79783424)))]; tensor input1_80_cast_fp16 = transpose(perm = input1_80_perm_0, x = x_259_cast_fp16)[name = tensor("transpose_140")]; tensor x_261_cast_fp16 = layer_norm(axes = x_261_axes_0, beta = encoder_layers_12_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_12_conv_batch_norm_weight_to_fp16, x = input1_80_cast_fp16)[name = tensor("x_261_cast_fp16")]; tensor input2_52_perm_0 = const()[name = tensor("input2_52_perm_0"), val = tensor([0, 2, 1])]; tensor input2_52_cast_fp16 = transpose(perm = input2_52_perm_0, x = x_261_cast_fp16)[name = tensor("transpose_139")]; tensor var_3061_cast_fp16 = silu(x = input2_52_cast_fp16)[name = tensor("op_3061_cast_fp16")]; tensor x_263_pad_type_0 = const()[name = tensor("x_263_pad_type_0"), val = tensor("valid")]; tensor x_263_strides_0 = const()[name = tensor("x_263_strides_0"), val = tensor([1])]; tensor x_263_pad_0 = const()[name = tensor("x_263_pad_0"), val = tensor([0, 0])]; tensor x_263_dilations_0 = const()[name = tensor("x_263_dilations_0"), val = tensor([1])]; tensor x_263_groups_0 = const()[name = tensor("x_263_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(79784512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80046720))), name = tensor("encoder_layers_12_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_263_cast_fp16 = conv(dilations = x_263_dilations_0, groups = x_263_groups_0, pad = x_263_pad_0, pad_type = x_263_pad_type_0, strides = x_263_strides_0, weight = encoder_layers_12_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3061_cast_fp16)[name = tensor("x_263_cast_fp16")]; tensor input3_28_perm_0 = const()[name = tensor("input3_28_perm_0"), val = tensor([0, 2, 1])]; tensor input3_28_cast_fp16 = transpose(perm = input3_28_perm_0, x = x_263_cast_fp16)[name = tensor("transpose_138")]; tensor input1_82_cast_fp16 = add(x = input0_157_cast_fp16, y = input3_28_cast_fp16)[name = tensor("input1_82_cast_fp16")]; tensor input0_163_axes_0 = const()[name = tensor("input0_163_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(80047296)))]; 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(80048384)))]; tensor input0_163_cast_fp16 = layer_norm(axes = input0_163_axes_0, beta = encoder_layers_12_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_12_norm_feed_forward2_weight_to_fp16, x = input1_82_cast_fp16)[name = tensor("input0_163_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(80049472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(81098112))), name = tensor("encoder_layers_12_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_163_cast_fp16)[name = tensor("linear_116_cast_fp16")]; tensor var_3082_cast_fp16 = silu(x = linear_116_cast_fp16)[name = tensor("op_3082_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(81098688))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82147328))), name = tensor("encoder_layers_12_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3082_cast_fp16)[name = tensor("linear_117_cast_fp16")]; tensor var_3087_to_fp16 = const()[name = tensor("op_3087_to_fp16"), val = tensor(0x1p-1)]; tensor var_3088_cast_fp16 = mul(x = linear_117_cast_fp16, y = var_3087_to_fp16)[name = tensor("op_3088_cast_fp16")]; tensor input2_54_cast_fp16 = add(x = input1_82_cast_fp16, y = var_3088_cast_fp16)[name = tensor("input2_54_cast_fp16")]; tensor input0_165_axes_0 = const()[name = tensor("input0_165_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(82147904)))]; 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(82148992)))]; tensor input0_165_cast_fp16 = layer_norm(axes = input0_165_axes_0, beta = encoder_layers_12_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_12_norm_out_weight_to_fp16, x = input2_54_cast_fp16)[name = tensor("input0_165_cast_fp16")]; tensor cache25_1_begin_0 = const()[name = tensor("cache25_1_begin_0"), val = tensor([13, 0, 0, 0])]; tensor cache25_1_end_0 = const()[name = tensor("cache25_1_end_0"), val = tensor([14, 1, 70, 512])]; tensor cache25_1_end_mask_0 = const()[name = tensor("cache25_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache25_1_squeeze_mask_0 = const()[name = tensor("cache25_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache25_1_cast_fp16 = slice_by_index(begin = cache25_1_begin_0, end = cache25_1_end_0, end_mask = cache25_1_end_mask_0, squeeze_mask = cache25_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache25_1_cast_fp16")]; tensor cache26_1_begin_0 = const()[name = tensor("cache26_1_begin_0"), val = tensor([13, 0, 0, 0])]; tensor cache26_1_end_0 = const()[name = tensor("cache26_1_end_0"), val = tensor([14, 1, 512, 8])]; tensor cache26_1_end_mask_0 = const()[name = tensor("cache26_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache26_1_squeeze_mask_0 = const()[name = tensor("cache26_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache26_1_cast_fp16 = slice_by_index(begin = cache26_1_begin_0, end = cache26_1_end_0, end_mask = cache26_1_end_mask_0, squeeze_mask = cache26_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache26_1_cast_fp16")]; tensor input_165_axes_0 = const()[name = tensor("input_165_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(82150080)))]; 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(82151168)))]; tensor input_165_cast_fp16 = layer_norm(axes = input_165_axes_0, beta = encoder_layers_13_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_13_norm_feed_forward1_weight_to_fp16, x = input0_165_cast_fp16)[name = tensor("input_165_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(82152256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83200896))), name = tensor("encoder_layers_13_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_165_cast_fp16)[name = tensor("linear_118_cast_fp16")]; tensor var_3117_cast_fp16 = silu(x = linear_118_cast_fp16)[name = tensor("op_3117_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(83201472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84250112))), name = tensor("encoder_layers_13_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3117_cast_fp16)[name = tensor("linear_119_cast_fp16")]; tensor var_3122_to_fp16 = const()[name = tensor("op_3122_to_fp16"), val = tensor(0x1p-1)]; tensor var_3123_cast_fp16 = mul(x = linear_119_cast_fp16, y = var_3122_to_fp16)[name = tensor("op_3123_cast_fp16")]; tensor input_169_cast_fp16 = add(x = input0_165_cast_fp16, y = var_3123_cast_fp16)[name = tensor("input_169_cast_fp16")]; tensor key_28_axes_0 = const()[name = tensor("key_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(84250688)))]; 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(84251776)))]; tensor key_28_cast_fp16 = layer_norm(axes = key_28_axes_0, beta = encoder_layers_13_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_13_norm_self_att_weight_to_fp16, x = input_169_cast_fp16)[name = tensor("key_28_cast_fp16")]; tensor input_171_interleave_0 = const()[name = tensor("input_171_interleave_0"), val = tensor(false)]; tensor input_171_cast_fp16 = concat(axis = var_55, interleave = input_171_interleave_0, values = (cache25_1_cast_fp16, key_28_cast_fp16))[name = tensor("input_171_cast_fp16")]; tensor var_3145_begin_0 = const()[name = tensor("op_3145_begin_0"), val = tensor([0, 4, 0])]; tensor var_3145_end_0 = const()[name = tensor("op_3145_end_0"), val = tensor([1, 70, 512])]; tensor var_3145_end_mask_0 = const()[name = tensor("op_3145_end_mask_0"), val = tensor([true, true, true])]; tensor var_3145_cast_fp16 = slice_by_index(begin = var_3145_begin_0, end = var_3145_end_0, end_mask = var_3145_end_mask_0, x = cache25_1_cast_fp16)[name = tensor("op_3145_cast_fp16")]; tensor var_3148_begin_0 = const()[name = tensor("op_3148_begin_0"), val = tensor([0, 0, 0])]; tensor var_3148_end_0 = const()[name = tensor("op_3148_end_0"), val = tensor([1, 4, 512])]; tensor var_3148_end_mask_0 = const()[name = tensor("op_3148_end_mask_0"), val = tensor([true, false, true])]; tensor var_3148_cast_fp16 = slice_by_index(begin = var_3148_begin_0, end = var_3148_end_0, end_mask = var_3148_end_mask_0, x = key_28_cast_fp16)[name = tensor("op_3148_cast_fp16")]; tensor var_3151_interleave_0 = const()[name = tensor("op_3151_interleave_0"), val = tensor(false)]; tensor var_3151_cast_fp16 = concat(axis = var_55, interleave = var_3151_interleave_0, values = (var_3145_cast_fp16, var_3148_cast_fp16))[name = tensor("op_3151_cast_fp16")]; 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(84252864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84515072))), name = tensor("encoder_layers_13_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_28_cast_fp16)[name = tensor("linear_120_cast_fp16")]; tensor var_3155 = const()[name = tensor("op_3155"), val = tensor([1, -1, 8, 64])]; tensor q_28_cast_fp16 = reshape(shape = var_3155, 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(84515648))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84777856))), name = tensor("encoder_layers_13_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_171_cast_fp16)[name = tensor("linear_121_cast_fp16")]; tensor var_3159 = const()[name = tensor("op_3159"), val = tensor([1, -1, 8, 64])]; tensor k_28_cast_fp16 = reshape(shape = var_3159, 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(84778432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85040640))), name = tensor("encoder_layers_13_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_171_cast_fp16)[name = tensor("linear_122_cast_fp16")]; tensor var_3163 = const()[name = tensor("op_3163"), val = tensor([1, -1, 8, 64])]; tensor v_28_cast_fp16 = reshape(shape = var_3163, x = linear_122_cast_fp16)[name = tensor("v_28_cast_fp16")]; tensor value_30_perm_0 = const()[name = tensor("value_30_perm_0"), val = tensor([0, 2, -3, -1])]; 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(85041216)))]; tensor var_3175_cast_fp16 = add(x = q_28_cast_fp16, y = encoder_layers_13_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3175_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(85042304)))]; tensor var_3177_cast_fp16 = add(x = q_28_cast_fp16, y = encoder_layers_13_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3177_cast_fp16")]; tensor q_with_bias_v_28_perm_0 = const()[name = tensor("q_with_bias_v_28_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_271_transpose_x_0 = const()[name = tensor("x_271_transpose_x_0"), val = tensor(false)]; tensor x_271_transpose_y_0 = const()[name = tensor("x_271_transpose_y_0"), val = tensor(false)]; tensor op_3179_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85043392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85122816))), name = tensor("op_3179_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_28_cast_fp16 = transpose(perm = q_with_bias_v_28_perm_0, x = var_3177_cast_fp16)[name = tensor("transpose_137")]; tensor x_271_cast_fp16 = matmul(transpose_x = x_271_transpose_x_0, transpose_y = x_271_transpose_y_0, x = q_with_bias_v_28_cast_fp16, y = op_3179_to_fp16_palettized)[name = tensor("x_271_cast_fp16")]; 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_248_to_fp16 = const()[name = tensor("const_248_to_fp16"), val = tensor(0x0p+0)]; tensor x0_30_cast_fp16 = pad(constant_val = const_248_to_fp16, mode = x0_30_mode_0, pad = x0_30_pad_0, x = x_271_cast_fp16)[name = tensor("x0_30_cast_fp16")]; tensor var_3187 = const()[name = tensor("op_3187"), val = tensor([1, 8, -1, 8])]; tensor x1_28_cast_fp16 = reshape(shape = var_3187, x = x0_30_cast_fp16)[name = tensor("x1_28_cast_fp16")]; tensor var_3191_begin_0 = const()[name = tensor("op_3191_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3191_end_0 = const()[name = tensor("op_3191_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_3191_end_mask_0 = const()[name = tensor("op_3191_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3191_cast_fp16 = slice_by_index(begin = var_3191_begin_0, end = var_3191_end_0, end_mask = var_3191_end_mask_0, x = x1_28_cast_fp16)[name = tensor("op_3191_cast_fp16")]; tensor var_3192 = const()[name = tensor("op_3192"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_28_cast_fp16 = reshape(shape = var_3192, x = var_3191_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_94_perm_0 = const()[name = tensor("transpose_94_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_95_perm_0 = const()[name = tensor("transpose_95_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_95 = transpose(perm = transpose_95_perm_0, x = k_28_cast_fp16)[name = tensor("transpose_135")]; tensor transpose_94 = transpose(perm = transpose_94_perm_0, x = var_3175_cast_fp16)[name = tensor("transpose_136")]; 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_94, y = transpose_95)[name = tensor("matrix_ac_28_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_28_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_28_end_0, end_mask = matrix_bd0_28_end_mask_0, x = matrix_bd_28_cast_fp16)[name = tensor("matrix_bd0_28_cast_fp16")]; tensor var_3201_cast_fp16 = add(x = matrix_ac_28_cast_fp16, y = matrix_bd0_28_cast_fp16)[name = tensor("op_3201_cast_fp16")]; tensor _inversed_scores_28_y_0_to_fp16 = const()[name = tensor("_inversed_scores_28_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_28_cast_fp16 = mul(x = var_3201_cast_fp16, y = _inversed_scores_28_y_0_to_fp16)[name = tensor("_inversed_scores_28_cast_fp16")]; tensor scores0_28_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_28_cast_fp16, cond = mask0_4)[name = tensor("scores0_28_cast_fp16")]; tensor var_3207_cast_fp16 = softmax(axis = var_47, x = scores0_28_cast_fp16)[name = tensor("op_3207_cast_fp16")]; tensor input0_167_cast_fp16 = select(a = var_26_to_fp16, b = var_3207_cast_fp16, cond = mask0_4)[name = tensor("input0_167_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 value_30_cast_fp16 = transpose(perm = value_30_perm_0, x = v_28_cast_fp16)[name = tensor("transpose_134")]; tensor x2_28_cast_fp16 = matmul(transpose_x = x2_28_transpose_x_0, transpose_y = x2_28_transpose_y_0, x = input0_167_cast_fp16, y = value_30_cast_fp16)[name = tensor("x2_28_cast_fp16")]; tensor var_3211_perm_0 = const()[name = tensor("op_3211_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_3212 = const()[name = tensor("op_3212"), val = tensor([1, -1, 512])]; tensor var_3211_cast_fp16 = transpose(perm = var_3211_perm_0, x = x2_28_cast_fp16)[name = tensor("transpose_133")]; tensor input1_84_cast_fp16 = reshape(shape = var_3212, x = var_3211_cast_fp16)[name = tensor("input1_84_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(85123392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85385600))), name = tensor("encoder_layers_13_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_84_cast_fp16)[name = tensor("linear_124_cast_fp16")]; tensor input0_169_cast_fp16 = add(x = input_169_cast_fp16, y = linear_124_cast_fp16)[name = tensor("input0_169_cast_fp16")]; tensor x_275_axes_0 = const()[name = tensor("x_275_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(85386176)))]; 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(85387264)))]; tensor x_275_cast_fp16 = layer_norm(axes = x_275_axes_0, beta = encoder_layers_13_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_13_norm_conv_weight_to_fp16, x = input0_169_cast_fp16)[name = tensor("x_275_cast_fp16")]; tensor input_173_perm_0 = const()[name = tensor("input_173_perm_0"), val = tensor([0, 2, 1])]; tensor input0_171_pad_type_0 = const()[name = tensor("input0_171_pad_type_0"), val = tensor("valid")]; tensor input0_171_strides_0 = const()[name = tensor("input0_171_strides_0"), val = tensor([1])]; tensor input0_171_pad_0 = const()[name = tensor("input0_171_pad_0"), val = tensor([0, 0])]; tensor input0_171_dilations_0 = const()[name = tensor("input0_171_dilations_0"), val = tensor([1])]; tensor input0_171_groups_0 = const()[name = tensor("input0_171_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(85388352))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85912704))), name = tensor("encoder_layers_13_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_173_cast_fp16 = transpose(perm = input_173_perm_0, x = x_275_cast_fp16)[name = tensor("transpose_132")]; tensor input0_171_cast_fp16 = conv(dilations = input0_171_dilations_0, groups = input0_171_groups_0, pad = input0_171_pad_0, pad_type = input0_171_pad_type_0, strides = input0_171_strides_0, weight = encoder_layers_13_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_173_cast_fp16)[name = tensor("input0_171_cast_fp16")]; tensor x_277_split_num_splits_0 = const()[name = tensor("x_277_split_num_splits_0"), val = tensor(2)]; tensor x_277_split_axis_0 = const()[name = tensor("x_277_split_axis_0"), val = tensor(1)]; tensor x_277_split_cast_fp16_0, tensor x_277_split_cast_fp16_1 = split(axis = x_277_split_axis_0, num_splits = x_277_split_num_splits_0, x = input0_171_cast_fp16)[name = tensor("x_277_split_cast_fp16")]; tensor x_277_split_1_sigmoid_cast_fp16 = sigmoid(x = x_277_split_cast_fp16_1)[name = tensor("x_277_split_1_sigmoid_cast_fp16")]; tensor x_277_cast_fp16 = mul(x = x_277_split_cast_fp16_0, y = x_277_split_1_sigmoid_cast_fp16)[name = tensor("x_277_cast_fp16")]; tensor input0_173_cast_fp16 = select(a = var_26_to_fp16, b = x_277_cast_fp16, cond = var_546)[name = tensor("input0_173_cast_fp16")]; tensor new_x0_28_interleave_0 = const()[name = tensor("new_x0_28_interleave_0"), val = tensor(false)]; tensor new_x0_28_cast_fp16 = concat(axis = var_47, interleave = new_x0_28_interleave_0, values = (cache26_1_cast_fp16, input0_173_cast_fp16))[name = tensor("new_x0_28_cast_fp16")]; tensor next_cache_28_begin_0 = const()[name = tensor("next_cache_28_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_28_end_0 = const()[name = tensor("next_cache_28_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_28_end_mask_0 = const()[name = tensor("next_cache_28_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_28_cast_fp16 = slice_by_index(begin = next_cache_28_begin_0, end = next_cache_28_end_0, end_mask = next_cache_28_end_mask_0, x = new_x0_28_cast_fp16)[name = tensor("next_cache_28_cast_fp16")]; tensor var_3253_begin_0 = const()[name = tensor("op_3253_begin_0"), val = tensor([0, 0, 4])]; tensor var_3253_end_0 = const()[name = tensor("op_3253_end_0"), val = tensor([1, 512, 12])]; tensor var_3253_end_mask_0 = const()[name = tensor("op_3253_end_mask_0"), val = tensor([true, true, true])]; tensor var_3253_cast_fp16 = slice_by_index(begin = var_3253_begin_0, end = var_3253_end_0, end_mask = var_3253_end_mask_0, x = next_cache_28_cast_fp16)[name = tensor("op_3253_cast_fp16")]; tensor x_279_pad_type_0 = const()[name = tensor("x_279_pad_type_0"), val = tensor("valid")]; tensor x_279_groups_0 = const()[name = tensor("x_279_groups_0"), val = tensor(512)]; tensor x_279_strides_0 = const()[name = tensor("x_279_strides_0"), val = tensor([1])]; tensor x_279_pad_0 = const()[name = tensor("x_279_pad_0"), val = tensor([0, 0])]; tensor x_279_dilations_0 = const()[name = tensor("x_279_dilations_0"), val = tensor([1])]; tensor encoder_layers_13_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85913280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85917952))), name = tensor("encoder_layers_13_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_279_cast_fp16 = conv(dilations = x_279_dilations_0, groups = x_279_groups_0, pad = x_279_pad_0, pad_type = x_279_pad_type_0, strides = x_279_strides_0, weight = encoder_layers_13_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_28_cast_fp16)[name = tensor("x_279_cast_fp16")]; tensor input1_86_perm_0 = const()[name = tensor("input1_86_perm_0"), val = tensor([0, 2, 1])]; tensor x_281_axes_0 = const()[name = tensor("x_281_axes_0"), val = tensor([-1])]; tensor encoder_layers_13_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_13_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85918528)))]; tensor encoder_layers_13_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_13_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85919616)))]; tensor input1_86_cast_fp16 = transpose(perm = input1_86_perm_0, x = x_279_cast_fp16)[name = tensor("transpose_131")]; tensor x_281_cast_fp16 = layer_norm(axes = x_281_axes_0, beta = encoder_layers_13_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_13_conv_batch_norm_weight_to_fp16, x = input1_86_cast_fp16)[name = tensor("x_281_cast_fp16")]; tensor input2_56_perm_0 = const()[name = tensor("input2_56_perm_0"), val = tensor([0, 2, 1])]; tensor input2_56_cast_fp16 = transpose(perm = input2_56_perm_0, x = x_281_cast_fp16)[name = tensor("transpose_130")]; tensor var_3268_cast_fp16 = silu(x = input2_56_cast_fp16)[name = tensor("op_3268_cast_fp16")]; tensor x_283_pad_type_0 = const()[name = tensor("x_283_pad_type_0"), val = tensor("valid")]; tensor x_283_strides_0 = const()[name = tensor("x_283_strides_0"), val = tensor([1])]; tensor x_283_pad_0 = const()[name = tensor("x_283_pad_0"), val = tensor([0, 0])]; tensor x_283_dilations_0 = const()[name = tensor("x_283_dilations_0"), val = tensor([1])]; tensor x_283_groups_0 = const()[name = tensor("x_283_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(85920704))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86182912))), name = tensor("encoder_layers_13_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_283_cast_fp16 = conv(dilations = x_283_dilations_0, groups = x_283_groups_0, pad = x_283_pad_0, pad_type = x_283_pad_type_0, strides = x_283_strides_0, weight = encoder_layers_13_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3268_cast_fp16)[name = tensor("x_283_cast_fp16")]; tensor input3_30_perm_0 = const()[name = tensor("input3_30_perm_0"), val = tensor([0, 2, 1])]; tensor input3_30_cast_fp16 = transpose(perm = input3_30_perm_0, x = x_283_cast_fp16)[name = tensor("transpose_129")]; tensor input1_88_cast_fp16 = add(x = input0_169_cast_fp16, y = input3_30_cast_fp16)[name = tensor("input1_88_cast_fp16")]; tensor input0_175_axes_0 = const()[name = tensor("input0_175_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(86183488)))]; 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(86184576)))]; tensor input0_175_cast_fp16 = layer_norm(axes = input0_175_axes_0, beta = encoder_layers_13_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_13_norm_feed_forward2_weight_to_fp16, x = input1_88_cast_fp16)[name = tensor("input0_175_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(86185664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(87234304))), name = tensor("encoder_layers_13_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_175_cast_fp16)[name = tensor("linear_125_cast_fp16")]; tensor var_3289_cast_fp16 = silu(x = linear_125_cast_fp16)[name = tensor("op_3289_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(87234880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88283520))), name = tensor("encoder_layers_13_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3289_cast_fp16)[name = tensor("linear_126_cast_fp16")]; tensor var_3294_to_fp16 = const()[name = tensor("op_3294_to_fp16"), val = tensor(0x1p-1)]; tensor var_3295_cast_fp16 = mul(x = linear_126_cast_fp16, y = var_3294_to_fp16)[name = tensor("op_3295_cast_fp16")]; tensor input2_58_cast_fp16 = add(x = input1_88_cast_fp16, y = var_3295_cast_fp16)[name = tensor("input2_58_cast_fp16")]; tensor input0_177_axes_0 = const()[name = tensor("input0_177_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(88284096)))]; 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(88285184)))]; tensor input0_177_cast_fp16 = layer_norm(axes = input0_177_axes_0, beta = encoder_layers_13_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_13_norm_out_weight_to_fp16, x = input2_58_cast_fp16)[name = tensor("input0_177_cast_fp16")]; tensor cache27_1_begin_0 = const()[name = tensor("cache27_1_begin_0"), val = tensor([14, 0, 0, 0])]; tensor cache27_1_end_0 = const()[name = tensor("cache27_1_end_0"), val = tensor([15, 1, 70, 512])]; tensor cache27_1_end_mask_0 = const()[name = tensor("cache27_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache27_1_squeeze_mask_0 = const()[name = tensor("cache27_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache27_1_cast_fp16 = slice_by_index(begin = cache27_1_begin_0, end = cache27_1_end_0, end_mask = cache27_1_end_mask_0, squeeze_mask = cache27_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache27_1_cast_fp16")]; tensor cache28_1_begin_0 = const()[name = tensor("cache28_1_begin_0"), val = tensor([14, 0, 0, 0])]; tensor cache28_1_end_0 = const()[name = tensor("cache28_1_end_0"), val = tensor([15, 1, 512, 8])]; tensor cache28_1_end_mask_0 = const()[name = tensor("cache28_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache28_1_squeeze_mask_0 = const()[name = tensor("cache28_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache28_1_cast_fp16 = slice_by_index(begin = cache28_1_begin_0, end = cache28_1_end_0, end_mask = cache28_1_end_mask_0, squeeze_mask = cache28_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache28_1_cast_fp16")]; tensor input_177_axes_0 = const()[name = tensor("input_177_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(88286272)))]; 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(88287360)))]; tensor input_177_cast_fp16 = layer_norm(axes = input_177_axes_0, beta = encoder_layers_14_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_14_norm_feed_forward1_weight_to_fp16, x = input0_177_cast_fp16)[name = tensor("input_177_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(88288448))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89337088))), name = tensor("encoder_layers_14_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_177_cast_fp16)[name = tensor("linear_127_cast_fp16")]; tensor var_3324_cast_fp16 = silu(x = linear_127_cast_fp16)[name = tensor("op_3324_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(89337664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90386304))), name = tensor("encoder_layers_14_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3324_cast_fp16)[name = tensor("linear_128_cast_fp16")]; tensor var_3329_to_fp16 = const()[name = tensor("op_3329_to_fp16"), val = tensor(0x1p-1)]; tensor var_3330_cast_fp16 = mul(x = linear_128_cast_fp16, y = var_3329_to_fp16)[name = tensor("op_3330_cast_fp16")]; tensor input_181_cast_fp16 = add(x = input0_177_cast_fp16, y = var_3330_cast_fp16)[name = tensor("input_181_cast_fp16")]; tensor key_30_axes_0 = const()[name = tensor("key_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(90386880)))]; 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(90387968)))]; tensor key_30_cast_fp16 = layer_norm(axes = key_30_axes_0, beta = encoder_layers_14_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_14_norm_self_att_weight_to_fp16, x = input_181_cast_fp16)[name = tensor("key_30_cast_fp16")]; tensor input_183_interleave_0 = const()[name = tensor("input_183_interleave_0"), val = tensor(false)]; tensor input_183_cast_fp16 = concat(axis = var_55, interleave = input_183_interleave_0, values = (cache27_1_cast_fp16, key_30_cast_fp16))[name = tensor("input_183_cast_fp16")]; tensor var_3352_begin_0 = const()[name = tensor("op_3352_begin_0"), val = tensor([0, 4, 0])]; tensor var_3352_end_0 = const()[name = tensor("op_3352_end_0"), val = tensor([1, 70, 512])]; tensor var_3352_end_mask_0 = const()[name = tensor("op_3352_end_mask_0"), val = tensor([true, true, true])]; tensor var_3352_cast_fp16 = slice_by_index(begin = var_3352_begin_0, end = var_3352_end_0, end_mask = var_3352_end_mask_0, x = cache27_1_cast_fp16)[name = tensor("op_3352_cast_fp16")]; tensor var_3355_begin_0 = const()[name = tensor("op_3355_begin_0"), val = tensor([0, 0, 0])]; tensor var_3355_end_0 = const()[name = tensor("op_3355_end_0"), val = tensor([1, 4, 512])]; tensor var_3355_end_mask_0 = const()[name = tensor("op_3355_end_mask_0"), val = tensor([true, false, true])]; tensor var_3355_cast_fp16 = slice_by_index(begin = var_3355_begin_0, end = var_3355_end_0, end_mask = var_3355_end_mask_0, x = key_30_cast_fp16)[name = tensor("op_3355_cast_fp16")]; tensor var_3358_interleave_0 = const()[name = tensor("op_3358_interleave_0"), val = tensor(false)]; tensor var_3358_cast_fp16 = concat(axis = var_55, interleave = var_3358_interleave_0, values = (var_3352_cast_fp16, var_3355_cast_fp16))[name = tensor("op_3358_cast_fp16")]; 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(90389056))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90651264))), name = tensor("encoder_layers_14_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_30_cast_fp16)[name = tensor("linear_129_cast_fp16")]; tensor var_3362 = const()[name = tensor("op_3362"), val = tensor([1, -1, 8, 64])]; tensor q_30_cast_fp16 = reshape(shape = var_3362, 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(90651840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90914048))), name = tensor("encoder_layers_14_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_183_cast_fp16)[name = tensor("linear_130_cast_fp16")]; tensor var_3366 = const()[name = tensor("op_3366"), val = tensor([1, -1, 8, 64])]; tensor k_30_cast_fp16 = reshape(shape = var_3366, 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(90914624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91176832))), name = tensor("encoder_layers_14_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_183_cast_fp16)[name = tensor("linear_131_cast_fp16")]; tensor var_3370 = const()[name = tensor("op_3370"), val = tensor([1, -1, 8, 64])]; tensor v_30_cast_fp16 = reshape(shape = var_3370, x = linear_131_cast_fp16)[name = tensor("v_30_cast_fp16")]; tensor value_32_perm_0 = const()[name = tensor("value_32_perm_0"), val = tensor([0, 2, -3, -1])]; 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(91177408)))]; tensor var_3382_cast_fp16 = add(x = q_30_cast_fp16, y = encoder_layers_14_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3382_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(91178496)))]; tensor var_3384_cast_fp16 = add(x = q_30_cast_fp16, y = encoder_layers_14_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3384_cast_fp16")]; tensor q_with_bias_v_30_perm_0 = const()[name = tensor("q_with_bias_v_30_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_291_transpose_x_0 = const()[name = tensor("x_291_transpose_x_0"), val = tensor(false)]; tensor x_291_transpose_y_0 = const()[name = tensor("x_291_transpose_y_0"), val = tensor(false)]; tensor op_3386_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91179584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91259008))), name = tensor("op_3386_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_30_cast_fp16 = transpose(perm = q_with_bias_v_30_perm_0, x = var_3384_cast_fp16)[name = tensor("transpose_128")]; tensor x_291_cast_fp16 = matmul(transpose_x = x_291_transpose_x_0, transpose_y = x_291_transpose_y_0, x = q_with_bias_v_30_cast_fp16, y = op_3386_to_fp16_palettized)[name = tensor("x_291_cast_fp16")]; 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_261_to_fp16 = const()[name = tensor("const_261_to_fp16"), val = tensor(0x0p+0)]; tensor x0_32_cast_fp16 = pad(constant_val = const_261_to_fp16, mode = x0_32_mode_0, pad = x0_32_pad_0, x = x_291_cast_fp16)[name = tensor("x0_32_cast_fp16")]; tensor var_3394 = const()[name = tensor("op_3394"), val = tensor([1, 8, -1, 8])]; tensor x1_30_cast_fp16 = reshape(shape = var_3394, x = x0_32_cast_fp16)[name = tensor("x1_30_cast_fp16")]; tensor var_3398_begin_0 = const()[name = tensor("op_3398_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3398_end_0 = const()[name = tensor("op_3398_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_3398_end_mask_0 = const()[name = tensor("op_3398_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3398_cast_fp16 = slice_by_index(begin = var_3398_begin_0, end = var_3398_end_0, end_mask = var_3398_end_mask_0, x = x1_30_cast_fp16)[name = tensor("op_3398_cast_fp16")]; tensor var_3399 = const()[name = tensor("op_3399"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_30_cast_fp16 = reshape(shape = var_3399, x = var_3398_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_96_perm_0 = const()[name = tensor("transpose_96_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_97_perm_0 = const()[name = tensor("transpose_97_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_97 = transpose(perm = transpose_97_perm_0, x = k_30_cast_fp16)[name = tensor("transpose_126")]; tensor transpose_96 = transpose(perm = transpose_96_perm_0, x = var_3382_cast_fp16)[name = tensor("transpose_127")]; 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_96, y = transpose_97)[name = tensor("matrix_ac_30_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_30_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_30_end_0, end_mask = matrix_bd0_30_end_mask_0, x = matrix_bd_30_cast_fp16)[name = tensor("matrix_bd0_30_cast_fp16")]; tensor var_3408_cast_fp16 = add(x = matrix_ac_30_cast_fp16, y = matrix_bd0_30_cast_fp16)[name = tensor("op_3408_cast_fp16")]; tensor _inversed_scores_30_y_0_to_fp16 = const()[name = tensor("_inversed_scores_30_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_30_cast_fp16 = mul(x = var_3408_cast_fp16, y = _inversed_scores_30_y_0_to_fp16)[name = tensor("_inversed_scores_30_cast_fp16")]; tensor scores0_30_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_30_cast_fp16, cond = mask0_4)[name = tensor("scores0_30_cast_fp16")]; tensor var_3414_cast_fp16 = softmax(axis = var_47, x = scores0_30_cast_fp16)[name = tensor("op_3414_cast_fp16")]; tensor input0_179_cast_fp16 = select(a = var_26_to_fp16, b = var_3414_cast_fp16, cond = mask0_4)[name = tensor("input0_179_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 value_32_cast_fp16 = transpose(perm = value_32_perm_0, x = v_30_cast_fp16)[name = tensor("transpose_125")]; tensor x2_30_cast_fp16 = matmul(transpose_x = x2_30_transpose_x_0, transpose_y = x2_30_transpose_y_0, x = input0_179_cast_fp16, y = value_32_cast_fp16)[name = tensor("x2_30_cast_fp16")]; tensor var_3418_perm_0 = const()[name = tensor("op_3418_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_3419 = const()[name = tensor("op_3419"), val = tensor([1, -1, 512])]; tensor var_3418_cast_fp16 = transpose(perm = var_3418_perm_0, x = x2_30_cast_fp16)[name = tensor("transpose_124")]; tensor input1_90_cast_fp16 = reshape(shape = var_3419, x = var_3418_cast_fp16)[name = tensor("input1_90_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(91259584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91521792))), name = tensor("encoder_layers_14_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_90_cast_fp16)[name = tensor("linear_133_cast_fp16")]; tensor input0_181_cast_fp16 = add(x = input_181_cast_fp16, y = linear_133_cast_fp16)[name = tensor("input0_181_cast_fp16")]; tensor x_295_axes_0 = const()[name = tensor("x_295_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(91522368)))]; 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(91523456)))]; tensor x_295_cast_fp16 = layer_norm(axes = x_295_axes_0, beta = encoder_layers_14_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_14_norm_conv_weight_to_fp16, x = input0_181_cast_fp16)[name = tensor("x_295_cast_fp16")]; tensor input_185_perm_0 = const()[name = tensor("input_185_perm_0"), val = tensor([0, 2, 1])]; tensor input0_183_pad_type_0 = const()[name = tensor("input0_183_pad_type_0"), val = tensor("valid")]; tensor input0_183_strides_0 = const()[name = tensor("input0_183_strides_0"), val = tensor([1])]; tensor input0_183_pad_0 = const()[name = tensor("input0_183_pad_0"), val = tensor([0, 0])]; tensor input0_183_dilations_0 = const()[name = tensor("input0_183_dilations_0"), val = tensor([1])]; tensor input0_183_groups_0 = const()[name = tensor("input0_183_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(91524544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92048896))), name = tensor("encoder_layers_14_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_185_cast_fp16 = transpose(perm = input_185_perm_0, x = x_295_cast_fp16)[name = tensor("transpose_123")]; tensor input0_183_cast_fp16 = conv(dilations = input0_183_dilations_0, groups = input0_183_groups_0, pad = input0_183_pad_0, pad_type = input0_183_pad_type_0, strides = input0_183_strides_0, weight = encoder_layers_14_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_185_cast_fp16)[name = tensor("input0_183_cast_fp16")]; tensor x_297_split_num_splits_0 = const()[name = tensor("x_297_split_num_splits_0"), val = tensor(2)]; tensor x_297_split_axis_0 = const()[name = tensor("x_297_split_axis_0"), val = tensor(1)]; tensor x_297_split_cast_fp16_0, tensor x_297_split_cast_fp16_1 = split(axis = x_297_split_axis_0, num_splits = x_297_split_num_splits_0, x = input0_183_cast_fp16)[name = tensor("x_297_split_cast_fp16")]; tensor x_297_split_1_sigmoid_cast_fp16 = sigmoid(x = x_297_split_cast_fp16_1)[name = tensor("x_297_split_1_sigmoid_cast_fp16")]; tensor x_297_cast_fp16 = mul(x = x_297_split_cast_fp16_0, y = x_297_split_1_sigmoid_cast_fp16)[name = tensor("x_297_cast_fp16")]; tensor input0_185_cast_fp16 = select(a = var_26_to_fp16, b = x_297_cast_fp16, cond = var_546)[name = tensor("input0_185_cast_fp16")]; tensor new_x0_30_interleave_0 = const()[name = tensor("new_x0_30_interleave_0"), val = tensor(false)]; tensor new_x0_30_cast_fp16 = concat(axis = var_47, interleave = new_x0_30_interleave_0, values = (cache28_1_cast_fp16, input0_185_cast_fp16))[name = tensor("new_x0_30_cast_fp16")]; tensor next_cache_30_begin_0 = const()[name = tensor("next_cache_30_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_30_end_0 = const()[name = tensor("next_cache_30_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_30_end_mask_0 = const()[name = tensor("next_cache_30_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_30_cast_fp16 = slice_by_index(begin = next_cache_30_begin_0, end = next_cache_30_end_0, end_mask = next_cache_30_end_mask_0, x = new_x0_30_cast_fp16)[name = tensor("next_cache_30_cast_fp16")]; tensor var_3460_begin_0 = const()[name = tensor("op_3460_begin_0"), val = tensor([0, 0, 4])]; tensor var_3460_end_0 = const()[name = tensor("op_3460_end_0"), val = tensor([1, 512, 12])]; tensor var_3460_end_mask_0 = const()[name = tensor("op_3460_end_mask_0"), val = tensor([true, true, true])]; tensor var_3460_cast_fp16 = slice_by_index(begin = var_3460_begin_0, end = var_3460_end_0, end_mask = var_3460_end_mask_0, x = next_cache_30_cast_fp16)[name = tensor("op_3460_cast_fp16")]; tensor x_299_pad_type_0 = const()[name = tensor("x_299_pad_type_0"), val = tensor("valid")]; tensor x_299_groups_0 = const()[name = tensor("x_299_groups_0"), val = tensor(512)]; tensor x_299_strides_0 = const()[name = tensor("x_299_strides_0"), val = tensor([1])]; tensor x_299_pad_0 = const()[name = tensor("x_299_pad_0"), val = tensor([0, 0])]; tensor x_299_dilations_0 = const()[name = tensor("x_299_dilations_0"), val = tensor([1])]; tensor encoder_layers_14_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92049472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92054144))), name = tensor("encoder_layers_14_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_299_cast_fp16 = conv(dilations = x_299_dilations_0, groups = x_299_groups_0, pad = x_299_pad_0, pad_type = x_299_pad_type_0, strides = x_299_strides_0, weight = encoder_layers_14_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_30_cast_fp16)[name = tensor("x_299_cast_fp16")]; tensor input1_92_perm_0 = const()[name = tensor("input1_92_perm_0"), val = tensor([0, 2, 1])]; tensor x_301_axes_0 = const()[name = tensor("x_301_axes_0"), val = tensor([-1])]; tensor encoder_layers_14_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_14_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92054720)))]; tensor encoder_layers_14_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_14_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92055808)))]; tensor input1_92_cast_fp16 = transpose(perm = input1_92_perm_0, x = x_299_cast_fp16)[name = tensor("transpose_122")]; tensor x_301_cast_fp16 = layer_norm(axes = x_301_axes_0, beta = encoder_layers_14_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_14_conv_batch_norm_weight_to_fp16, x = input1_92_cast_fp16)[name = tensor("x_301_cast_fp16")]; tensor input2_60_perm_0 = const()[name = tensor("input2_60_perm_0"), val = tensor([0, 2, 1])]; tensor input2_60_cast_fp16 = transpose(perm = input2_60_perm_0, x = x_301_cast_fp16)[name = tensor("transpose_121")]; tensor var_3475_cast_fp16 = silu(x = input2_60_cast_fp16)[name = tensor("op_3475_cast_fp16")]; tensor x_303_pad_type_0 = const()[name = tensor("x_303_pad_type_0"), val = tensor("valid")]; tensor x_303_strides_0 = const()[name = tensor("x_303_strides_0"), val = tensor([1])]; tensor x_303_pad_0 = const()[name = tensor("x_303_pad_0"), val = tensor([0, 0])]; tensor x_303_dilations_0 = const()[name = tensor("x_303_dilations_0"), val = tensor([1])]; tensor x_303_groups_0 = const()[name = tensor("x_303_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(92056896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(92319104))), name = tensor("encoder_layers_14_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_303_cast_fp16 = conv(dilations = x_303_dilations_0, groups = x_303_groups_0, pad = x_303_pad_0, pad_type = x_303_pad_type_0, strides = x_303_strides_0, weight = encoder_layers_14_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3475_cast_fp16)[name = tensor("x_303_cast_fp16")]; tensor input3_32_perm_0 = const()[name = tensor("input3_32_perm_0"), val = tensor([0, 2, 1])]; tensor input3_32_cast_fp16 = transpose(perm = input3_32_perm_0, x = x_303_cast_fp16)[name = tensor("transpose_120")]; tensor input1_94_cast_fp16 = add(x = input0_181_cast_fp16, y = input3_32_cast_fp16)[name = tensor("input1_94_cast_fp16")]; tensor input0_187_axes_0 = const()[name = tensor("input0_187_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(92319680)))]; 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(92320768)))]; tensor input0_187_cast_fp16 = layer_norm(axes = input0_187_axes_0, beta = encoder_layers_14_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_14_norm_feed_forward2_weight_to_fp16, x = input1_94_cast_fp16)[name = tensor("input0_187_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(92321856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93370496))), name = tensor("encoder_layers_14_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_187_cast_fp16)[name = tensor("linear_134_cast_fp16")]; tensor var_3496_cast_fp16 = silu(x = linear_134_cast_fp16)[name = tensor("op_3496_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(93371072))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94419712))), name = tensor("encoder_layers_14_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3496_cast_fp16)[name = tensor("linear_135_cast_fp16")]; tensor var_3501_to_fp16 = const()[name = tensor("op_3501_to_fp16"), val = tensor(0x1p-1)]; tensor var_3502_cast_fp16 = mul(x = linear_135_cast_fp16, y = var_3501_to_fp16)[name = tensor("op_3502_cast_fp16")]; tensor input2_62_cast_fp16 = add(x = input1_94_cast_fp16, y = var_3502_cast_fp16)[name = tensor("input2_62_cast_fp16")]; tensor input0_189_axes_0 = const()[name = tensor("input0_189_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(94420288)))]; 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(94421376)))]; tensor input0_189_cast_fp16 = layer_norm(axes = input0_189_axes_0, beta = encoder_layers_14_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_14_norm_out_weight_to_fp16, x = input2_62_cast_fp16)[name = tensor("input0_189_cast_fp16")]; tensor cache29_1_begin_0 = const()[name = tensor("cache29_1_begin_0"), val = tensor([15, 0, 0, 0])]; tensor cache29_1_end_0 = const()[name = tensor("cache29_1_end_0"), val = tensor([16, 1, 70, 512])]; tensor cache29_1_end_mask_0 = const()[name = tensor("cache29_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache29_1_squeeze_mask_0 = const()[name = tensor("cache29_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache29_1_cast_fp16 = slice_by_index(begin = cache29_1_begin_0, end = cache29_1_end_0, end_mask = cache29_1_end_mask_0, squeeze_mask = cache29_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache29_1_cast_fp16")]; tensor cache30_1_begin_0 = const()[name = tensor("cache30_1_begin_0"), val = tensor([15, 0, 0, 0])]; tensor cache30_1_end_0 = const()[name = tensor("cache30_1_end_0"), val = tensor([16, 1, 512, 8])]; tensor cache30_1_end_mask_0 = const()[name = tensor("cache30_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache30_1_squeeze_mask_0 = const()[name = tensor("cache30_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache30_1_cast_fp16 = slice_by_index(begin = cache30_1_begin_0, end = cache30_1_end_0, end_mask = cache30_1_end_mask_0, squeeze_mask = cache30_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache30_1_cast_fp16")]; tensor input_189_axes_0 = const()[name = tensor("input_189_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(94422464)))]; 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(94423552)))]; tensor input_189_cast_fp16 = layer_norm(axes = input_189_axes_0, beta = encoder_layers_15_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_15_norm_feed_forward1_weight_to_fp16, x = input0_189_cast_fp16)[name = tensor("input_189_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(94424640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(95473280))), name = tensor("encoder_layers_15_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_189_cast_fp16)[name = tensor("linear_136_cast_fp16")]; tensor var_3531_cast_fp16 = silu(x = linear_136_cast_fp16)[name = tensor("op_3531_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(95473856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96522496))), name = tensor("encoder_layers_15_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3531_cast_fp16)[name = tensor("linear_137_cast_fp16")]; tensor var_3536_to_fp16 = const()[name = tensor("op_3536_to_fp16"), val = tensor(0x1p-1)]; tensor var_3537_cast_fp16 = mul(x = linear_137_cast_fp16, y = var_3536_to_fp16)[name = tensor("op_3537_cast_fp16")]; tensor input_193_cast_fp16 = add(x = input0_189_cast_fp16, y = var_3537_cast_fp16)[name = tensor("input_193_cast_fp16")]; tensor key_32_axes_0 = const()[name = tensor("key_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(96523072)))]; 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(96524160)))]; tensor key_32_cast_fp16 = layer_norm(axes = key_32_axes_0, beta = encoder_layers_15_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_15_norm_self_att_weight_to_fp16, x = input_193_cast_fp16)[name = tensor("key_32_cast_fp16")]; tensor input_195_interleave_0 = const()[name = tensor("input_195_interleave_0"), val = tensor(false)]; tensor input_195_cast_fp16 = concat(axis = var_55, interleave = input_195_interleave_0, values = (cache29_1_cast_fp16, key_32_cast_fp16))[name = tensor("input_195_cast_fp16")]; tensor var_3559_begin_0 = const()[name = tensor("op_3559_begin_0"), val = tensor([0, 4, 0])]; tensor var_3559_end_0 = const()[name = tensor("op_3559_end_0"), val = tensor([1, 70, 512])]; tensor var_3559_end_mask_0 = const()[name = tensor("op_3559_end_mask_0"), val = tensor([true, true, true])]; tensor var_3559_cast_fp16 = slice_by_index(begin = var_3559_begin_0, end = var_3559_end_0, end_mask = var_3559_end_mask_0, x = cache29_1_cast_fp16)[name = tensor("op_3559_cast_fp16")]; tensor var_3562_begin_0 = const()[name = tensor("op_3562_begin_0"), val = tensor([0, 0, 0])]; tensor var_3562_end_0 = const()[name = tensor("op_3562_end_0"), val = tensor([1, 4, 512])]; tensor var_3562_end_mask_0 = const()[name = tensor("op_3562_end_mask_0"), val = tensor([true, false, true])]; tensor var_3562_cast_fp16 = slice_by_index(begin = var_3562_begin_0, end = var_3562_end_0, end_mask = var_3562_end_mask_0, x = key_32_cast_fp16)[name = tensor("op_3562_cast_fp16")]; tensor var_3565_interleave_0 = const()[name = tensor("op_3565_interleave_0"), val = tensor(false)]; tensor var_3565_cast_fp16 = concat(axis = var_55, interleave = var_3565_interleave_0, values = (var_3559_cast_fp16, var_3562_cast_fp16))[name = tensor("op_3565_cast_fp16")]; 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(96525248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(96787456))), name = tensor("encoder_layers_15_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_32_cast_fp16)[name = tensor("linear_138_cast_fp16")]; tensor var_3569 = const()[name = tensor("op_3569"), val = tensor([1, -1, 8, 64])]; tensor q_32_cast_fp16 = reshape(shape = var_3569, 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(96788032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97050240))), name = tensor("encoder_layers_15_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_195_cast_fp16)[name = tensor("linear_139_cast_fp16")]; tensor var_3573 = const()[name = tensor("op_3573"), val = tensor([1, -1, 8, 64])]; tensor k_32_cast_fp16 = reshape(shape = var_3573, 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(97050816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97313024))), name = tensor("encoder_layers_15_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_195_cast_fp16)[name = tensor("linear_140_cast_fp16")]; tensor var_3577 = const()[name = tensor("op_3577"), val = tensor([1, -1, 8, 64])]; tensor v_32_cast_fp16 = reshape(shape = var_3577, x = linear_140_cast_fp16)[name = tensor("v_32_cast_fp16")]; tensor value_34_perm_0 = const()[name = tensor("value_34_perm_0"), val = tensor([0, 2, -3, -1])]; 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(97313600)))]; tensor var_3589_cast_fp16 = add(x = q_32_cast_fp16, y = encoder_layers_15_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3589_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(97314688)))]; tensor var_3591_cast_fp16 = add(x = q_32_cast_fp16, y = encoder_layers_15_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3591_cast_fp16")]; tensor q_with_bias_v_32_perm_0 = const()[name = tensor("q_with_bias_v_32_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_311_transpose_x_0 = const()[name = tensor("x_311_transpose_x_0"), val = tensor(false)]; tensor x_311_transpose_y_0 = const()[name = tensor("x_311_transpose_y_0"), val = tensor(false)]; tensor op_3593_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97315776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97395200))), name = tensor("op_3593_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_32_cast_fp16 = transpose(perm = q_with_bias_v_32_perm_0, x = var_3591_cast_fp16)[name = tensor("transpose_119")]; tensor x_311_cast_fp16 = matmul(transpose_x = x_311_transpose_x_0, transpose_y = x_311_transpose_y_0, x = q_with_bias_v_32_cast_fp16, y = op_3593_to_fp16_palettized)[name = tensor("x_311_cast_fp16")]; 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_274_to_fp16 = const()[name = tensor("const_274_to_fp16"), val = tensor(0x0p+0)]; tensor x0_34_cast_fp16 = pad(constant_val = const_274_to_fp16, mode = x0_34_mode_0, pad = x0_34_pad_0, x = x_311_cast_fp16)[name = tensor("x0_34_cast_fp16")]; tensor var_3601 = const()[name = tensor("op_3601"), val = tensor([1, 8, -1, 8])]; tensor x1_32_cast_fp16 = reshape(shape = var_3601, x = x0_34_cast_fp16)[name = tensor("x1_32_cast_fp16")]; tensor var_3605_begin_0 = const()[name = tensor("op_3605_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3605_end_0 = const()[name = tensor("op_3605_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_3605_end_mask_0 = const()[name = tensor("op_3605_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3605_cast_fp16 = slice_by_index(begin = var_3605_begin_0, end = var_3605_end_0, end_mask = var_3605_end_mask_0, x = x1_32_cast_fp16)[name = tensor("op_3605_cast_fp16")]; tensor var_3606 = const()[name = tensor("op_3606"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_32_cast_fp16 = reshape(shape = var_3606, x = var_3605_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_98_perm_0 = const()[name = tensor("transpose_98_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_99_perm_0 = const()[name = tensor("transpose_99_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_99 = transpose(perm = transpose_99_perm_0, x = k_32_cast_fp16)[name = tensor("transpose_117")]; tensor transpose_98 = transpose(perm = transpose_98_perm_0, x = var_3589_cast_fp16)[name = tensor("transpose_118")]; 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_98, y = transpose_99)[name = tensor("matrix_ac_32_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_32_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_32_end_0, end_mask = matrix_bd0_32_end_mask_0, x = matrix_bd_32_cast_fp16)[name = tensor("matrix_bd0_32_cast_fp16")]; tensor var_3615_cast_fp16 = add(x = matrix_ac_32_cast_fp16, y = matrix_bd0_32_cast_fp16)[name = tensor("op_3615_cast_fp16")]; tensor _inversed_scores_32_y_0_to_fp16 = const()[name = tensor("_inversed_scores_32_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_32_cast_fp16 = mul(x = var_3615_cast_fp16, y = _inversed_scores_32_y_0_to_fp16)[name = tensor("_inversed_scores_32_cast_fp16")]; tensor scores0_32_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_32_cast_fp16, cond = mask0_4)[name = tensor("scores0_32_cast_fp16")]; tensor var_3621_cast_fp16 = softmax(axis = var_47, x = scores0_32_cast_fp16)[name = tensor("op_3621_cast_fp16")]; tensor input0_191_cast_fp16 = select(a = var_26_to_fp16, b = var_3621_cast_fp16, cond = mask0_4)[name = tensor("input0_191_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 value_34_cast_fp16 = transpose(perm = value_34_perm_0, x = v_32_cast_fp16)[name = tensor("transpose_116")]; tensor x2_32_cast_fp16 = matmul(transpose_x = x2_32_transpose_x_0, transpose_y = x2_32_transpose_y_0, x = input0_191_cast_fp16, y = value_34_cast_fp16)[name = tensor("x2_32_cast_fp16")]; tensor var_3625_perm_0 = const()[name = tensor("op_3625_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_3626 = const()[name = tensor("op_3626"), val = tensor([1, -1, 512])]; tensor var_3625_cast_fp16 = transpose(perm = var_3625_perm_0, x = x2_32_cast_fp16)[name = tensor("transpose_115")]; tensor input1_96_cast_fp16 = reshape(shape = var_3626, x = var_3625_cast_fp16)[name = tensor("input1_96_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(97395776))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(97657984))), name = tensor("encoder_layers_15_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_96_cast_fp16)[name = tensor("linear_142_cast_fp16")]; tensor input0_193_cast_fp16 = add(x = input_193_cast_fp16, y = linear_142_cast_fp16)[name = tensor("input0_193_cast_fp16")]; tensor x_315_axes_0 = const()[name = tensor("x_315_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(97658560)))]; 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(97659648)))]; tensor x_315_cast_fp16 = layer_norm(axes = x_315_axes_0, beta = encoder_layers_15_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_15_norm_conv_weight_to_fp16, x = input0_193_cast_fp16)[name = tensor("x_315_cast_fp16")]; tensor input_197_perm_0 = const()[name = tensor("input_197_perm_0"), val = tensor([0, 2, 1])]; tensor input0_195_pad_type_0 = const()[name = tensor("input0_195_pad_type_0"), val = tensor("valid")]; tensor input0_195_strides_0 = const()[name = tensor("input0_195_strides_0"), val = tensor([1])]; tensor input0_195_pad_0 = const()[name = tensor("input0_195_pad_0"), val = tensor([0, 0])]; tensor input0_195_dilations_0 = const()[name = tensor("input0_195_dilations_0"), val = tensor([1])]; tensor input0_195_groups_0 = const()[name = tensor("input0_195_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(97660736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98185088))), name = tensor("encoder_layers_15_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_197_cast_fp16 = transpose(perm = input_197_perm_0, x = x_315_cast_fp16)[name = tensor("transpose_114")]; tensor input0_195_cast_fp16 = conv(dilations = input0_195_dilations_0, groups = input0_195_groups_0, pad = input0_195_pad_0, pad_type = input0_195_pad_type_0, strides = input0_195_strides_0, weight = encoder_layers_15_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_197_cast_fp16)[name = tensor("input0_195_cast_fp16")]; tensor x_317_split_num_splits_0 = const()[name = tensor("x_317_split_num_splits_0"), val = tensor(2)]; tensor x_317_split_axis_0 = const()[name = tensor("x_317_split_axis_0"), val = tensor(1)]; tensor x_317_split_cast_fp16_0, tensor x_317_split_cast_fp16_1 = split(axis = x_317_split_axis_0, num_splits = x_317_split_num_splits_0, x = input0_195_cast_fp16)[name = tensor("x_317_split_cast_fp16")]; tensor x_317_split_1_sigmoid_cast_fp16 = sigmoid(x = x_317_split_cast_fp16_1)[name = tensor("x_317_split_1_sigmoid_cast_fp16")]; tensor x_317_cast_fp16 = mul(x = x_317_split_cast_fp16_0, y = x_317_split_1_sigmoid_cast_fp16)[name = tensor("x_317_cast_fp16")]; tensor input0_197_cast_fp16 = select(a = var_26_to_fp16, b = x_317_cast_fp16, cond = var_546)[name = tensor("input0_197_cast_fp16")]; tensor new_x0_32_interleave_0 = const()[name = tensor("new_x0_32_interleave_0"), val = tensor(false)]; tensor new_x0_32_cast_fp16 = concat(axis = var_47, interleave = new_x0_32_interleave_0, values = (cache30_1_cast_fp16, input0_197_cast_fp16))[name = tensor("new_x0_32_cast_fp16")]; tensor next_cache_32_begin_0 = const()[name = tensor("next_cache_32_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_32_end_0 = const()[name = tensor("next_cache_32_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_32_end_mask_0 = const()[name = tensor("next_cache_32_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_32_cast_fp16 = slice_by_index(begin = next_cache_32_begin_0, end = next_cache_32_end_0, end_mask = next_cache_32_end_mask_0, x = new_x0_32_cast_fp16)[name = tensor("next_cache_32_cast_fp16")]; tensor var_3667_begin_0 = const()[name = tensor("op_3667_begin_0"), val = tensor([0, 0, 4])]; tensor var_3667_end_0 = const()[name = tensor("op_3667_end_0"), val = tensor([1, 512, 12])]; tensor var_3667_end_mask_0 = const()[name = tensor("op_3667_end_mask_0"), val = tensor([true, true, true])]; tensor var_3667_cast_fp16 = slice_by_index(begin = var_3667_begin_0, end = var_3667_end_0, end_mask = var_3667_end_mask_0, x = next_cache_32_cast_fp16)[name = tensor("op_3667_cast_fp16")]; tensor x_319_pad_type_0 = const()[name = tensor("x_319_pad_type_0"), val = tensor("valid")]; tensor x_319_groups_0 = const()[name = tensor("x_319_groups_0"), val = tensor(512)]; tensor x_319_strides_0 = const()[name = tensor("x_319_strides_0"), val = tensor([1])]; tensor x_319_pad_0 = const()[name = tensor("x_319_pad_0"), val = tensor([0, 0])]; tensor x_319_dilations_0 = const()[name = tensor("x_319_dilations_0"), val = tensor([1])]; tensor encoder_layers_15_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98185664))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98190336))), name = tensor("encoder_layers_15_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_319_cast_fp16 = conv(dilations = x_319_dilations_0, groups = x_319_groups_0, pad = x_319_pad_0, pad_type = x_319_pad_type_0, strides = x_319_strides_0, weight = encoder_layers_15_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_32_cast_fp16)[name = tensor("x_319_cast_fp16")]; tensor input1_98_perm_0 = const()[name = tensor("input1_98_perm_0"), val = tensor([0, 2, 1])]; tensor x_321_axes_0 = const()[name = tensor("x_321_axes_0"), val = tensor([-1])]; tensor encoder_layers_15_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_15_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98190912)))]; tensor encoder_layers_15_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_15_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98192000)))]; tensor input1_98_cast_fp16 = transpose(perm = input1_98_perm_0, x = x_319_cast_fp16)[name = tensor("transpose_113")]; tensor x_321_cast_fp16 = layer_norm(axes = x_321_axes_0, beta = encoder_layers_15_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_15_conv_batch_norm_weight_to_fp16, x = input1_98_cast_fp16)[name = tensor("x_321_cast_fp16")]; tensor input2_64_perm_0 = const()[name = tensor("input2_64_perm_0"), val = tensor([0, 2, 1])]; tensor input2_64_cast_fp16 = transpose(perm = input2_64_perm_0, x = x_321_cast_fp16)[name = tensor("transpose_112")]; tensor var_3682_cast_fp16 = silu(x = input2_64_cast_fp16)[name = tensor("op_3682_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_15_conv_pointwise_conv2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98193088))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(98455296))), name = tensor("encoder_layers_15_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 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_15_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3682_cast_fp16)[name = tensor("x_323_cast_fp16")]; tensor input3_34_perm_0 = const()[name = tensor("input3_34_perm_0"), val = tensor([0, 2, 1])]; tensor input3_34_cast_fp16 = transpose(perm = input3_34_perm_0, x = x_323_cast_fp16)[name = tensor("transpose_111")]; tensor input1_100_cast_fp16 = add(x = input0_193_cast_fp16, y = input3_34_cast_fp16)[name = tensor("input1_100_cast_fp16")]; tensor input0_10_axes_0 = const()[name = tensor("input0_10_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(98455872)))]; 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(98456960)))]; tensor input0_10_cast_fp16 = layer_norm(axes = input0_10_axes_0, beta = encoder_layers_15_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_15_norm_feed_forward2_weight_to_fp16, x = input1_100_cast_fp16)[name = tensor("input0_10_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(98458048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(99506688))), name = tensor("encoder_layers_15_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_10_cast_fp16)[name = tensor("linear_143_cast_fp16")]; tensor var_3703_cast_fp16 = silu(x = linear_143_cast_fp16)[name = tensor("op_3703_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(99507264))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(100555904))), name = tensor("encoder_layers_15_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3703_cast_fp16)[name = tensor("linear_144_cast_fp16")]; tensor var_3708_to_fp16 = const()[name = tensor("op_3708_to_fp16"), val = tensor(0x1p-1)]; tensor var_3709_cast_fp16 = mul(x = linear_144_cast_fp16, y = var_3708_to_fp16)[name = tensor("op_3709_cast_fp16")]; tensor input2_66_cast_fp16 = add(x = input1_100_cast_fp16, y = var_3709_cast_fp16)[name = tensor("input2_66_cast_fp16")]; tensor input0_199_axes_0 = const()[name = tensor("input0_199_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(100556480)))]; 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(100557568)))]; tensor input0_199_cast_fp16 = layer_norm(axes = input0_199_axes_0, beta = encoder_layers_15_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_15_norm_out_weight_to_fp16, x = input2_66_cast_fp16)[name = tensor("input0_199_cast_fp16")]; tensor cache31_1_begin_0 = const()[name = tensor("cache31_1_begin_0"), val = tensor([16, 0, 0, 0])]; tensor cache31_1_end_0 = const()[name = tensor("cache31_1_end_0"), val = tensor([17, 1, 70, 512])]; tensor cache31_1_end_mask_0 = const()[name = tensor("cache31_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache31_1_squeeze_mask_0 = const()[name = tensor("cache31_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache31_1_cast_fp16 = slice_by_index(begin = cache31_1_begin_0, end = cache31_1_end_0, end_mask = cache31_1_end_mask_0, squeeze_mask = cache31_1_squeeze_mask_0, x = cache_last_channel_to_fp16)[name = tensor("cache31_1_cast_fp16")]; tensor cache32_1_begin_0 = const()[name = tensor("cache32_1_begin_0"), val = tensor([16, 0, 0, 0])]; tensor cache32_1_end_0 = const()[name = tensor("cache32_1_end_0"), val = tensor([17, 1, 512, 8])]; tensor cache32_1_end_mask_0 = const()[name = tensor("cache32_1_end_mask_0"), val = tensor([false, true, true, true])]; tensor cache32_1_squeeze_mask_0 = const()[name = tensor("cache32_1_squeeze_mask_0"), val = tensor([true, false, false, false])]; tensor cache32_1_cast_fp16 = slice_by_index(begin = cache32_1_begin_0, end = cache32_1_end_0, end_mask = cache32_1_end_mask_0, squeeze_mask = cache32_1_squeeze_mask_0, x = cache_last_time_to_fp16)[name = tensor("cache32_1_cast_fp16")]; tensor input_4_axes_0 = const()[name = tensor("input_4_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(100558656)))]; 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(100559744)))]; tensor input_4_cast_fp16 = layer_norm(axes = input_4_axes_0, beta = encoder_layers_16_norm_feed_forward1_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_16_norm_feed_forward1_weight_to_fp16, x = input0_199_cast_fp16)[name = tensor("input_4_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(100560832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(101609472))), name = tensor("encoder_layers_16_feed_forward1_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_4_cast_fp16)[name = tensor("linear_145_cast_fp16")]; tensor var_3738_cast_fp16 = silu(x = linear_145_cast_fp16)[name = tensor("op_3738_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(101610048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102658688))), name = tensor("encoder_layers_16_feed_forward1_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3738_cast_fp16)[name = tensor("linear_146_cast_fp16")]; tensor var_3743_to_fp16 = const()[name = tensor("op_3743_to_fp16"), val = tensor(0x1p-1)]; tensor var_3744_cast_fp16 = mul(x = linear_146_cast_fp16, y = var_3743_to_fp16)[name = tensor("op_3744_cast_fp16")]; tensor input_2_cast_fp16 = add(x = input0_199_cast_fp16, y = var_3744_cast_fp16)[name = tensor("input_2_cast_fp16")]; tensor key_1_axes_0 = const()[name = tensor("key_1_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(102659264)))]; 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(102660352)))]; tensor key_1_cast_fp16 = layer_norm(axes = key_1_axes_0, beta = encoder_layers_16_norm_self_att_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_16_norm_self_att_weight_to_fp16, x = input_2_cast_fp16)[name = tensor("key_1_cast_fp16")]; tensor input_8_interleave_0 = const()[name = tensor("input_8_interleave_0"), val = tensor(false)]; tensor input_8_cast_fp16 = concat(axis = var_55, interleave = input_8_interleave_0, values = (cache31_1_cast_fp16, key_1_cast_fp16))[name = tensor("input_8_cast_fp16")]; tensor var_3766_begin_0 = const()[name = tensor("op_3766_begin_0"), val = tensor([0, 4, 0])]; tensor var_3766_end_0 = const()[name = tensor("op_3766_end_0"), val = tensor([1, 70, 512])]; tensor var_3766_end_mask_0 = const()[name = tensor("op_3766_end_mask_0"), val = tensor([true, true, true])]; tensor var_3766_cast_fp16 = slice_by_index(begin = var_3766_begin_0, end = var_3766_end_0, end_mask = var_3766_end_mask_0, x = cache31_1_cast_fp16)[name = tensor("op_3766_cast_fp16")]; tensor var_3769_begin_0 = const()[name = tensor("op_3769_begin_0"), val = tensor([0, 0, 0])]; tensor var_3769_end_0 = const()[name = tensor("op_3769_end_0"), val = tensor([1, 4, 512])]; tensor var_3769_end_mask_0 = const()[name = tensor("op_3769_end_mask_0"), val = tensor([true, false, true])]; tensor var_3769_cast_fp16 = slice_by_index(begin = var_3769_begin_0, end = var_3769_end_0, end_mask = var_3769_end_mask_0, x = key_1_cast_fp16)[name = tensor("op_3769_cast_fp16")]; tensor cache_last_channel_cur_1_interleave_0 = const()[name = tensor("cache_last_channel_cur_1_interleave_0"), val = tensor(false)]; tensor cache_last_channel_cur_1_cast_fp16 = concat(axis = var_55, interleave = cache_last_channel_cur_1_interleave_0, values = (var_3766_cast_fp16, var_3769_cast_fp16))[name = tensor("cache_last_channel_cur_1_cast_fp16")]; 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(102661440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(102923648))), name = tensor("encoder_layers_16_self_attn_linear_q_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = key_1_cast_fp16)[name = tensor("linear_147_cast_fp16")]; tensor var_3776 = const()[name = tensor("op_3776"), val = tensor([1, -1, 8, 64])]; tensor q_1_cast_fp16 = reshape(shape = var_3776, x = linear_147_cast_fp16)[name = tensor("q_1_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(102924224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103186432))), name = tensor("encoder_layers_16_self_attn_linear_k_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_8_cast_fp16)[name = tensor("linear_148_cast_fp16")]; tensor var_3780 = const()[name = tensor("op_3780"), val = tensor([1, -1, 8, 64])]; tensor k_1_cast_fp16 = reshape(shape = var_3780, x = linear_148_cast_fp16)[name = tensor("k_1_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(103187008))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103449216))), name = tensor("encoder_layers_16_self_attn_linear_v_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input_8_cast_fp16)[name = tensor("linear_149_cast_fp16")]; tensor var_3784 = const()[name = tensor("op_3784"), val = tensor([1, -1, 8, 64])]; tensor v_1_cast_fp16 = reshape(shape = var_3784, x = linear_149_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_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(103449792)))]; tensor var_3796_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_layers_16_self_attn_pos_bias_u_to_fp16)[name = tensor("op_3796_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(103450880)))]; tensor var_3798_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_layers_16_self_attn_pos_bias_v_to_fp16)[name = tensor("op_3798_cast_fp16")]; tensor q_with_bias_v_1_perm_0 = const()[name = tensor("q_with_bias_v_1_perm_0"), val = tensor([0, 2, -3, -1])]; tensor x_10_transpose_x_0 = const()[name = tensor("x_10_transpose_x_0"), val = tensor(false)]; tensor x_10_transpose_y_0 = const()[name = tensor("x_10_transpose_y_0"), val = tensor(false)]; tensor op_3800_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103451968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103531392))), name = tensor("op_3800_to_fp16_palettized"), shape = tensor([1, 8, 64, 155])]; tensor q_with_bias_v_1_cast_fp16 = transpose(perm = q_with_bias_v_1_perm_0, x = var_3798_cast_fp16)[name = tensor("transpose_110")]; tensor x_10_cast_fp16 = matmul(transpose_x = x_10_transpose_x_0, transpose_y = x_10_transpose_y_0, x = q_with_bias_v_1_cast_fp16, y = op_3800_to_fp16_palettized)[name = tensor("x_10_cast_fp16")]; 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_287_to_fp16 = const()[name = tensor("const_287_to_fp16"), val = tensor(0x0p+0)]; tensor x0_1_cast_fp16 = pad(constant_val = const_287_to_fp16, mode = x0_1_mode_0, pad = x0_1_pad_0, x = x_10_cast_fp16)[name = tensor("x0_1_cast_fp16")]; tensor var_3808 = const()[name = tensor("op_3808"), val = tensor([1, 8, -1, 8])]; tensor x1_1_cast_fp16 = reshape(shape = var_3808, x = x0_1_cast_fp16)[name = tensor("x1_1_cast_fp16")]; tensor var_3812_begin_0 = const()[name = tensor("op_3812_begin_0"), val = tensor([0, 0, 1, 0])]; tensor var_3812_end_0 = const()[name = tensor("op_3812_end_0"), val = tensor([1, 8, 156, 8])]; tensor var_3812_end_mask_0 = const()[name = tensor("op_3812_end_mask_0"), val = tensor([true, true, true, true])]; tensor var_3812_cast_fp16 = slice_by_index(begin = var_3812_begin_0, end = var_3812_end_0, end_mask = var_3812_end_mask_0, x = x1_1_cast_fp16)[name = tensor("op_3812_cast_fp16")]; tensor var_3813 = const()[name = tensor("op_3813"), val = tensor([1, 8, 8, 155])]; tensor matrix_bd_1_cast_fp16 = reshape(shape = var_3813, x = var_3812_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_100_perm_0 = const()[name = tensor("transpose_100_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_101_perm_0 = const()[name = tensor("transpose_101_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_101 = transpose(perm = transpose_101_perm_0, x = k_1_cast_fp16)[name = tensor("transpose_108")]; tensor transpose_100 = transpose(perm = transpose_100_perm_0, x = var_3796_cast_fp16)[name = tensor("transpose_109")]; 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_100, y = transpose_101)[name = tensor("matrix_ac_1_cast_fp16")]; 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_0 = const()[name = tensor("matrix_bd0_1_end_0"), val = tensor([1, 8, 8, 78])]; 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 = matrix_bd0_1_end_0, end_mask = matrix_bd0_1_end_mask_0, x = matrix_bd_1_cast_fp16)[name = tensor("matrix_bd0_1_cast_fp16")]; tensor var_3822_cast_fp16 = add(x = matrix_ac_1_cast_fp16, y = matrix_bd0_1_cast_fp16)[name = tensor("op_3822_cast_fp16")]; tensor _inversed_scores_1_y_0_to_fp16 = const()[name = tensor("_inversed_scores_1_y_0_to_fp16"), val = tensor(0x1p-3)]; tensor _inversed_scores_1_cast_fp16 = mul(x = var_3822_cast_fp16, y = _inversed_scores_1_y_0_to_fp16)[name = tensor("_inversed_scores_1_cast_fp16")]; tensor scores0_1_cast_fp16 = select(a = var_27_to_fp16, b = _inversed_scores_1_cast_fp16, cond = mask0_4)[name = tensor("scores0_1_cast_fp16")]; tensor var_3828_cast_fp16 = softmax(axis = var_47, x = scores0_1_cast_fp16)[name = tensor("op_3828_cast_fp16")]; tensor input0_4_cast_fp16 = select(a = var_26_to_fp16, b = var_3828_cast_fp16, cond = mask0_4)[name = tensor("input0_4_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 value_1_cast_fp16 = transpose(perm = value_1_perm_0, x = v_1_cast_fp16)[name = tensor("transpose_107")]; tensor x2_1_cast_fp16 = matmul(transpose_x = x2_1_transpose_x_0, transpose_y = x2_1_transpose_y_0, x = input0_4_cast_fp16, y = value_1_cast_fp16)[name = tensor("x2_1_cast_fp16")]; tensor var_3832_perm_0 = const()[name = tensor("op_3832_perm_0"), val = tensor([0, 2, 1, 3])]; tensor var_3833 = const()[name = tensor("op_3833"), val = tensor([1, -1, 512])]; tensor var_3832_cast_fp16 = transpose(perm = var_3832_perm_0, x = x2_1_cast_fp16)[name = tensor("transpose_106")]; tensor input1_4_cast_fp16 = reshape(shape = var_3833, x = var_3832_cast_fp16)[name = tensor("input1_4_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(103531968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(103794176))), name = tensor("encoder_layers_16_self_attn_linear_out_weight_to_fp16_palettized"), shape = tensor([512, 512])]; 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 = input1_4_cast_fp16)[name = tensor("linear_151_cast_fp16")]; tensor input0_6_cast_fp16 = add(x = input_2_cast_fp16, y = linear_151_cast_fp16)[name = tensor("input0_6_cast_fp16")]; tensor x_14_axes_0 = const()[name = tensor("x_14_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(103794752)))]; 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(103795840)))]; tensor x_14_cast_fp16 = layer_norm(axes = x_14_axes_0, beta = encoder_layers_16_norm_conv_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_16_norm_conv_weight_to_fp16, x = input0_6_cast_fp16)[name = tensor("x_14_cast_fp16")]; tensor input_10_perm_0 = const()[name = tensor("input_10_perm_0"), val = tensor([0, 2, 1])]; tensor input0_8_pad_type_0 = const()[name = tensor("input0_8_pad_type_0"), val = tensor("valid")]; tensor input0_8_strides_0 = const()[name = tensor("input0_8_strides_0"), val = tensor([1])]; tensor input0_8_pad_0 = const()[name = tensor("input0_8_pad_0"), val = tensor([0, 0])]; tensor input0_8_dilations_0 = const()[name = tensor("input0_8_dilations_0"), val = tensor([1])]; tensor input0_8_groups_0 = const()[name = tensor("input0_8_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(103796928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104321280))), name = tensor("encoder_layers_16_conv_pointwise_conv1_weight_to_fp16_palettized"), shape = tensor([1024, 512, 1])]; tensor input_10_cast_fp16 = transpose(perm = input_10_perm_0, x = x_14_cast_fp16)[name = tensor("transpose_105")]; tensor input0_8_cast_fp16 = conv(dilations = input0_8_dilations_0, groups = input0_8_groups_0, pad = input0_8_pad_0, pad_type = input0_8_pad_type_0, strides = input0_8_strides_0, weight = encoder_layers_16_conv_pointwise_conv1_weight_to_fp16_palettized, x = input_10_cast_fp16)[name = tensor("input0_8_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_8_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_26_to_fp16, b = x_2_cast_fp16, cond = var_546)[name = tensor("input0_2_cast_fp16")]; tensor new_x0_1_interleave_0 = const()[name = tensor("new_x0_1_interleave_0"), val = tensor(false)]; tensor new_x0_1_cast_fp16 = concat(axis = var_47, interleave = new_x0_1_interleave_0, values = (cache32_1_cast_fp16, input0_2_cast_fp16))[name = tensor("new_x0_1_cast_fp16")]; tensor next_cache_1_begin_0 = const()[name = tensor("next_cache_1_begin_0"), val = tensor([0, 0, 0])]; tensor next_cache_1_end_0 = const()[name = tensor("next_cache_1_end_0"), val = tensor([1, 512, 12])]; tensor next_cache_1_end_mask_0 = const()[name = tensor("next_cache_1_end_mask_0"), val = tensor([true, true, false])]; tensor next_cache_1_cast_fp16 = slice_by_index(begin = next_cache_1_begin_0, end = next_cache_1_end_0, end_mask = next_cache_1_end_mask_0, x = new_x0_1_cast_fp16)[name = tensor("next_cache_1_cast_fp16")]; tensor cache_last_time_cur_1_begin_0 = const()[name = tensor("cache_last_time_cur_1_begin_0"), val = tensor([0, 0, 4])]; tensor cache_last_time_cur_1_end_0 = const()[name = tensor("cache_last_time_cur_1_end_0"), val = tensor([1, 512, 12])]; tensor cache_last_time_cur_1_end_mask_0 = const()[name = tensor("cache_last_time_cur_1_end_mask_0"), val = tensor([true, true, true])]; tensor cache_last_time_cur_1_cast_fp16 = slice_by_index(begin = cache_last_time_cur_1_begin_0, end = cache_last_time_cur_1_end_0, end_mask = cache_last_time_cur_1_end_mask_0, x = next_cache_1_cast_fp16)[name = tensor("cache_last_time_cur_1_cast_fp16")]; tensor x_4_pad_type_0 = const()[name = tensor("x_4_pad_type_0"), val = tensor("valid")]; tensor x_4_groups_0 = const()[name = tensor("x_4_groups_0"), val = tensor(512)]; tensor x_4_strides_0 = const()[name = tensor("x_4_strides_0"), val = tensor([1])]; tensor x_4_pad_0 = const()[name = tensor("x_4_pad_0"), val = tensor([0, 0])]; tensor x_4_dilations_0 = const()[name = tensor("x_4_dilations_0"), val = tensor([1])]; tensor encoder_layers_16_conv_depthwise_conv_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104321856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104326528))), name = tensor("encoder_layers_16_conv_depthwise_conv_weight_to_fp16_palettized"), shape = tensor([512, 1, 9])]; tensor x_4_cast_fp16 = conv(dilations = x_4_dilations_0, groups = x_4_groups_0, pad = x_4_pad_0, pad_type = x_4_pad_type_0, strides = x_4_strides_0, weight = encoder_layers_16_conv_depthwise_conv_weight_to_fp16_palettized, x = new_x0_1_cast_fp16)[name = tensor("x_4_cast_fp16")]; tensor input1_1_perm_0 = const()[name = tensor("input1_1_perm_0"), val = tensor([0, 2, 1])]; tensor x_6_axes_0 = const()[name = tensor("x_6_axes_0"), val = tensor([-1])]; tensor encoder_layers_16_conv_batch_norm_weight_to_fp16 = const()[name = tensor("encoder_layers_16_conv_batch_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104327104)))]; tensor encoder_layers_16_conv_batch_norm_bias_to_fp16 = const()[name = tensor("encoder_layers_16_conv_batch_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104328192)))]; tensor input1_1_cast_fp16 = transpose(perm = input1_1_perm_0, x = x_4_cast_fp16)[name = tensor("transpose_104")]; tensor x_6_cast_fp16 = layer_norm(axes = x_6_axes_0, beta = encoder_layers_16_conv_batch_norm_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_16_conv_batch_norm_weight_to_fp16, x = input1_1_cast_fp16)[name = tensor("x_6_cast_fp16")]; tensor input2_1_perm_0 = const()[name = tensor("input2_1_perm_0"), val = tensor([0, 2, 1])]; tensor input2_1_cast_fp16 = transpose(perm = input2_1_perm_0, x = x_6_cast_fp16)[name = tensor("transpose_103")]; tensor var_3889_cast_fp16 = silu(x = input2_1_cast_fp16)[name = tensor("op_3889_cast_fp16")]; tensor x_16_pad_type_0 = const()[name = tensor("x_16_pad_type_0"), val = tensor("valid")]; tensor x_16_strides_0 = const()[name = tensor("x_16_strides_0"), val = tensor([1])]; tensor x_16_pad_0 = const()[name = tensor("x_16_pad_0"), val = tensor([0, 0])]; tensor x_16_dilations_0 = const()[name = tensor("x_16_dilations_0"), val = tensor([1])]; tensor x_16_groups_0 = const()[name = tensor("x_16_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(104329280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(104591488))), name = tensor("encoder_layers_16_conv_pointwise_conv2_weight_to_fp16_palettized"), shape = tensor([512, 512, 1])]; tensor x_16_cast_fp16 = conv(dilations = x_16_dilations_0, groups = x_16_groups_0, pad = x_16_pad_0, pad_type = x_16_pad_type_0, strides = x_16_strides_0, weight = encoder_layers_16_conv_pointwise_conv2_weight_to_fp16_palettized, x = var_3889_cast_fp16)[name = tensor("x_16_cast_fp16")]; tensor input3_1_perm_0 = const()[name = tensor("input3_1_perm_0"), val = tensor([0, 2, 1])]; tensor input3_1_cast_fp16 = transpose(perm = input3_1_perm_0, x = x_16_cast_fp16)[name = tensor("transpose_102")]; tensor input1_2_cast_fp16 = add(x = input0_6_cast_fp16, y = input3_1_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_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(104592064)))]; 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(104593152)))]; tensor input0_1_cast_fp16 = layer_norm(axes = input0_1_axes_0, beta = encoder_layers_16_norm_feed_forward2_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_16_norm_feed_forward2_weight_to_fp16, x = input1_2_cast_fp16)[name = tensor("input0_1_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(104594240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(105642880))), name = tensor("encoder_layers_16_feed_forward2_linear1_weight_to_fp16_palettized"), shape = tensor([2048, 512])]; 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_1_cast_fp16)[name = tensor("linear_152_cast_fp16")]; tensor var_3910_cast_fp16 = silu(x = linear_152_cast_fp16)[name = tensor("op_3910_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(105643456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(106692096))), name = tensor("encoder_layers_16_feed_forward2_linear2_weight_to_fp16_palettized"), shape = tensor([512, 2048])]; 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_3910_cast_fp16)[name = tensor("linear_153_cast_fp16")]; tensor var_3915_to_fp16 = const()[name = tensor("op_3915_to_fp16"), val = tensor(0x1p-1)]; tensor var_3916_cast_fp16 = mul(x = linear_153_cast_fp16, y = var_3915_to_fp16)[name = tensor("op_3916_cast_fp16")]; tensor input2_2_cast_fp16 = add(x = input1_2_cast_fp16, y = var_3916_cast_fp16)[name = tensor("input2_2_cast_fp16")]; tensor audio_signal_1_axes_0 = const()[name = tensor("audio_signal_1_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(106692672)))]; 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(106693760)))]; tensor encoded_output = layer_norm(axes = audio_signal_1_axes_0, beta = encoder_layers_16_norm_out_bias_to_fp16, epsilon = var_25_to_fp16, gamma = encoder_layers_16_norm_out_weight_to_fp16, x = input2_2_cast_fp16)[name = tensor("audio_signal_1_cast_fp16")]; tensor obj1_1_axis_0 = const()[name = tensor("obj1_1_axis_0"), val = tensor(0)]; tensor new_cache_last_channel = stack(axis = obj1_1_axis_0, values = (var_460_cast_fp16, var_667_cast_fp16, var_874_cast_fp16, var_1081_cast_fp16, var_1288_cast_fp16, var_1495_cast_fp16, var_1702_cast_fp16, var_1909_cast_fp16, var_2116_cast_fp16, var_2323_cast_fp16, var_2530_cast_fp16, var_2737_cast_fp16, var_2944_cast_fp16, var_3151_cast_fp16, var_3358_cast_fp16, var_3565_cast_fp16, cache_last_channel_cur_1_cast_fp16))[name = tensor("obj1_1_cast_fp16")]; tensor obj2_1_axis_0 = const()[name = tensor("obj2_1_axis_0"), val = tensor(0)]; tensor new_cache_last_time = stack(axis = obj2_1_axis_0, values = (var_562_cast_fp16, var_769_cast_fp16, var_976_cast_fp16, var_1183_cast_fp16, var_1390_cast_fp16, var_1597_cast_fp16, var_1804_cast_fp16, var_2011_cast_fp16, var_2218_cast_fp16, var_2425_cast_fp16, var_2632_cast_fp16, var_2839_cast_fp16, var_3046_cast_fp16, var_3253_cast_fp16, var_3460_cast_fp16, var_3667_cast_fp16, cache_last_time_cur_1_cast_fp16))[name = tensor("obj2_1_cast_fp16")]; tensor var_3932 = add(x = cache_last_channel_len, y = cache_keep_size_1)[name = tensor("op_3932")]; tensor var_3932_promoted_to_fp16_dtype_0 = const()[name = tensor("op_3932_promoted_to_fp16_dtype_0"), val = tensor("fp16")]; tensor const_293_to_fp16 = const()[name = tensor("const_293_to_fp16"), val = tensor(-inf)]; tensor var_46_promoted_to_fp16 = const()[name = tensor("op_46_promoted_to_fp16"), val = tensor(0x1.18p+6)]; tensor var_3932_to_fp16 = cast(dtype = var_3932_promoted_to_fp16_dtype_0, x = var_3932)[name = tensor("cast_2")]; tensor clip_1_cast_fp16 = clip(alpha = const_293_to_fp16, beta = var_46_promoted_to_fp16, x = var_3932_to_fp16)[name = tensor("clip_1_cast_fp16")]; tensor cast_179_dtype_0 = const()[name = tensor("cast_179_dtype_0"), val = tensor("int32")]; tensor cast_180_dtype_0 = const()[name = tensor("cast_180_dtype_0"), val = tensor("int32")]; tensor encoded_length = cast(dtype = cast_179_dtype_0, x = clip_0_cast_fp16)[name = tensor("cast_0")]; tensor new_cache_last_channel_len = cast(dtype = cast_180_dtype_0, x = clip_1_cast_fp16)[name = tensor("cast_1")]; } -> (encoded_output, encoded_length, new_pre_cache, new_cache_last_channel, new_cache_last_time, new_cache_last_channel_len); }