program(1.0) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "3520.4.1"}, {"coremlc-version", "3520.5.1"}})] { func main(tensor mel) [FlexibleShapeInformation = tuple, dict, tensor>>, tuple, dict, dict, tensor>>>>((("DefaultShapes", {{"mel", [1, 128, 100]}}), ("EnumeratedShapes", {{"mel_1_1_1_128_1000_", {{"mel", [1, 128, 1000]}}}, {"mel_1_1_1_128_100_", {{"mel", [1, 128, 100]}}}, {"mel_1_1_1_128_1500_", {{"mel", [1, 128, 1500]}}}, {"mel_1_1_1_128_2000_", {{"mel", [1, 128, 2000]}}}, {"mel_1_1_1_128_200_", {{"mel", [1, 128, 200]}}}, {"mel_1_1_1_128_3000_", {{"mel", [1, 128, 3000]}}}, {"mel_1_1_1_128_400_", {{"mel", [1, 128, 400]}}}, {"mel_1_1_1_128_600_", {{"mel", [1, 128, 600]}}}, {"mel_1_1_1_128_800_", {{"mel", [1, 128, 800]}}}})))] { tensor input_1_axes_0 = const()[name = tensor("input_1_axes_0"), val = tensor([1])]; tensor mel_to_fp16_dtype_0 = const()[name = tensor("mel_to_fp16_dtype_0"), val = tensor("fp16")]; tensor mel_to_fp16 = cast(dtype = mel_to_fp16_dtype_0, x = mel)[name = tensor("cast_2")]; tensor input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = mel_to_fp16)[name = tensor("input_1_cast_fp16")]; tensor var_59_pad_type_0 = const()[name = tensor("op_59_pad_type_0"), val = tensor("custom")]; tensor var_59_pad_0 = const()[name = tensor("op_59_pad_0"), val = tensor([1, 1, 1, 1])]; tensor var_59_strides_0 = const()[name = tensor("op_59_strides_0"), val = tensor([2, 2])]; tensor var_59_dilations_0 = const()[name = tensor("op_59_dilations_0"), val = tensor([1, 1])]; tensor var_59_groups_0 = const()[name = tensor("op_59_groups_0"), val = tensor(1)]; tensor conv2d1_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(2304))), name = tensor("conv2d1_weight_to_fp16_palettized"), shape = tensor([480, 1, 3, 3])]; tensor conv2d1_bias_to_fp16 = const()[name = tensor("conv2d1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2432)))]; tensor var_59_cast_fp16 = conv(bias = conv2d1_bias_to_fp16, dilations = var_59_dilations_0, groups = var_59_groups_0, pad = var_59_pad_0, pad_type = var_59_pad_type_0, strides = var_59_strides_0, weight = conv2d1_weight_to_fp16_palettized, x = input_1_cast_fp16)[name = tensor("op_59_cast_fp16")]; tensor input_3_mode_0 = const()[name = tensor("input_3_mode_0"), val = tensor("EXACT")]; tensor input_3_cast_fp16 = gelu(mode = input_3_mode_0, x = var_59_cast_fp16)[name = tensor("input_3_cast_fp16")]; tensor var_73_pad_type_0 = const()[name = tensor("op_73_pad_type_0"), val = tensor("custom")]; tensor var_73_pad_0 = const()[name = tensor("op_73_pad_0"), val = tensor([1, 1, 1, 1])]; tensor var_73_strides_0 = const()[name = tensor("op_73_strides_0"), val = tensor([2, 2])]; tensor var_73_dilations_0 = const()[name = tensor("op_73_dilations_0"), val = tensor([1, 1])]; tensor var_73_groups_0 = const()[name = tensor("op_73_groups_0"), val = tensor(1)]; tensor conv2d2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(3456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1040320))), name = tensor("conv2d2_weight_to_fp16_palettized"), shape = tensor([480, 480, 3, 3])]; tensor conv2d2_bias_to_fp16 = const()[name = tensor("conv2d2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1040448)))]; tensor var_73_cast_fp16 = conv(bias = conv2d2_bias_to_fp16, dilations = var_73_dilations_0, groups = var_73_groups_0, pad = var_73_pad_0, pad_type = var_73_pad_type_0, strides = var_73_strides_0, weight = conv2d2_weight_to_fp16_palettized, x = input_3_cast_fp16)[name = tensor("op_73_cast_fp16")]; tensor input_5_mode_0 = const()[name = tensor("input_5_mode_0"), val = tensor("EXACT")]; tensor input_5_cast_fp16 = gelu(mode = input_5_mode_0, x = var_73_cast_fp16)[name = tensor("input_5_cast_fp16")]; tensor var_87_pad_type_0 = const()[name = tensor("op_87_pad_type_0"), val = tensor("custom")]; tensor var_87_pad_0 = const()[name = tensor("op_87_pad_0"), val = tensor([1, 1, 1, 1])]; tensor var_87_strides_0 = const()[name = tensor("op_87_strides_0"), val = tensor([2, 2])]; tensor var_87_dilations_0 = const()[name = tensor("op_87_dilations_0"), val = tensor([1, 1])]; tensor var_87_groups_0 = const()[name = tensor("op_87_groups_0"), val = tensor(1)]; tensor conv2d3_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(1041472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2078336))), name = tensor("conv2d3_weight_to_fp16_palettized"), shape = tensor([480, 480, 3, 3])]; tensor conv2d3_bias_to_fp16 = const()[name = tensor("conv2d3_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2078464)))]; tensor var_87_cast_fp16 = conv(bias = conv2d3_bias_to_fp16, dilations = var_87_dilations_0, groups = var_87_groups_0, pad = var_87_pad_0, pad_type = var_87_pad_type_0, strides = var_87_strides_0, weight = conv2d3_weight_to_fp16_palettized, x = input_5_cast_fp16)[name = tensor("op_87_cast_fp16")]; tensor x_1_mode_0 = const()[name = tensor("x_1_mode_0"), val = tensor("EXACT")]; tensor x_1_cast_fp16 = gelu(mode = x_1_mode_0, x = var_87_cast_fp16)[name = tensor("x_1_cast_fp16")]; tensor var_108 = const()[name = tensor("op_108"), val = tensor([0, 3, 1, 2])]; tensor concat_0x = const()[name = tensor("concat_0x"), val = tensor([1, -1, 7680])]; tensor var_109_cast_fp16 = transpose(perm = var_108, x = x_1_cast_fp16)[name = tensor("transpose_180")]; tensor input_7_cast_fp16 = reshape(shape = concat_0x, x = var_109_cast_fp16)[name = tensor("input_7_cast_fp16")]; tensor conv_out_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(2079488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5520192))), name = tensor("conv_out_weight_to_fp16_palettized"), shape = tensor([896, 7680])]; tensor linear_0_bias_0_to_fp16 = const()[name = tensor("linear_0_bias_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5520320)))]; tensor linear_0_cast_fp16 = linear(bias = linear_0_bias_0_to_fp16, weight = conv_out_weight_to_fp16_palettized, x = input_7_cast_fp16)[name = tensor("linear_0_cast_fp16")]; tensor var_118_shape_cast_fp16 = shape(x = linear_0_cast_fp16)[name = tensor("op_118_shape_cast_fp16")]; tensor gather_4_axis_0 = const()[name = tensor("gather_4_axis_0"), val = tensor(0)]; tensor gather_4_batch_dims_0 = const()[name = tensor("gather_4_batch_dims_0"), val = tensor(0)]; tensor gather_4_validate_indices_0 = const()[name = tensor("gather_4_validate_indices_0"), val = tensor(false)]; tensor var_118_shape_cast_fp16_to_uint16_dtype_0 = const()[name = tensor("op_118_shape_cast_fp16_to_uint16_dtype_0"), val = tensor("uint16")]; tensor select_4_to_uint16 = const()[name = tensor("select_4_to_uint16"), val = tensor(1)]; tensor var_118_shape_cast_fp16_to_uint16 = cast(dtype = var_118_shape_cast_fp16_to_uint16_dtype_0, x = var_118_shape_cast_fp16)[name = tensor("cast_1")]; tensor gather_4_cast_uint16 = gather(axis = gather_4_axis_0, batch_dims = gather_4_batch_dims_0, indices = select_4_to_uint16, validate_indices = gather_4_validate_indices_0, x = var_118_shape_cast_fp16_to_uint16)[name = tensor("gather_4_cast_uint16")]; tensor gather_4_cast_uint16_to_int32_dtype_0 = const()[name = tensor("gather_4_cast_uint16_to_int32_dtype_0"), val = tensor("int32")]; tensor concat_1_values0_0 = const()[name = tensor("concat_1_values0_0"), val = tensor(1)]; tensor concat_1_values2_0 = const()[name = tensor("concat_1_values2_0"), val = tensor(896)]; tensor concat_1_axis_0 = const()[name = tensor("concat_1_axis_0"), val = tensor(0)]; tensor concat_1_interleave_0 = const()[name = tensor("concat_1_interleave_0"), val = tensor(false)]; tensor gather_4_cast_uint16_to_int32 = cast(dtype = gather_4_cast_uint16_to_int32_dtype_0, x = gather_4_cast_uint16)[name = tensor("cast_0")]; tensor concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (concat_1_values0_0, gather_4_cast_uint16_to_int32, concat_1_values2_0))[name = tensor("concat_1")]; tensor var_129_begin_0 = const()[name = tensor("op_129_begin_0"), val = tensor([0, 0, 0])]; tensor var_129_end_mask_0 = const()[name = tensor("op_129_end_mask_0"), val = tensor([true, false, true])]; tensor pos_embed_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(5522176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6194240))), name = tensor("pos_embed_to_fp16_palettized"), shape = tensor([1, 1500, 896])]; tensor var_129_cast_fp16 = slice_by_index(begin = var_129_begin_0, end = concat_1, end_mask = var_129_end_mask_0, x = pos_embed_to_fp16_palettized)[name = tensor("op_129_cast_fp16")]; tensor input_9_cast_fp16 = add(x = linear_0_cast_fp16, y = var_129_cast_fp16)[name = tensor("input_9_cast_fp16")]; tensor var_144 = const()[name = tensor("op_144"), val = tensor(-1)]; tensor x_5_axes_0 = const()[name = tensor("x_5_axes_0"), val = tensor([-1])]; tensor layers_0_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_0_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6194368)))]; tensor layers_0_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6196224)))]; tensor var_147_to_fp16 = const()[name = tensor("op_147_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_5_cast_fp16 = layer_norm(axes = x_5_axes_0, beta = layers_0_self_attn_layer_norm_bias_to_fp16, epsilon = var_147_to_fp16, gamma = layers_0_self_attn_layer_norm_weight_to_fp16, x = input_9_cast_fp16)[name = tensor("x_5_cast_fp16")]; tensor layers_0_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6198080))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6599552))), name = tensor("layers_0_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_0_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6599680)))]; tensor linear_1_cast_fp16 = linear(bias = layers_0_self_attn_q_proj_bias_to_fp16, weight = layers_0_self_attn_q_proj_weight_to_fp16_palettized, x = x_5_cast_fp16)[name = tensor("linear_1_cast_fp16")]; tensor concat_2x = const()[name = tensor("concat_2x"), val = tensor([1, -1, 14, 64])]; tensor var_168_cast_fp16 = reshape(shape = concat_2x, x = linear_1_cast_fp16)[name = tensor("op_168_cast_fp16")]; tensor layers_0_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(6601536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7003008))), name = tensor("layers_0_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_0_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7003136)))]; tensor linear_2_cast_fp16 = linear(bias = layers_0_self_attn_k_proj_bias_to_fp16, weight = layers_0_self_attn_k_proj_weight_to_fp16_palettized, x = x_5_cast_fp16)[name = tensor("linear_2_cast_fp16")]; tensor concat_3x = const()[name = tensor("concat_3x"), val = tensor([1, -1, 14, 64])]; tensor var_174_cast_fp16 = reshape(shape = concat_3x, x = linear_2_cast_fp16)[name = tensor("op_174_cast_fp16")]; tensor layers_0_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7004992))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7406464))), name = tensor("layers_0_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_0_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7406592)))]; tensor linear_3_cast_fp16 = linear(bias = layers_0_self_attn_v_proj_bias_to_fp16, weight = layers_0_self_attn_v_proj_weight_to_fp16_palettized, x = x_5_cast_fp16)[name = tensor("linear_3_cast_fp16")]; tensor concat_4x = const()[name = tensor("concat_4x"), val = tensor([1, -1, 14, 64])]; tensor var_180_cast_fp16 = reshape(shape = concat_4x, x = linear_3_cast_fp16)[name = tensor("op_180_cast_fp16")]; tensor v_1_perm_0 = const()[name = tensor("v_1_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_183_transpose_x_0 = const()[name = tensor("op_183_transpose_x_0"), val = tensor(false)]; tensor var_183_transpose_y_0 = const()[name = tensor("op_183_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 = var_174_cast_fp16)[name = tensor("transpose_178")]; tensor transpose_72 = transpose(perm = transpose_72_perm_0, x = var_168_cast_fp16)[name = tensor("transpose_179")]; tensor var_183_cast_fp16 = matmul(transpose_x = var_183_transpose_x_0, transpose_y = var_183_transpose_y_0, x = transpose_72, y = transpose_73)[name = tensor("op_183_cast_fp16")]; tensor var_184_to_fp16 = const()[name = tensor("op_184_to_fp16"), val = tensor(0x1p-3)]; tensor input_11_cast_fp16 = mul(x = var_183_cast_fp16, y = var_184_to_fp16)[name = tensor("input_11_cast_fp16")]; tensor attn_1_cast_fp16 = softmax(axis = var_144, x = input_11_cast_fp16)[name = tensor("attn_1_cast_fp16")]; tensor out_1_transpose_x_0 = const()[name = tensor("out_1_transpose_x_0"), val = tensor(false)]; tensor out_1_transpose_y_0 = const()[name = tensor("out_1_transpose_y_0"), val = tensor(false)]; tensor v_1_cast_fp16 = transpose(perm = v_1_perm_0, x = var_180_cast_fp16)[name = tensor("transpose_177")]; tensor out_1_cast_fp16 = matmul(transpose_x = out_1_transpose_x_0, transpose_y = out_1_transpose_y_0, x = attn_1_cast_fp16, y = v_1_cast_fp16)[name = tensor("out_1_cast_fp16")]; tensor var_188_perm_0 = const()[name = tensor("op_188_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_5x = const()[name = tensor("concat_5x"), val = tensor([1, -1, 896])]; tensor var_188_cast_fp16 = transpose(perm = var_188_perm_0, x = out_1_cast_fp16)[name = tensor("transpose_176")]; tensor input_13_cast_fp16 = reshape(shape = concat_5x, x = var_188_cast_fp16)[name = tensor("input_13_cast_fp16")]; tensor layers_0_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7408448))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7809920))), name = tensor("layers_0_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_0_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_0_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7810048)))]; tensor linear_4_cast_fp16 = linear(bias = layers_0_self_attn_out_proj_bias_to_fp16, weight = layers_0_self_attn_out_proj_weight_to_fp16_palettized, x = input_13_cast_fp16)[name = tensor("linear_4_cast_fp16")]; tensor input_15_cast_fp16 = add(x = input_9_cast_fp16, y = linear_4_cast_fp16)[name = tensor("input_15_cast_fp16")]; tensor input_17_axes_0 = const()[name = tensor("input_17_axes_0"), val = tensor([-1])]; tensor layers_0_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_0_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7811904)))]; tensor layers_0_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_0_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7813760)))]; tensor input_17_cast_fp16 = layer_norm(axes = input_17_axes_0, beta = layers_0_final_layer_norm_bias_to_fp16, epsilon = var_147_to_fp16, gamma = layers_0_final_layer_norm_weight_to_fp16, x = input_15_cast_fp16)[name = tensor("input_17_cast_fp16")]; tensor layers_0_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(7815616))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9421312))), name = tensor("layers_0_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_0_fc1_bias_to_fp16 = const()[name = tensor("layers_0_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9421440)))]; tensor linear_5_cast_fp16 = linear(bias = layers_0_fc1_bias_to_fp16, weight = layers_0_fc1_weight_to_fp16_palettized, x = input_17_cast_fp16)[name = tensor("linear_5_cast_fp16")]; tensor input_19_mode_0 = const()[name = tensor("input_19_mode_0"), val = tensor("EXACT")]; tensor input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = linear_5_cast_fp16)[name = tensor("input_19_cast_fp16")]; tensor layers_0_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(9428672))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11034368))), name = tensor("layers_0_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_0_fc2_bias_to_fp16 = const()[name = tensor("layers_0_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11034496)))]; tensor linear_6_cast_fp16 = linear(bias = layers_0_fc2_bias_to_fp16, weight = layers_0_fc2_weight_to_fp16_palettized, x = input_19_cast_fp16)[name = tensor("linear_6_cast_fp16")]; tensor input_21_cast_fp16 = add(x = input_15_cast_fp16, y = linear_6_cast_fp16)[name = tensor("input_21_cast_fp16")]; tensor var_214 = const()[name = tensor("op_214"), val = tensor(-1)]; tensor x_11_axes_0 = const()[name = tensor("x_11_axes_0"), val = tensor([-1])]; tensor layers_1_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_1_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11036352)))]; tensor layers_1_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11038208)))]; tensor var_217_to_fp16 = const()[name = tensor("op_217_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_11_cast_fp16 = layer_norm(axes = x_11_axes_0, beta = layers_1_self_attn_layer_norm_bias_to_fp16, epsilon = var_217_to_fp16, gamma = layers_1_self_attn_layer_norm_weight_to_fp16, x = input_21_cast_fp16)[name = tensor("x_11_cast_fp16")]; tensor layers_1_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11040064))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11441536))), name = tensor("layers_1_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_1_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11441664)))]; tensor linear_7_cast_fp16 = linear(bias = layers_1_self_attn_q_proj_bias_to_fp16, weight = layers_1_self_attn_q_proj_weight_to_fp16_palettized, x = x_11_cast_fp16)[name = tensor("linear_7_cast_fp16")]; tensor concat_6x = const()[name = tensor("concat_6x"), val = tensor([1, -1, 14, 64])]; tensor var_238_cast_fp16 = reshape(shape = concat_6x, x = linear_7_cast_fp16)[name = tensor("op_238_cast_fp16")]; tensor layers_1_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11443520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11844992))), name = tensor("layers_1_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_1_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11845120)))]; tensor linear_8_cast_fp16 = linear(bias = layers_1_self_attn_k_proj_bias_to_fp16, weight = layers_1_self_attn_k_proj_weight_to_fp16_palettized, x = x_11_cast_fp16)[name = tensor("linear_8_cast_fp16")]; tensor concat_7x = const()[name = tensor("concat_7x"), val = tensor([1, -1, 14, 64])]; tensor var_244_cast_fp16 = reshape(shape = concat_7x, x = linear_8_cast_fp16)[name = tensor("op_244_cast_fp16")]; tensor layers_1_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(11846976))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12248448))), name = tensor("layers_1_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_1_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12248576)))]; tensor linear_9_cast_fp16 = linear(bias = layers_1_self_attn_v_proj_bias_to_fp16, weight = layers_1_self_attn_v_proj_weight_to_fp16_palettized, x = x_11_cast_fp16)[name = tensor("linear_9_cast_fp16")]; tensor concat_8x = const()[name = tensor("concat_8x"), val = tensor([1, -1, 14, 64])]; tensor var_250_cast_fp16 = reshape(shape = concat_8x, x = linear_9_cast_fp16)[name = tensor("op_250_cast_fp16")]; tensor v_3_perm_0 = const()[name = tensor("v_3_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_253_transpose_x_0 = const()[name = tensor("op_253_transpose_x_0"), val = tensor(false)]; tensor var_253_transpose_y_0 = const()[name = tensor("op_253_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 = var_244_cast_fp16)[name = tensor("transpose_174")]; tensor transpose_74 = transpose(perm = transpose_74_perm_0, x = var_238_cast_fp16)[name = tensor("transpose_175")]; tensor var_253_cast_fp16 = matmul(transpose_x = var_253_transpose_x_0, transpose_y = var_253_transpose_y_0, x = transpose_74, y = transpose_75)[name = tensor("op_253_cast_fp16")]; tensor var_254_to_fp16 = const()[name = tensor("op_254_to_fp16"), val = tensor(0x1p-3)]; tensor input_23_cast_fp16 = mul(x = var_253_cast_fp16, y = var_254_to_fp16)[name = tensor("input_23_cast_fp16")]; tensor attn_3_cast_fp16 = softmax(axis = var_214, x = input_23_cast_fp16)[name = tensor("attn_3_cast_fp16")]; tensor out_3_transpose_x_0 = const()[name = tensor("out_3_transpose_x_0"), val = tensor(false)]; tensor out_3_transpose_y_0 = const()[name = tensor("out_3_transpose_y_0"), val = tensor(false)]; tensor v_3_cast_fp16 = transpose(perm = v_3_perm_0, x = var_250_cast_fp16)[name = tensor("transpose_173")]; tensor out_3_cast_fp16 = matmul(transpose_x = out_3_transpose_x_0, transpose_y = out_3_transpose_y_0, x = attn_3_cast_fp16, y = v_3_cast_fp16)[name = tensor("out_3_cast_fp16")]; tensor var_258_perm_0 = const()[name = tensor("op_258_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_9x = const()[name = tensor("concat_9x"), val = tensor([1, -1, 896])]; tensor var_258_cast_fp16 = transpose(perm = var_258_perm_0, x = out_3_cast_fp16)[name = tensor("transpose_172")]; tensor input_25_cast_fp16 = reshape(shape = concat_9x, x = var_258_cast_fp16)[name = tensor("input_25_cast_fp16")]; tensor layers_1_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12250432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12651904))), name = tensor("layers_1_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_1_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_1_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12652032)))]; tensor linear_10_cast_fp16 = linear(bias = layers_1_self_attn_out_proj_bias_to_fp16, weight = layers_1_self_attn_out_proj_weight_to_fp16_palettized, x = input_25_cast_fp16)[name = tensor("linear_10_cast_fp16")]; tensor input_27_cast_fp16 = add(x = input_21_cast_fp16, y = linear_10_cast_fp16)[name = tensor("input_27_cast_fp16")]; tensor input_29_axes_0 = const()[name = tensor("input_29_axes_0"), val = tensor([-1])]; tensor layers_1_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_1_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12653888)))]; tensor layers_1_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_1_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12655744)))]; tensor input_29_cast_fp16 = layer_norm(axes = input_29_axes_0, beta = layers_1_final_layer_norm_bias_to_fp16, epsilon = var_217_to_fp16, gamma = layers_1_final_layer_norm_weight_to_fp16, x = input_27_cast_fp16)[name = tensor("input_29_cast_fp16")]; tensor layers_1_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(12657600))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14263296))), name = tensor("layers_1_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_1_fc1_bias_to_fp16 = const()[name = tensor("layers_1_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14263424)))]; tensor linear_11_cast_fp16 = linear(bias = layers_1_fc1_bias_to_fp16, weight = layers_1_fc1_weight_to_fp16_palettized, x = input_29_cast_fp16)[name = tensor("linear_11_cast_fp16")]; tensor input_31_mode_0 = const()[name = tensor("input_31_mode_0"), val = tensor("EXACT")]; tensor input_31_cast_fp16 = gelu(mode = input_31_mode_0, x = linear_11_cast_fp16)[name = tensor("input_31_cast_fp16")]; tensor layers_1_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(14270656))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15876352))), name = tensor("layers_1_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_1_fc2_bias_to_fp16 = const()[name = tensor("layers_1_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15876480)))]; tensor linear_12_cast_fp16 = linear(bias = layers_1_fc2_bias_to_fp16, weight = layers_1_fc2_weight_to_fp16_palettized, x = input_31_cast_fp16)[name = tensor("linear_12_cast_fp16")]; tensor input_33_cast_fp16 = add(x = input_27_cast_fp16, y = linear_12_cast_fp16)[name = tensor("input_33_cast_fp16")]; tensor var_284 = const()[name = tensor("op_284"), val = tensor(-1)]; tensor x_17_axes_0 = const()[name = tensor("x_17_axes_0"), val = tensor([-1])]; tensor layers_2_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_2_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15878336)))]; tensor layers_2_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15880192)))]; tensor var_287_to_fp16 = const()[name = tensor("op_287_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_17_cast_fp16 = layer_norm(axes = x_17_axes_0, beta = layers_2_self_attn_layer_norm_bias_to_fp16, epsilon = var_287_to_fp16, gamma = layers_2_self_attn_layer_norm_weight_to_fp16, x = input_33_cast_fp16)[name = tensor("x_17_cast_fp16")]; tensor layers_2_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(15882048))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16283520))), name = tensor("layers_2_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_2_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16283648)))]; tensor linear_13_cast_fp16 = linear(bias = layers_2_self_attn_q_proj_bias_to_fp16, weight = layers_2_self_attn_q_proj_weight_to_fp16_palettized, x = x_17_cast_fp16)[name = tensor("linear_13_cast_fp16")]; tensor concat_10x = const()[name = tensor("concat_10x"), val = tensor([1, -1, 14, 64])]; tensor var_308_cast_fp16 = reshape(shape = concat_10x, x = linear_13_cast_fp16)[name = tensor("op_308_cast_fp16")]; tensor layers_2_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16285504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16686976))), name = tensor("layers_2_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_2_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16687104)))]; tensor linear_14_cast_fp16 = linear(bias = layers_2_self_attn_k_proj_bias_to_fp16, weight = layers_2_self_attn_k_proj_weight_to_fp16_palettized, x = x_17_cast_fp16)[name = tensor("linear_14_cast_fp16")]; tensor concat_11x = const()[name = tensor("concat_11x"), val = tensor([1, -1, 14, 64])]; tensor var_314_cast_fp16 = reshape(shape = concat_11x, x = linear_14_cast_fp16)[name = tensor("op_314_cast_fp16")]; tensor layers_2_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(16688960))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17090432))), name = tensor("layers_2_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_2_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17090560)))]; tensor linear_15_cast_fp16 = linear(bias = layers_2_self_attn_v_proj_bias_to_fp16, weight = layers_2_self_attn_v_proj_weight_to_fp16_palettized, x = x_17_cast_fp16)[name = tensor("linear_15_cast_fp16")]; tensor concat_12x = const()[name = tensor("concat_12x"), val = tensor([1, -1, 14, 64])]; tensor var_320_cast_fp16 = reshape(shape = concat_12x, x = linear_15_cast_fp16)[name = tensor("op_320_cast_fp16")]; tensor v_5_perm_0 = const()[name = tensor("v_5_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_323_transpose_x_0 = const()[name = tensor("op_323_transpose_x_0"), val = tensor(false)]; tensor var_323_transpose_y_0 = const()[name = tensor("op_323_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 = var_314_cast_fp16)[name = tensor("transpose_170")]; tensor transpose_76 = transpose(perm = transpose_76_perm_0, x = var_308_cast_fp16)[name = tensor("transpose_171")]; tensor var_323_cast_fp16 = matmul(transpose_x = var_323_transpose_x_0, transpose_y = var_323_transpose_y_0, x = transpose_76, y = transpose_77)[name = tensor("op_323_cast_fp16")]; tensor var_324_to_fp16 = const()[name = tensor("op_324_to_fp16"), val = tensor(0x1p-3)]; tensor input_35_cast_fp16 = mul(x = var_323_cast_fp16, y = var_324_to_fp16)[name = tensor("input_35_cast_fp16")]; tensor attn_5_cast_fp16 = softmax(axis = var_284, x = input_35_cast_fp16)[name = tensor("attn_5_cast_fp16")]; tensor out_5_transpose_x_0 = const()[name = tensor("out_5_transpose_x_0"), val = tensor(false)]; tensor out_5_transpose_y_0 = const()[name = tensor("out_5_transpose_y_0"), val = tensor(false)]; tensor v_5_cast_fp16 = transpose(perm = v_5_perm_0, x = var_320_cast_fp16)[name = tensor("transpose_169")]; tensor out_5_cast_fp16 = matmul(transpose_x = out_5_transpose_x_0, transpose_y = out_5_transpose_y_0, x = attn_5_cast_fp16, y = v_5_cast_fp16)[name = tensor("out_5_cast_fp16")]; tensor var_328_perm_0 = const()[name = tensor("op_328_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_13x = const()[name = tensor("concat_13x"), val = tensor([1, -1, 896])]; tensor var_328_cast_fp16 = transpose(perm = var_328_perm_0, x = out_5_cast_fp16)[name = tensor("transpose_168")]; tensor input_37_cast_fp16 = reshape(shape = concat_13x, x = var_328_cast_fp16)[name = tensor("input_37_cast_fp16")]; tensor layers_2_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17092416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17493888))), name = tensor("layers_2_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_2_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_2_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17494016)))]; tensor linear_16_cast_fp16 = linear(bias = layers_2_self_attn_out_proj_bias_to_fp16, weight = layers_2_self_attn_out_proj_weight_to_fp16_palettized, x = input_37_cast_fp16)[name = tensor("linear_16_cast_fp16")]; tensor input_39_cast_fp16 = add(x = input_33_cast_fp16, y = linear_16_cast_fp16)[name = tensor("input_39_cast_fp16")]; tensor input_41_axes_0 = const()[name = tensor("input_41_axes_0"), val = tensor([-1])]; tensor layers_2_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_2_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17495872)))]; tensor layers_2_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_2_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17497728)))]; tensor input_41_cast_fp16 = layer_norm(axes = input_41_axes_0, beta = layers_2_final_layer_norm_bias_to_fp16, epsilon = var_287_to_fp16, gamma = layers_2_final_layer_norm_weight_to_fp16, x = input_39_cast_fp16)[name = tensor("input_41_cast_fp16")]; tensor layers_2_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(17499584))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19105280))), name = tensor("layers_2_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_2_fc1_bias_to_fp16 = const()[name = tensor("layers_2_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19105408)))]; tensor linear_17_cast_fp16 = linear(bias = layers_2_fc1_bias_to_fp16, weight = layers_2_fc1_weight_to_fp16_palettized, x = input_41_cast_fp16)[name = tensor("linear_17_cast_fp16")]; tensor input_43_mode_0 = const()[name = tensor("input_43_mode_0"), val = tensor("EXACT")]; tensor input_43_cast_fp16 = gelu(mode = input_43_mode_0, x = linear_17_cast_fp16)[name = tensor("input_43_cast_fp16")]; tensor layers_2_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(19112640))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20718336))), name = tensor("layers_2_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_2_fc2_bias_to_fp16 = const()[name = tensor("layers_2_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20718464)))]; tensor linear_18_cast_fp16 = linear(bias = layers_2_fc2_bias_to_fp16, weight = layers_2_fc2_weight_to_fp16_palettized, x = input_43_cast_fp16)[name = tensor("linear_18_cast_fp16")]; tensor input_45_cast_fp16 = add(x = input_39_cast_fp16, y = linear_18_cast_fp16)[name = tensor("input_45_cast_fp16")]; tensor var_354 = const()[name = tensor("op_354"), val = tensor(-1)]; tensor x_23_axes_0 = const()[name = tensor("x_23_axes_0"), val = tensor([-1])]; tensor layers_3_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_3_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20720320)))]; tensor layers_3_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20722176)))]; tensor var_357_to_fp16 = const()[name = tensor("op_357_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_23_cast_fp16 = layer_norm(axes = x_23_axes_0, beta = layers_3_self_attn_layer_norm_bias_to_fp16, epsilon = var_357_to_fp16, gamma = layers_3_self_attn_layer_norm_weight_to_fp16, x = input_45_cast_fp16)[name = tensor("x_23_cast_fp16")]; tensor layers_3_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(20724032))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21125504))), name = tensor("layers_3_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_3_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21125632)))]; tensor linear_19_cast_fp16 = linear(bias = layers_3_self_attn_q_proj_bias_to_fp16, weight = layers_3_self_attn_q_proj_weight_to_fp16_palettized, x = x_23_cast_fp16)[name = tensor("linear_19_cast_fp16")]; tensor concat_14x = const()[name = tensor("concat_14x"), val = tensor([1, -1, 14, 64])]; tensor var_378_cast_fp16 = reshape(shape = concat_14x, x = linear_19_cast_fp16)[name = tensor("op_378_cast_fp16")]; tensor layers_3_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21127488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21528960))), name = tensor("layers_3_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_3_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21529088)))]; tensor linear_20_cast_fp16 = linear(bias = layers_3_self_attn_k_proj_bias_to_fp16, weight = layers_3_self_attn_k_proj_weight_to_fp16_palettized, x = x_23_cast_fp16)[name = tensor("linear_20_cast_fp16")]; tensor concat_15x = const()[name = tensor("concat_15x"), val = tensor([1, -1, 14, 64])]; tensor var_384_cast_fp16 = reshape(shape = concat_15x, x = linear_20_cast_fp16)[name = tensor("op_384_cast_fp16")]; tensor layers_3_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21530944))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21932416))), name = tensor("layers_3_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_3_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21932544)))]; tensor linear_21_cast_fp16 = linear(bias = layers_3_self_attn_v_proj_bias_to_fp16, weight = layers_3_self_attn_v_proj_weight_to_fp16_palettized, x = x_23_cast_fp16)[name = tensor("linear_21_cast_fp16")]; tensor concat_16x = const()[name = tensor("concat_16x"), val = tensor([1, -1, 14, 64])]; tensor var_390_cast_fp16 = reshape(shape = concat_16x, x = linear_21_cast_fp16)[name = tensor("op_390_cast_fp16")]; tensor v_7_perm_0 = const()[name = tensor("v_7_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_393_transpose_x_0 = const()[name = tensor("op_393_transpose_x_0"), val = tensor(false)]; tensor var_393_transpose_y_0 = const()[name = tensor("op_393_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 = var_384_cast_fp16)[name = tensor("transpose_166")]; tensor transpose_78 = transpose(perm = transpose_78_perm_0, x = var_378_cast_fp16)[name = tensor("transpose_167")]; tensor var_393_cast_fp16 = matmul(transpose_x = var_393_transpose_x_0, transpose_y = var_393_transpose_y_0, x = transpose_78, y = transpose_79)[name = tensor("op_393_cast_fp16")]; tensor var_394_to_fp16 = const()[name = tensor("op_394_to_fp16"), val = tensor(0x1p-3)]; tensor input_47_cast_fp16 = mul(x = var_393_cast_fp16, y = var_394_to_fp16)[name = tensor("input_47_cast_fp16")]; tensor attn_7_cast_fp16 = softmax(axis = var_354, x = input_47_cast_fp16)[name = tensor("attn_7_cast_fp16")]; tensor out_7_transpose_x_0 = const()[name = tensor("out_7_transpose_x_0"), val = tensor(false)]; tensor out_7_transpose_y_0 = const()[name = tensor("out_7_transpose_y_0"), val = tensor(false)]; tensor v_7_cast_fp16 = transpose(perm = v_7_perm_0, x = var_390_cast_fp16)[name = tensor("transpose_165")]; tensor out_7_cast_fp16 = matmul(transpose_x = out_7_transpose_x_0, transpose_y = out_7_transpose_y_0, x = attn_7_cast_fp16, y = v_7_cast_fp16)[name = tensor("out_7_cast_fp16")]; tensor var_398_perm_0 = const()[name = tensor("op_398_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_17x = const()[name = tensor("concat_17x"), val = tensor([1, -1, 896])]; tensor var_398_cast_fp16 = transpose(perm = var_398_perm_0, x = out_7_cast_fp16)[name = tensor("transpose_164")]; tensor input_49_cast_fp16 = reshape(shape = concat_17x, x = var_398_cast_fp16)[name = tensor("input_49_cast_fp16")]; tensor layers_3_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(21934400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22335872))), name = tensor("layers_3_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_3_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_3_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22336000)))]; tensor linear_22_cast_fp16 = linear(bias = layers_3_self_attn_out_proj_bias_to_fp16, weight = layers_3_self_attn_out_proj_weight_to_fp16_palettized, x = input_49_cast_fp16)[name = tensor("linear_22_cast_fp16")]; tensor input_51_cast_fp16 = add(x = input_45_cast_fp16, y = linear_22_cast_fp16)[name = tensor("input_51_cast_fp16")]; tensor input_53_axes_0 = const()[name = tensor("input_53_axes_0"), val = tensor([-1])]; tensor layers_3_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_3_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22337856)))]; tensor layers_3_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_3_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22339712)))]; tensor input_53_cast_fp16 = layer_norm(axes = input_53_axes_0, beta = layers_3_final_layer_norm_bias_to_fp16, epsilon = var_357_to_fp16, gamma = layers_3_final_layer_norm_weight_to_fp16, x = input_51_cast_fp16)[name = tensor("input_53_cast_fp16")]; tensor layers_3_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(22341568))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23947264))), name = tensor("layers_3_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_3_fc1_bias_to_fp16 = const()[name = tensor("layers_3_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23947392)))]; tensor linear_23_cast_fp16 = linear(bias = layers_3_fc1_bias_to_fp16, weight = layers_3_fc1_weight_to_fp16_palettized, x = input_53_cast_fp16)[name = tensor("linear_23_cast_fp16")]; tensor input_55_mode_0 = const()[name = tensor("input_55_mode_0"), val = tensor("EXACT")]; tensor input_55_cast_fp16 = gelu(mode = input_55_mode_0, x = linear_23_cast_fp16)[name = tensor("input_55_cast_fp16")]; tensor layers_3_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(23954624))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25560320))), name = tensor("layers_3_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_3_fc2_bias_to_fp16 = const()[name = tensor("layers_3_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25560448)))]; tensor linear_24_cast_fp16 = linear(bias = layers_3_fc2_bias_to_fp16, weight = layers_3_fc2_weight_to_fp16_palettized, x = input_55_cast_fp16)[name = tensor("linear_24_cast_fp16")]; tensor input_57_cast_fp16 = add(x = input_51_cast_fp16, y = linear_24_cast_fp16)[name = tensor("input_57_cast_fp16")]; tensor var_424 = const()[name = tensor("op_424"), val = tensor(-1)]; tensor x_29_axes_0 = const()[name = tensor("x_29_axes_0"), val = tensor([-1])]; tensor layers_4_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_4_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25562304)))]; tensor layers_4_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25564160)))]; tensor var_427_to_fp16 = const()[name = tensor("op_427_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_29_cast_fp16 = layer_norm(axes = x_29_axes_0, beta = layers_4_self_attn_layer_norm_bias_to_fp16, epsilon = var_427_to_fp16, gamma = layers_4_self_attn_layer_norm_weight_to_fp16, x = input_57_cast_fp16)[name = tensor("x_29_cast_fp16")]; tensor layers_4_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25566016))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25967488))), name = tensor("layers_4_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_4_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25967616)))]; tensor linear_25_cast_fp16 = linear(bias = layers_4_self_attn_q_proj_bias_to_fp16, weight = layers_4_self_attn_q_proj_weight_to_fp16_palettized, x = x_29_cast_fp16)[name = tensor("linear_25_cast_fp16")]; tensor concat_18x = const()[name = tensor("concat_18x"), val = tensor([1, -1, 14, 64])]; tensor var_448_cast_fp16 = reshape(shape = concat_18x, x = linear_25_cast_fp16)[name = tensor("op_448_cast_fp16")]; tensor layers_4_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(25969472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26370944))), name = tensor("layers_4_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_4_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26371072)))]; tensor linear_26_cast_fp16 = linear(bias = layers_4_self_attn_k_proj_bias_to_fp16, weight = layers_4_self_attn_k_proj_weight_to_fp16_palettized, x = x_29_cast_fp16)[name = tensor("linear_26_cast_fp16")]; tensor concat_19x = const()[name = tensor("concat_19x"), val = tensor([1, -1, 14, 64])]; tensor var_454_cast_fp16 = reshape(shape = concat_19x, x = linear_26_cast_fp16)[name = tensor("op_454_cast_fp16")]; tensor layers_4_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26372928))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26774400))), name = tensor("layers_4_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_4_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26774528)))]; tensor linear_27_cast_fp16 = linear(bias = layers_4_self_attn_v_proj_bias_to_fp16, weight = layers_4_self_attn_v_proj_weight_to_fp16_palettized, x = x_29_cast_fp16)[name = tensor("linear_27_cast_fp16")]; tensor concat_20x = const()[name = tensor("concat_20x"), val = tensor([1, -1, 14, 64])]; tensor var_460_cast_fp16 = reshape(shape = concat_20x, x = linear_27_cast_fp16)[name = tensor("op_460_cast_fp16")]; tensor v_9_perm_0 = const()[name = tensor("v_9_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_463_transpose_x_0 = const()[name = tensor("op_463_transpose_x_0"), val = tensor(false)]; tensor var_463_transpose_y_0 = const()[name = tensor("op_463_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 = var_454_cast_fp16)[name = tensor("transpose_162")]; tensor transpose_80 = transpose(perm = transpose_80_perm_0, x = var_448_cast_fp16)[name = tensor("transpose_163")]; tensor var_463_cast_fp16 = matmul(transpose_x = var_463_transpose_x_0, transpose_y = var_463_transpose_y_0, x = transpose_80, y = transpose_81)[name = tensor("op_463_cast_fp16")]; tensor var_464_to_fp16 = const()[name = tensor("op_464_to_fp16"), val = tensor(0x1p-3)]; tensor input_59_cast_fp16 = mul(x = var_463_cast_fp16, y = var_464_to_fp16)[name = tensor("input_59_cast_fp16")]; tensor attn_9_cast_fp16 = softmax(axis = var_424, x = input_59_cast_fp16)[name = tensor("attn_9_cast_fp16")]; tensor out_9_transpose_x_0 = const()[name = tensor("out_9_transpose_x_0"), val = tensor(false)]; tensor out_9_transpose_y_0 = const()[name = tensor("out_9_transpose_y_0"), val = tensor(false)]; tensor v_9_cast_fp16 = transpose(perm = v_9_perm_0, x = var_460_cast_fp16)[name = tensor("transpose_161")]; tensor out_9_cast_fp16 = matmul(transpose_x = out_9_transpose_x_0, transpose_y = out_9_transpose_y_0, x = attn_9_cast_fp16, y = v_9_cast_fp16)[name = tensor("out_9_cast_fp16")]; tensor var_468_perm_0 = const()[name = tensor("op_468_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_21x = const()[name = tensor("concat_21x"), val = tensor([1, -1, 896])]; tensor var_468_cast_fp16 = transpose(perm = var_468_perm_0, x = out_9_cast_fp16)[name = tensor("transpose_160")]; tensor input_61_cast_fp16 = reshape(shape = concat_21x, x = var_468_cast_fp16)[name = tensor("input_61_cast_fp16")]; tensor layers_4_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(26776384))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27177856))), name = tensor("layers_4_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_4_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_4_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27177984)))]; tensor linear_28_cast_fp16 = linear(bias = layers_4_self_attn_out_proj_bias_to_fp16, weight = layers_4_self_attn_out_proj_weight_to_fp16_palettized, x = input_61_cast_fp16)[name = tensor("linear_28_cast_fp16")]; tensor input_63_cast_fp16 = add(x = input_57_cast_fp16, y = linear_28_cast_fp16)[name = tensor("input_63_cast_fp16")]; tensor input_65_axes_0 = const()[name = tensor("input_65_axes_0"), val = tensor([-1])]; tensor layers_4_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_4_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27179840)))]; tensor layers_4_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_4_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27181696)))]; tensor input_65_cast_fp16 = layer_norm(axes = input_65_axes_0, beta = layers_4_final_layer_norm_bias_to_fp16, epsilon = var_427_to_fp16, gamma = layers_4_final_layer_norm_weight_to_fp16, x = input_63_cast_fp16)[name = tensor("input_65_cast_fp16")]; tensor layers_4_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(27183552))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28789248))), name = tensor("layers_4_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_4_fc1_bias_to_fp16 = const()[name = tensor("layers_4_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28789376)))]; tensor linear_29_cast_fp16 = linear(bias = layers_4_fc1_bias_to_fp16, weight = layers_4_fc1_weight_to_fp16_palettized, x = input_65_cast_fp16)[name = tensor("linear_29_cast_fp16")]; tensor input_67_mode_0 = const()[name = tensor("input_67_mode_0"), val = tensor("EXACT")]; tensor input_67_cast_fp16 = gelu(mode = input_67_mode_0, x = linear_29_cast_fp16)[name = tensor("input_67_cast_fp16")]; tensor layers_4_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(28796608))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30402304))), name = tensor("layers_4_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_4_fc2_bias_to_fp16 = const()[name = tensor("layers_4_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30402432)))]; tensor linear_30_cast_fp16 = linear(bias = layers_4_fc2_bias_to_fp16, weight = layers_4_fc2_weight_to_fp16_palettized, x = input_67_cast_fp16)[name = tensor("linear_30_cast_fp16")]; tensor input_69_cast_fp16 = add(x = input_63_cast_fp16, y = linear_30_cast_fp16)[name = tensor("input_69_cast_fp16")]; tensor var_494 = const()[name = tensor("op_494"), val = tensor(-1)]; tensor x_35_axes_0 = const()[name = tensor("x_35_axes_0"), val = tensor([-1])]; tensor layers_5_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_5_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30404288)))]; tensor layers_5_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30406144)))]; tensor var_497_to_fp16 = const()[name = tensor("op_497_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_35_cast_fp16 = layer_norm(axes = x_35_axes_0, beta = layers_5_self_attn_layer_norm_bias_to_fp16, epsilon = var_497_to_fp16, gamma = layers_5_self_attn_layer_norm_weight_to_fp16, x = input_69_cast_fp16)[name = tensor("x_35_cast_fp16")]; tensor layers_5_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30408000))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30809472))), name = tensor("layers_5_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_5_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30809600)))]; tensor linear_31_cast_fp16 = linear(bias = layers_5_self_attn_q_proj_bias_to_fp16, weight = layers_5_self_attn_q_proj_weight_to_fp16_palettized, x = x_35_cast_fp16)[name = tensor("linear_31_cast_fp16")]; tensor concat_22x = const()[name = tensor("concat_22x"), val = tensor([1, -1, 14, 64])]; tensor var_518_cast_fp16 = reshape(shape = concat_22x, x = linear_31_cast_fp16)[name = tensor("op_518_cast_fp16")]; tensor layers_5_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(30811456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31212928))), name = tensor("layers_5_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_5_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31213056)))]; tensor linear_32_cast_fp16 = linear(bias = layers_5_self_attn_k_proj_bias_to_fp16, weight = layers_5_self_attn_k_proj_weight_to_fp16_palettized, x = x_35_cast_fp16)[name = tensor("linear_32_cast_fp16")]; tensor concat_23x = const()[name = tensor("concat_23x"), val = tensor([1, -1, 14, 64])]; tensor var_524_cast_fp16 = reshape(shape = concat_23x, x = linear_32_cast_fp16)[name = tensor("op_524_cast_fp16")]; tensor layers_5_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31214912))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31616384))), name = tensor("layers_5_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_5_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31616512)))]; tensor linear_33_cast_fp16 = linear(bias = layers_5_self_attn_v_proj_bias_to_fp16, weight = layers_5_self_attn_v_proj_weight_to_fp16_palettized, x = x_35_cast_fp16)[name = tensor("linear_33_cast_fp16")]; tensor concat_24x = const()[name = tensor("concat_24x"), val = tensor([1, -1, 14, 64])]; tensor var_530_cast_fp16 = reshape(shape = concat_24x, x = linear_33_cast_fp16)[name = tensor("op_530_cast_fp16")]; tensor v_11_perm_0 = const()[name = tensor("v_11_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_533_transpose_x_0 = const()[name = tensor("op_533_transpose_x_0"), val = tensor(false)]; tensor var_533_transpose_y_0 = const()[name = tensor("op_533_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 = var_524_cast_fp16)[name = tensor("transpose_158")]; tensor transpose_82 = transpose(perm = transpose_82_perm_0, x = var_518_cast_fp16)[name = tensor("transpose_159")]; tensor var_533_cast_fp16 = matmul(transpose_x = var_533_transpose_x_0, transpose_y = var_533_transpose_y_0, x = transpose_82, y = transpose_83)[name = tensor("op_533_cast_fp16")]; tensor var_534_to_fp16 = const()[name = tensor("op_534_to_fp16"), val = tensor(0x1p-3)]; tensor input_71_cast_fp16 = mul(x = var_533_cast_fp16, y = var_534_to_fp16)[name = tensor("input_71_cast_fp16")]; tensor attn_11_cast_fp16 = softmax(axis = var_494, x = input_71_cast_fp16)[name = tensor("attn_11_cast_fp16")]; tensor out_11_transpose_x_0 = const()[name = tensor("out_11_transpose_x_0"), val = tensor(false)]; tensor out_11_transpose_y_0 = const()[name = tensor("out_11_transpose_y_0"), val = tensor(false)]; tensor v_11_cast_fp16 = transpose(perm = v_11_perm_0, x = var_530_cast_fp16)[name = tensor("transpose_157")]; tensor out_11_cast_fp16 = matmul(transpose_x = out_11_transpose_x_0, transpose_y = out_11_transpose_y_0, x = attn_11_cast_fp16, y = v_11_cast_fp16)[name = tensor("out_11_cast_fp16")]; tensor var_538_perm_0 = const()[name = tensor("op_538_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_25x = const()[name = tensor("concat_25x"), val = tensor([1, -1, 896])]; tensor var_538_cast_fp16 = transpose(perm = var_538_perm_0, x = out_11_cast_fp16)[name = tensor("transpose_156")]; tensor input_73_cast_fp16 = reshape(shape = concat_25x, x = var_538_cast_fp16)[name = tensor("input_73_cast_fp16")]; tensor layers_5_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(31618368))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32019840))), name = tensor("layers_5_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_5_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_5_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32019968)))]; tensor linear_34_cast_fp16 = linear(bias = layers_5_self_attn_out_proj_bias_to_fp16, weight = layers_5_self_attn_out_proj_weight_to_fp16_palettized, x = input_73_cast_fp16)[name = tensor("linear_34_cast_fp16")]; tensor input_75_cast_fp16 = add(x = input_69_cast_fp16, y = linear_34_cast_fp16)[name = tensor("input_75_cast_fp16")]; tensor input_77_axes_0 = const()[name = tensor("input_77_axes_0"), val = tensor([-1])]; tensor layers_5_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_5_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32021824)))]; tensor layers_5_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_5_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32023680)))]; tensor input_77_cast_fp16 = layer_norm(axes = input_77_axes_0, beta = layers_5_final_layer_norm_bias_to_fp16, epsilon = var_497_to_fp16, gamma = layers_5_final_layer_norm_weight_to_fp16, x = input_75_cast_fp16)[name = tensor("input_77_cast_fp16")]; tensor layers_5_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(32025536))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33631232))), name = tensor("layers_5_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_5_fc1_bias_to_fp16 = const()[name = tensor("layers_5_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33631360)))]; tensor linear_35_cast_fp16 = linear(bias = layers_5_fc1_bias_to_fp16, weight = layers_5_fc1_weight_to_fp16_palettized, x = input_77_cast_fp16)[name = tensor("linear_35_cast_fp16")]; tensor input_79_mode_0 = const()[name = tensor("input_79_mode_0"), val = tensor("EXACT")]; tensor input_79_cast_fp16 = gelu(mode = input_79_mode_0, x = linear_35_cast_fp16)[name = tensor("input_79_cast_fp16")]; tensor layers_5_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(33638592))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35244288))), name = tensor("layers_5_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_5_fc2_bias_to_fp16 = const()[name = tensor("layers_5_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35244416)))]; tensor linear_36_cast_fp16 = linear(bias = layers_5_fc2_bias_to_fp16, weight = layers_5_fc2_weight_to_fp16_palettized, x = input_79_cast_fp16)[name = tensor("linear_36_cast_fp16")]; tensor input_81_cast_fp16 = add(x = input_75_cast_fp16, y = linear_36_cast_fp16)[name = tensor("input_81_cast_fp16")]; tensor var_564 = const()[name = tensor("op_564"), val = tensor(-1)]; tensor x_41_axes_0 = const()[name = tensor("x_41_axes_0"), val = tensor([-1])]; tensor layers_6_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_6_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35246272)))]; tensor layers_6_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35248128)))]; tensor var_567_to_fp16 = const()[name = tensor("op_567_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_41_cast_fp16 = layer_norm(axes = x_41_axes_0, beta = layers_6_self_attn_layer_norm_bias_to_fp16, epsilon = var_567_to_fp16, gamma = layers_6_self_attn_layer_norm_weight_to_fp16, x = input_81_cast_fp16)[name = tensor("x_41_cast_fp16")]; tensor layers_6_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35249984))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35651456))), name = tensor("layers_6_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_6_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35651584)))]; tensor linear_37_cast_fp16 = linear(bias = layers_6_self_attn_q_proj_bias_to_fp16, weight = layers_6_self_attn_q_proj_weight_to_fp16_palettized, x = x_41_cast_fp16)[name = tensor("linear_37_cast_fp16")]; tensor concat_26x = const()[name = tensor("concat_26x"), val = tensor([1, -1, 14, 64])]; tensor var_588_cast_fp16 = reshape(shape = concat_26x, x = linear_37_cast_fp16)[name = tensor("op_588_cast_fp16")]; tensor layers_6_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(35653440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36054912))), name = tensor("layers_6_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_6_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36055040)))]; tensor linear_38_cast_fp16 = linear(bias = layers_6_self_attn_k_proj_bias_to_fp16, weight = layers_6_self_attn_k_proj_weight_to_fp16_palettized, x = x_41_cast_fp16)[name = tensor("linear_38_cast_fp16")]; tensor concat_27x = const()[name = tensor("concat_27x"), val = tensor([1, -1, 14, 64])]; tensor var_594_cast_fp16 = reshape(shape = concat_27x, x = linear_38_cast_fp16)[name = tensor("op_594_cast_fp16")]; tensor layers_6_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36056896))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36458368))), name = tensor("layers_6_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_6_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36458496)))]; tensor linear_39_cast_fp16 = linear(bias = layers_6_self_attn_v_proj_bias_to_fp16, weight = layers_6_self_attn_v_proj_weight_to_fp16_palettized, x = x_41_cast_fp16)[name = tensor("linear_39_cast_fp16")]; tensor concat_28x = const()[name = tensor("concat_28x"), val = tensor([1, -1, 14, 64])]; tensor var_600_cast_fp16 = reshape(shape = concat_28x, x = linear_39_cast_fp16)[name = tensor("op_600_cast_fp16")]; tensor v_13_perm_0 = const()[name = tensor("v_13_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_603_transpose_x_0 = const()[name = tensor("op_603_transpose_x_0"), val = tensor(false)]; tensor var_603_transpose_y_0 = const()[name = tensor("op_603_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 = var_594_cast_fp16)[name = tensor("transpose_154")]; tensor transpose_84 = transpose(perm = transpose_84_perm_0, x = var_588_cast_fp16)[name = tensor("transpose_155")]; tensor var_603_cast_fp16 = matmul(transpose_x = var_603_transpose_x_0, transpose_y = var_603_transpose_y_0, x = transpose_84, y = transpose_85)[name = tensor("op_603_cast_fp16")]; tensor var_604_to_fp16 = const()[name = tensor("op_604_to_fp16"), val = tensor(0x1p-3)]; tensor input_83_cast_fp16 = mul(x = var_603_cast_fp16, y = var_604_to_fp16)[name = tensor("input_83_cast_fp16")]; tensor attn_13_cast_fp16 = softmax(axis = var_564, x = input_83_cast_fp16)[name = tensor("attn_13_cast_fp16")]; tensor out_13_transpose_x_0 = const()[name = tensor("out_13_transpose_x_0"), val = tensor(false)]; tensor out_13_transpose_y_0 = const()[name = tensor("out_13_transpose_y_0"), val = tensor(false)]; tensor v_13_cast_fp16 = transpose(perm = v_13_perm_0, x = var_600_cast_fp16)[name = tensor("transpose_153")]; tensor out_13_cast_fp16 = matmul(transpose_x = out_13_transpose_x_0, transpose_y = out_13_transpose_y_0, x = attn_13_cast_fp16, y = v_13_cast_fp16)[name = tensor("out_13_cast_fp16")]; tensor var_608_perm_0 = const()[name = tensor("op_608_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_29x = const()[name = tensor("concat_29x"), val = tensor([1, -1, 896])]; tensor var_608_cast_fp16 = transpose(perm = var_608_perm_0, x = out_13_cast_fp16)[name = tensor("transpose_152")]; tensor input_85_cast_fp16 = reshape(shape = concat_29x, x = var_608_cast_fp16)[name = tensor("input_85_cast_fp16")]; tensor layers_6_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36460352))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36861824))), name = tensor("layers_6_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_6_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_6_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36861952)))]; tensor linear_40_cast_fp16 = linear(bias = layers_6_self_attn_out_proj_bias_to_fp16, weight = layers_6_self_attn_out_proj_weight_to_fp16_palettized, x = input_85_cast_fp16)[name = tensor("linear_40_cast_fp16")]; tensor input_87_cast_fp16 = add(x = input_81_cast_fp16, y = linear_40_cast_fp16)[name = tensor("input_87_cast_fp16")]; tensor input_89_axes_0 = const()[name = tensor("input_89_axes_0"), val = tensor([-1])]; tensor layers_6_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_6_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36863808)))]; tensor layers_6_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_6_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36865664)))]; tensor input_89_cast_fp16 = layer_norm(axes = input_89_axes_0, beta = layers_6_final_layer_norm_bias_to_fp16, epsilon = var_567_to_fp16, gamma = layers_6_final_layer_norm_weight_to_fp16, x = input_87_cast_fp16)[name = tensor("input_89_cast_fp16")]; tensor layers_6_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(36867520))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38473216))), name = tensor("layers_6_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_6_fc1_bias_to_fp16 = const()[name = tensor("layers_6_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38473344)))]; tensor linear_41_cast_fp16 = linear(bias = layers_6_fc1_bias_to_fp16, weight = layers_6_fc1_weight_to_fp16_palettized, x = input_89_cast_fp16)[name = tensor("linear_41_cast_fp16")]; tensor input_91_mode_0 = const()[name = tensor("input_91_mode_0"), val = tensor("EXACT")]; tensor input_91_cast_fp16 = gelu(mode = input_91_mode_0, x = linear_41_cast_fp16)[name = tensor("input_91_cast_fp16")]; tensor layers_6_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(38480576))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40086272))), name = tensor("layers_6_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_6_fc2_bias_to_fp16 = const()[name = tensor("layers_6_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40086400)))]; tensor linear_42_cast_fp16 = linear(bias = layers_6_fc2_bias_to_fp16, weight = layers_6_fc2_weight_to_fp16_palettized, x = input_91_cast_fp16)[name = tensor("linear_42_cast_fp16")]; tensor input_93_cast_fp16 = add(x = input_87_cast_fp16, y = linear_42_cast_fp16)[name = tensor("input_93_cast_fp16")]; tensor var_634 = const()[name = tensor("op_634"), val = tensor(-1)]; tensor x_47_axes_0 = const()[name = tensor("x_47_axes_0"), val = tensor([-1])]; tensor layers_7_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_7_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40088256)))]; tensor layers_7_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40090112)))]; tensor var_637_to_fp16 = const()[name = tensor("op_637_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_47_cast_fp16 = layer_norm(axes = x_47_axes_0, beta = layers_7_self_attn_layer_norm_bias_to_fp16, epsilon = var_637_to_fp16, gamma = layers_7_self_attn_layer_norm_weight_to_fp16, x = input_93_cast_fp16)[name = tensor("x_47_cast_fp16")]; tensor layers_7_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40091968))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40493440))), name = tensor("layers_7_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_7_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40493568)))]; tensor linear_43_cast_fp16 = linear(bias = layers_7_self_attn_q_proj_bias_to_fp16, weight = layers_7_self_attn_q_proj_weight_to_fp16_palettized, x = x_47_cast_fp16)[name = tensor("linear_43_cast_fp16")]; tensor concat_30x = const()[name = tensor("concat_30x"), val = tensor([1, -1, 14, 64])]; tensor var_658_cast_fp16 = reshape(shape = concat_30x, x = linear_43_cast_fp16)[name = tensor("op_658_cast_fp16")]; tensor layers_7_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40495424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40896896))), name = tensor("layers_7_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_7_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40897024)))]; tensor linear_44_cast_fp16 = linear(bias = layers_7_self_attn_k_proj_bias_to_fp16, weight = layers_7_self_attn_k_proj_weight_to_fp16_palettized, x = x_47_cast_fp16)[name = tensor("linear_44_cast_fp16")]; tensor concat_31x = const()[name = tensor("concat_31x"), val = tensor([1, -1, 14, 64])]; tensor var_664_cast_fp16 = reshape(shape = concat_31x, x = linear_44_cast_fp16)[name = tensor("op_664_cast_fp16")]; tensor layers_7_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(40898880))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41300352))), name = tensor("layers_7_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_7_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41300480)))]; tensor linear_45_cast_fp16 = linear(bias = layers_7_self_attn_v_proj_bias_to_fp16, weight = layers_7_self_attn_v_proj_weight_to_fp16_palettized, x = x_47_cast_fp16)[name = tensor("linear_45_cast_fp16")]; tensor concat_32x = const()[name = tensor("concat_32x"), val = tensor([1, -1, 14, 64])]; tensor var_670_cast_fp16 = reshape(shape = concat_32x, x = linear_45_cast_fp16)[name = tensor("op_670_cast_fp16")]; tensor v_15_perm_0 = const()[name = tensor("v_15_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_673_transpose_x_0 = const()[name = tensor("op_673_transpose_x_0"), val = tensor(false)]; tensor var_673_transpose_y_0 = const()[name = tensor("op_673_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 = var_664_cast_fp16)[name = tensor("transpose_150")]; tensor transpose_86 = transpose(perm = transpose_86_perm_0, x = var_658_cast_fp16)[name = tensor("transpose_151")]; tensor var_673_cast_fp16 = matmul(transpose_x = var_673_transpose_x_0, transpose_y = var_673_transpose_y_0, x = transpose_86, y = transpose_87)[name = tensor("op_673_cast_fp16")]; tensor var_674_to_fp16 = const()[name = tensor("op_674_to_fp16"), val = tensor(0x1p-3)]; tensor input_95_cast_fp16 = mul(x = var_673_cast_fp16, y = var_674_to_fp16)[name = tensor("input_95_cast_fp16")]; tensor attn_15_cast_fp16 = softmax(axis = var_634, x = input_95_cast_fp16)[name = tensor("attn_15_cast_fp16")]; tensor out_15_transpose_x_0 = const()[name = tensor("out_15_transpose_x_0"), val = tensor(false)]; tensor out_15_transpose_y_0 = const()[name = tensor("out_15_transpose_y_0"), val = tensor(false)]; tensor v_15_cast_fp16 = transpose(perm = v_15_perm_0, x = var_670_cast_fp16)[name = tensor("transpose_149")]; tensor out_15_cast_fp16 = matmul(transpose_x = out_15_transpose_x_0, transpose_y = out_15_transpose_y_0, x = attn_15_cast_fp16, y = v_15_cast_fp16)[name = tensor("out_15_cast_fp16")]; tensor var_678_perm_0 = const()[name = tensor("op_678_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_33x = const()[name = tensor("concat_33x"), val = tensor([1, -1, 896])]; tensor var_678_cast_fp16 = transpose(perm = var_678_perm_0, x = out_15_cast_fp16)[name = tensor("transpose_148")]; tensor input_97_cast_fp16 = reshape(shape = concat_33x, x = var_678_cast_fp16)[name = tensor("input_97_cast_fp16")]; tensor layers_7_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41302336))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41703808))), name = tensor("layers_7_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_7_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_7_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41703936)))]; tensor linear_46_cast_fp16 = linear(bias = layers_7_self_attn_out_proj_bias_to_fp16, weight = layers_7_self_attn_out_proj_weight_to_fp16_palettized, x = input_97_cast_fp16)[name = tensor("linear_46_cast_fp16")]; tensor input_99_cast_fp16 = add(x = input_93_cast_fp16, y = linear_46_cast_fp16)[name = tensor("input_99_cast_fp16")]; tensor input_101_axes_0 = const()[name = tensor("input_101_axes_0"), val = tensor([-1])]; tensor layers_7_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_7_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41705792)))]; tensor layers_7_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_7_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41707648)))]; tensor input_101_cast_fp16 = layer_norm(axes = input_101_axes_0, beta = layers_7_final_layer_norm_bias_to_fp16, epsilon = var_637_to_fp16, gamma = layers_7_final_layer_norm_weight_to_fp16, x = input_99_cast_fp16)[name = tensor("input_101_cast_fp16")]; tensor layers_7_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(41709504))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43315200))), name = tensor("layers_7_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_7_fc1_bias_to_fp16 = const()[name = tensor("layers_7_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43315328)))]; tensor linear_47_cast_fp16 = linear(bias = layers_7_fc1_bias_to_fp16, weight = layers_7_fc1_weight_to_fp16_palettized, x = input_101_cast_fp16)[name = tensor("linear_47_cast_fp16")]; tensor input_103_mode_0 = const()[name = tensor("input_103_mode_0"), val = tensor("EXACT")]; tensor input_103_cast_fp16 = gelu(mode = input_103_mode_0, x = linear_47_cast_fp16)[name = tensor("input_103_cast_fp16")]; tensor layers_7_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(43322560))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44928256))), name = tensor("layers_7_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_7_fc2_bias_to_fp16 = const()[name = tensor("layers_7_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44928384)))]; tensor linear_48_cast_fp16 = linear(bias = layers_7_fc2_bias_to_fp16, weight = layers_7_fc2_weight_to_fp16_palettized, x = input_103_cast_fp16)[name = tensor("linear_48_cast_fp16")]; tensor input_105_cast_fp16 = add(x = input_99_cast_fp16, y = linear_48_cast_fp16)[name = tensor("input_105_cast_fp16")]; tensor var_704 = const()[name = tensor("op_704"), val = tensor(-1)]; tensor x_53_axes_0 = const()[name = tensor("x_53_axes_0"), val = tensor([-1])]; tensor layers_8_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_8_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44930240)))]; tensor layers_8_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44932096)))]; tensor var_707_to_fp16 = const()[name = tensor("op_707_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_53_cast_fp16 = layer_norm(axes = x_53_axes_0, beta = layers_8_self_attn_layer_norm_bias_to_fp16, epsilon = var_707_to_fp16, gamma = layers_8_self_attn_layer_norm_weight_to_fp16, x = input_105_cast_fp16)[name = tensor("x_53_cast_fp16")]; tensor layers_8_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(44933952))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45335424))), name = tensor("layers_8_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_8_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45335552)))]; tensor linear_49_cast_fp16 = linear(bias = layers_8_self_attn_q_proj_bias_to_fp16, weight = layers_8_self_attn_q_proj_weight_to_fp16_palettized, x = x_53_cast_fp16)[name = tensor("linear_49_cast_fp16")]; tensor concat_34x = const()[name = tensor("concat_34x"), val = tensor([1, -1, 14, 64])]; tensor var_728_cast_fp16 = reshape(shape = concat_34x, x = linear_49_cast_fp16)[name = tensor("op_728_cast_fp16")]; tensor layers_8_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45337408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45738880))), name = tensor("layers_8_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_8_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45739008)))]; tensor linear_50_cast_fp16 = linear(bias = layers_8_self_attn_k_proj_bias_to_fp16, weight = layers_8_self_attn_k_proj_weight_to_fp16_palettized, x = x_53_cast_fp16)[name = tensor("linear_50_cast_fp16")]; tensor concat_35x = const()[name = tensor("concat_35x"), val = tensor([1, -1, 14, 64])]; tensor var_734_cast_fp16 = reshape(shape = concat_35x, x = linear_50_cast_fp16)[name = tensor("op_734_cast_fp16")]; tensor layers_8_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(45740864))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46142336))), name = tensor("layers_8_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_8_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46142464)))]; tensor linear_51_cast_fp16 = linear(bias = layers_8_self_attn_v_proj_bias_to_fp16, weight = layers_8_self_attn_v_proj_weight_to_fp16_palettized, x = x_53_cast_fp16)[name = tensor("linear_51_cast_fp16")]; tensor concat_36x = const()[name = tensor("concat_36x"), val = tensor([1, -1, 14, 64])]; tensor var_740_cast_fp16 = reshape(shape = concat_36x, x = linear_51_cast_fp16)[name = tensor("op_740_cast_fp16")]; tensor v_17_perm_0 = const()[name = tensor("v_17_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_743_transpose_x_0 = const()[name = tensor("op_743_transpose_x_0"), val = tensor(false)]; tensor var_743_transpose_y_0 = const()[name = tensor("op_743_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 = var_734_cast_fp16)[name = tensor("transpose_146")]; tensor transpose_88 = transpose(perm = transpose_88_perm_0, x = var_728_cast_fp16)[name = tensor("transpose_147")]; tensor var_743_cast_fp16 = matmul(transpose_x = var_743_transpose_x_0, transpose_y = var_743_transpose_y_0, x = transpose_88, y = transpose_89)[name = tensor("op_743_cast_fp16")]; tensor var_744_to_fp16 = const()[name = tensor("op_744_to_fp16"), val = tensor(0x1p-3)]; tensor input_107_cast_fp16 = mul(x = var_743_cast_fp16, y = var_744_to_fp16)[name = tensor("input_107_cast_fp16")]; tensor attn_17_cast_fp16 = softmax(axis = var_704, x = input_107_cast_fp16)[name = tensor("attn_17_cast_fp16")]; tensor out_17_transpose_x_0 = const()[name = tensor("out_17_transpose_x_0"), val = tensor(false)]; tensor out_17_transpose_y_0 = const()[name = tensor("out_17_transpose_y_0"), val = tensor(false)]; tensor v_17_cast_fp16 = transpose(perm = v_17_perm_0, x = var_740_cast_fp16)[name = tensor("transpose_145")]; tensor out_17_cast_fp16 = matmul(transpose_x = out_17_transpose_x_0, transpose_y = out_17_transpose_y_0, x = attn_17_cast_fp16, y = v_17_cast_fp16)[name = tensor("out_17_cast_fp16")]; tensor var_748_perm_0 = const()[name = tensor("op_748_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_37x = const()[name = tensor("concat_37x"), val = tensor([1, -1, 896])]; tensor var_748_cast_fp16 = transpose(perm = var_748_perm_0, x = out_17_cast_fp16)[name = tensor("transpose_144")]; tensor input_109_cast_fp16 = reshape(shape = concat_37x, x = var_748_cast_fp16)[name = tensor("input_109_cast_fp16")]; tensor layers_8_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46144320))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46545792))), name = tensor("layers_8_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_8_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_8_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46545920)))]; tensor linear_52_cast_fp16 = linear(bias = layers_8_self_attn_out_proj_bias_to_fp16, weight = layers_8_self_attn_out_proj_weight_to_fp16_palettized, x = input_109_cast_fp16)[name = tensor("linear_52_cast_fp16")]; tensor input_111_cast_fp16 = add(x = input_105_cast_fp16, y = linear_52_cast_fp16)[name = tensor("input_111_cast_fp16")]; tensor input_113_axes_0 = const()[name = tensor("input_113_axes_0"), val = tensor([-1])]; tensor layers_8_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_8_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46547776)))]; tensor layers_8_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_8_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46549632)))]; tensor input_113_cast_fp16 = layer_norm(axes = input_113_axes_0, beta = layers_8_final_layer_norm_bias_to_fp16, epsilon = var_707_to_fp16, gamma = layers_8_final_layer_norm_weight_to_fp16, x = input_111_cast_fp16)[name = tensor("input_113_cast_fp16")]; tensor layers_8_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(46551488))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48157184))), name = tensor("layers_8_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_8_fc1_bias_to_fp16 = const()[name = tensor("layers_8_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48157312)))]; tensor linear_53_cast_fp16 = linear(bias = layers_8_fc1_bias_to_fp16, weight = layers_8_fc1_weight_to_fp16_palettized, x = input_113_cast_fp16)[name = tensor("linear_53_cast_fp16")]; tensor input_115_mode_0 = const()[name = tensor("input_115_mode_0"), val = tensor("EXACT")]; tensor input_115_cast_fp16 = gelu(mode = input_115_mode_0, x = linear_53_cast_fp16)[name = tensor("input_115_cast_fp16")]; tensor layers_8_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(48164544))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49770240))), name = tensor("layers_8_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_8_fc2_bias_to_fp16 = const()[name = tensor("layers_8_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49770368)))]; tensor linear_54_cast_fp16 = linear(bias = layers_8_fc2_bias_to_fp16, weight = layers_8_fc2_weight_to_fp16_palettized, x = input_115_cast_fp16)[name = tensor("linear_54_cast_fp16")]; tensor input_117_cast_fp16 = add(x = input_111_cast_fp16, y = linear_54_cast_fp16)[name = tensor("input_117_cast_fp16")]; tensor var_774 = const()[name = tensor("op_774"), val = tensor(-1)]; tensor x_59_axes_0 = const()[name = tensor("x_59_axes_0"), val = tensor([-1])]; tensor layers_9_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_9_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49772224)))]; tensor layers_9_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49774080)))]; tensor var_777_to_fp16 = const()[name = tensor("op_777_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_59_cast_fp16 = layer_norm(axes = x_59_axes_0, beta = layers_9_self_attn_layer_norm_bias_to_fp16, epsilon = var_777_to_fp16, gamma = layers_9_self_attn_layer_norm_weight_to_fp16, x = input_117_cast_fp16)[name = tensor("x_59_cast_fp16")]; tensor layers_9_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(49775936))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50177408))), name = tensor("layers_9_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_9_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50177536)))]; tensor linear_55_cast_fp16 = linear(bias = layers_9_self_attn_q_proj_bias_to_fp16, weight = layers_9_self_attn_q_proj_weight_to_fp16_palettized, x = x_59_cast_fp16)[name = tensor("linear_55_cast_fp16")]; tensor concat_38x = const()[name = tensor("concat_38x"), val = tensor([1, -1, 14, 64])]; tensor var_798_cast_fp16 = reshape(shape = concat_38x, x = linear_55_cast_fp16)[name = tensor("op_798_cast_fp16")]; tensor layers_9_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50179392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50580864))), name = tensor("layers_9_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_9_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50580992)))]; tensor linear_56_cast_fp16 = linear(bias = layers_9_self_attn_k_proj_bias_to_fp16, weight = layers_9_self_attn_k_proj_weight_to_fp16_palettized, x = x_59_cast_fp16)[name = tensor("linear_56_cast_fp16")]; tensor concat_39x = const()[name = tensor("concat_39x"), val = tensor([1, -1, 14, 64])]; tensor var_804_cast_fp16 = reshape(shape = concat_39x, x = linear_56_cast_fp16)[name = tensor("op_804_cast_fp16")]; tensor layers_9_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50582848))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50984320))), name = tensor("layers_9_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_9_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50984448)))]; tensor linear_57_cast_fp16 = linear(bias = layers_9_self_attn_v_proj_bias_to_fp16, weight = layers_9_self_attn_v_proj_weight_to_fp16_palettized, x = x_59_cast_fp16)[name = tensor("linear_57_cast_fp16")]; tensor concat_40x = const()[name = tensor("concat_40x"), val = tensor([1, -1, 14, 64])]; tensor var_810_cast_fp16 = reshape(shape = concat_40x, x = linear_57_cast_fp16)[name = tensor("op_810_cast_fp16")]; tensor v_19_perm_0 = const()[name = tensor("v_19_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_813_transpose_x_0 = const()[name = tensor("op_813_transpose_x_0"), val = tensor(false)]; tensor var_813_transpose_y_0 = const()[name = tensor("op_813_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 = var_804_cast_fp16)[name = tensor("transpose_142")]; tensor transpose_90 = transpose(perm = transpose_90_perm_0, x = var_798_cast_fp16)[name = tensor("transpose_143")]; tensor var_813_cast_fp16 = matmul(transpose_x = var_813_transpose_x_0, transpose_y = var_813_transpose_y_0, x = transpose_90, y = transpose_91)[name = tensor("op_813_cast_fp16")]; tensor var_814_to_fp16 = const()[name = tensor("op_814_to_fp16"), val = tensor(0x1p-3)]; tensor input_119_cast_fp16 = mul(x = var_813_cast_fp16, y = var_814_to_fp16)[name = tensor("input_119_cast_fp16")]; tensor attn_19_cast_fp16 = softmax(axis = var_774, x = input_119_cast_fp16)[name = tensor("attn_19_cast_fp16")]; tensor out_19_transpose_x_0 = const()[name = tensor("out_19_transpose_x_0"), val = tensor(false)]; tensor out_19_transpose_y_0 = const()[name = tensor("out_19_transpose_y_0"), val = tensor(false)]; tensor v_19_cast_fp16 = transpose(perm = v_19_perm_0, x = var_810_cast_fp16)[name = tensor("transpose_141")]; tensor out_19_cast_fp16 = matmul(transpose_x = out_19_transpose_x_0, transpose_y = out_19_transpose_y_0, x = attn_19_cast_fp16, y = v_19_cast_fp16)[name = tensor("out_19_cast_fp16")]; tensor var_818_perm_0 = const()[name = tensor("op_818_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_41x = const()[name = tensor("concat_41x"), val = tensor([1, -1, 896])]; tensor var_818_cast_fp16 = transpose(perm = var_818_perm_0, x = out_19_cast_fp16)[name = tensor("transpose_140")]; tensor input_121_cast_fp16 = reshape(shape = concat_41x, x = var_818_cast_fp16)[name = tensor("input_121_cast_fp16")]; tensor layers_9_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(50986304))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51387776))), name = tensor("layers_9_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_9_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_9_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51387904)))]; tensor linear_58_cast_fp16 = linear(bias = layers_9_self_attn_out_proj_bias_to_fp16, weight = layers_9_self_attn_out_proj_weight_to_fp16_palettized, x = input_121_cast_fp16)[name = tensor("linear_58_cast_fp16")]; tensor input_123_cast_fp16 = add(x = input_117_cast_fp16, y = linear_58_cast_fp16)[name = tensor("input_123_cast_fp16")]; tensor input_125_axes_0 = const()[name = tensor("input_125_axes_0"), val = tensor([-1])]; tensor layers_9_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_9_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51389760)))]; tensor layers_9_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_9_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51391616)))]; tensor input_125_cast_fp16 = layer_norm(axes = input_125_axes_0, beta = layers_9_final_layer_norm_bias_to_fp16, epsilon = var_777_to_fp16, gamma = layers_9_final_layer_norm_weight_to_fp16, x = input_123_cast_fp16)[name = tensor("input_125_cast_fp16")]; tensor layers_9_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(51393472))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52999168))), name = tensor("layers_9_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_9_fc1_bias_to_fp16 = const()[name = tensor("layers_9_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(52999296)))]; tensor linear_59_cast_fp16 = linear(bias = layers_9_fc1_bias_to_fp16, weight = layers_9_fc1_weight_to_fp16_palettized, x = input_125_cast_fp16)[name = tensor("linear_59_cast_fp16")]; tensor input_127_mode_0 = const()[name = tensor("input_127_mode_0"), val = tensor("EXACT")]; tensor input_127_cast_fp16 = gelu(mode = input_127_mode_0, x = linear_59_cast_fp16)[name = tensor("input_127_cast_fp16")]; tensor layers_9_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(53006528))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54612224))), name = tensor("layers_9_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_9_fc2_bias_to_fp16 = const()[name = tensor("layers_9_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54612352)))]; tensor linear_60_cast_fp16 = linear(bias = layers_9_fc2_bias_to_fp16, weight = layers_9_fc2_weight_to_fp16_palettized, x = input_127_cast_fp16)[name = tensor("linear_60_cast_fp16")]; tensor input_129_cast_fp16 = add(x = input_123_cast_fp16, y = linear_60_cast_fp16)[name = tensor("input_129_cast_fp16")]; tensor var_844 = const()[name = tensor("op_844"), val = tensor(-1)]; tensor x_65_axes_0 = const()[name = tensor("x_65_axes_0"), val = tensor([-1])]; tensor layers_10_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_10_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54614208)))]; tensor layers_10_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54616064)))]; tensor var_847_to_fp16 = const()[name = tensor("op_847_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_65_cast_fp16 = layer_norm(axes = x_65_axes_0, beta = layers_10_self_attn_layer_norm_bias_to_fp16, epsilon = var_847_to_fp16, gamma = layers_10_self_attn_layer_norm_weight_to_fp16, x = input_129_cast_fp16)[name = tensor("x_65_cast_fp16")]; tensor layers_10_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(54617920))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55019392))), name = tensor("layers_10_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_10_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55019520)))]; tensor linear_61_cast_fp16 = linear(bias = layers_10_self_attn_q_proj_bias_to_fp16, weight = layers_10_self_attn_q_proj_weight_to_fp16_palettized, x = x_65_cast_fp16)[name = tensor("linear_61_cast_fp16")]; tensor concat_42x = const()[name = tensor("concat_42x"), val = tensor([1, -1, 14, 64])]; tensor var_868_cast_fp16 = reshape(shape = concat_42x, x = linear_61_cast_fp16)[name = tensor("op_868_cast_fp16")]; tensor layers_10_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55021376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55422848))), name = tensor("layers_10_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_10_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55422976)))]; tensor linear_62_cast_fp16 = linear(bias = layers_10_self_attn_k_proj_bias_to_fp16, weight = layers_10_self_attn_k_proj_weight_to_fp16_palettized, x = x_65_cast_fp16)[name = tensor("linear_62_cast_fp16")]; tensor concat_43x = const()[name = tensor("concat_43x"), val = tensor([1, -1, 14, 64])]; tensor var_874_cast_fp16 = reshape(shape = concat_43x, x = linear_62_cast_fp16)[name = tensor("op_874_cast_fp16")]; tensor layers_10_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55424832))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55826304))), name = tensor("layers_10_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_10_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55826432)))]; tensor linear_63_cast_fp16 = linear(bias = layers_10_self_attn_v_proj_bias_to_fp16, weight = layers_10_self_attn_v_proj_weight_to_fp16_palettized, x = x_65_cast_fp16)[name = tensor("linear_63_cast_fp16")]; tensor concat_44x = const()[name = tensor("concat_44x"), val = tensor([1, -1, 14, 64])]; tensor var_880_cast_fp16 = reshape(shape = concat_44x, x = linear_63_cast_fp16)[name = tensor("op_880_cast_fp16")]; tensor v_21_perm_0 = const()[name = tensor("v_21_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_883_transpose_x_0 = const()[name = tensor("op_883_transpose_x_0"), val = tensor(false)]; tensor var_883_transpose_y_0 = const()[name = tensor("op_883_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 = var_874_cast_fp16)[name = tensor("transpose_138")]; tensor transpose_92 = transpose(perm = transpose_92_perm_0, x = var_868_cast_fp16)[name = tensor("transpose_139")]; tensor var_883_cast_fp16 = matmul(transpose_x = var_883_transpose_x_0, transpose_y = var_883_transpose_y_0, x = transpose_92, y = transpose_93)[name = tensor("op_883_cast_fp16")]; tensor var_884_to_fp16 = const()[name = tensor("op_884_to_fp16"), val = tensor(0x1p-3)]; tensor input_131_cast_fp16 = mul(x = var_883_cast_fp16, y = var_884_to_fp16)[name = tensor("input_131_cast_fp16")]; tensor attn_21_cast_fp16 = softmax(axis = var_844, x = input_131_cast_fp16)[name = tensor("attn_21_cast_fp16")]; tensor out_21_transpose_x_0 = const()[name = tensor("out_21_transpose_x_0"), val = tensor(false)]; tensor out_21_transpose_y_0 = const()[name = tensor("out_21_transpose_y_0"), val = tensor(false)]; tensor v_21_cast_fp16 = transpose(perm = v_21_perm_0, x = var_880_cast_fp16)[name = tensor("transpose_137")]; tensor out_21_cast_fp16 = matmul(transpose_x = out_21_transpose_x_0, transpose_y = out_21_transpose_y_0, x = attn_21_cast_fp16, y = v_21_cast_fp16)[name = tensor("out_21_cast_fp16")]; tensor var_888_perm_0 = const()[name = tensor("op_888_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_45x = const()[name = tensor("concat_45x"), val = tensor([1, -1, 896])]; tensor var_888_cast_fp16 = transpose(perm = var_888_perm_0, x = out_21_cast_fp16)[name = tensor("transpose_136")]; tensor input_133_cast_fp16 = reshape(shape = concat_45x, x = var_888_cast_fp16)[name = tensor("input_133_cast_fp16")]; tensor layers_10_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(55828288))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56229760))), name = tensor("layers_10_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_10_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_10_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56229888)))]; tensor linear_64_cast_fp16 = linear(bias = layers_10_self_attn_out_proj_bias_to_fp16, weight = layers_10_self_attn_out_proj_weight_to_fp16_palettized, x = input_133_cast_fp16)[name = tensor("linear_64_cast_fp16")]; tensor input_135_cast_fp16 = add(x = input_129_cast_fp16, y = linear_64_cast_fp16)[name = tensor("input_135_cast_fp16")]; tensor input_137_axes_0 = const()[name = tensor("input_137_axes_0"), val = tensor([-1])]; tensor layers_10_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_10_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56231744)))]; tensor layers_10_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_10_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56233600)))]; tensor input_137_cast_fp16 = layer_norm(axes = input_137_axes_0, beta = layers_10_final_layer_norm_bias_to_fp16, epsilon = var_847_to_fp16, gamma = layers_10_final_layer_norm_weight_to_fp16, x = input_135_cast_fp16)[name = tensor("input_137_cast_fp16")]; tensor layers_10_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(56235456))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57841152))), name = tensor("layers_10_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_10_fc1_bias_to_fp16 = const()[name = tensor("layers_10_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57841280)))]; tensor linear_65_cast_fp16 = linear(bias = layers_10_fc1_bias_to_fp16, weight = layers_10_fc1_weight_to_fp16_palettized, x = input_137_cast_fp16)[name = tensor("linear_65_cast_fp16")]; tensor input_139_mode_0 = const()[name = tensor("input_139_mode_0"), val = tensor("EXACT")]; tensor input_139_cast_fp16 = gelu(mode = input_139_mode_0, x = linear_65_cast_fp16)[name = tensor("input_139_cast_fp16")]; tensor layers_10_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(57848512))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59454208))), name = tensor("layers_10_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_10_fc2_bias_to_fp16 = const()[name = tensor("layers_10_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59454336)))]; tensor linear_66_cast_fp16 = linear(bias = layers_10_fc2_bias_to_fp16, weight = layers_10_fc2_weight_to_fp16_palettized, x = input_139_cast_fp16)[name = tensor("linear_66_cast_fp16")]; tensor input_141_cast_fp16 = add(x = input_135_cast_fp16, y = linear_66_cast_fp16)[name = tensor("input_141_cast_fp16")]; tensor var_914 = const()[name = tensor("op_914"), val = tensor(-1)]; tensor x_71_axes_0 = const()[name = tensor("x_71_axes_0"), val = tensor([-1])]; tensor layers_11_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_11_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59456192)))]; tensor layers_11_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59458048)))]; tensor var_917_to_fp16 = const()[name = tensor("op_917_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_71_cast_fp16 = layer_norm(axes = x_71_axes_0, beta = layers_11_self_attn_layer_norm_bias_to_fp16, epsilon = var_917_to_fp16, gamma = layers_11_self_attn_layer_norm_weight_to_fp16, x = input_141_cast_fp16)[name = tensor("x_71_cast_fp16")]; tensor layers_11_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59459904))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59861376))), name = tensor("layers_11_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_11_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59861504)))]; tensor linear_67_cast_fp16 = linear(bias = layers_11_self_attn_q_proj_bias_to_fp16, weight = layers_11_self_attn_q_proj_weight_to_fp16_palettized, x = x_71_cast_fp16)[name = tensor("linear_67_cast_fp16")]; tensor concat_46x = const()[name = tensor("concat_46x"), val = tensor([1, -1, 14, 64])]; tensor var_938_cast_fp16 = reshape(shape = concat_46x, x = linear_67_cast_fp16)[name = tensor("op_938_cast_fp16")]; tensor layers_11_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(59863360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60264832))), name = tensor("layers_11_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_11_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60264960)))]; tensor linear_68_cast_fp16 = linear(bias = layers_11_self_attn_k_proj_bias_to_fp16, weight = layers_11_self_attn_k_proj_weight_to_fp16_palettized, x = x_71_cast_fp16)[name = tensor("linear_68_cast_fp16")]; tensor concat_47x = const()[name = tensor("concat_47x"), val = tensor([1, -1, 14, 64])]; tensor var_944_cast_fp16 = reshape(shape = concat_47x, x = linear_68_cast_fp16)[name = tensor("op_944_cast_fp16")]; tensor layers_11_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60266816))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60668288))), name = tensor("layers_11_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_11_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60668416)))]; tensor linear_69_cast_fp16 = linear(bias = layers_11_self_attn_v_proj_bias_to_fp16, weight = layers_11_self_attn_v_proj_weight_to_fp16_palettized, x = x_71_cast_fp16)[name = tensor("linear_69_cast_fp16")]; tensor concat_48x = const()[name = tensor("concat_48x"), val = tensor([1, -1, 14, 64])]; tensor var_950_cast_fp16 = reshape(shape = concat_48x, x = linear_69_cast_fp16)[name = tensor("op_950_cast_fp16")]; tensor v_23_perm_0 = const()[name = tensor("v_23_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_953_transpose_x_0 = const()[name = tensor("op_953_transpose_x_0"), val = tensor(false)]; tensor var_953_transpose_y_0 = const()[name = tensor("op_953_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 = var_944_cast_fp16)[name = tensor("transpose_134")]; tensor transpose_94 = transpose(perm = transpose_94_perm_0, x = var_938_cast_fp16)[name = tensor("transpose_135")]; tensor var_953_cast_fp16 = matmul(transpose_x = var_953_transpose_x_0, transpose_y = var_953_transpose_y_0, x = transpose_94, y = transpose_95)[name = tensor("op_953_cast_fp16")]; tensor var_954_to_fp16 = const()[name = tensor("op_954_to_fp16"), val = tensor(0x1p-3)]; tensor input_143_cast_fp16 = mul(x = var_953_cast_fp16, y = var_954_to_fp16)[name = tensor("input_143_cast_fp16")]; tensor attn_23_cast_fp16 = softmax(axis = var_914, x = input_143_cast_fp16)[name = tensor("attn_23_cast_fp16")]; tensor out_23_transpose_x_0 = const()[name = tensor("out_23_transpose_x_0"), val = tensor(false)]; tensor out_23_transpose_y_0 = const()[name = tensor("out_23_transpose_y_0"), val = tensor(false)]; tensor v_23_cast_fp16 = transpose(perm = v_23_perm_0, x = var_950_cast_fp16)[name = tensor("transpose_133")]; tensor out_23_cast_fp16 = matmul(transpose_x = out_23_transpose_x_0, transpose_y = out_23_transpose_y_0, x = attn_23_cast_fp16, y = v_23_cast_fp16)[name = tensor("out_23_cast_fp16")]; tensor var_958_perm_0 = const()[name = tensor("op_958_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_49x = const()[name = tensor("concat_49x"), val = tensor([1, -1, 896])]; tensor var_958_cast_fp16 = transpose(perm = var_958_perm_0, x = out_23_cast_fp16)[name = tensor("transpose_132")]; tensor input_145_cast_fp16 = reshape(shape = concat_49x, x = var_958_cast_fp16)[name = tensor("input_145_cast_fp16")]; tensor layers_11_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(60670272))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61071744))), name = tensor("layers_11_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_11_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_11_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61071872)))]; tensor linear_70_cast_fp16 = linear(bias = layers_11_self_attn_out_proj_bias_to_fp16, weight = layers_11_self_attn_out_proj_weight_to_fp16_palettized, x = input_145_cast_fp16)[name = tensor("linear_70_cast_fp16")]; tensor input_147_cast_fp16 = add(x = input_141_cast_fp16, y = linear_70_cast_fp16)[name = tensor("input_147_cast_fp16")]; tensor input_149_axes_0 = const()[name = tensor("input_149_axes_0"), val = tensor([-1])]; tensor layers_11_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_11_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61073728)))]; tensor layers_11_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_11_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61075584)))]; tensor input_149_cast_fp16 = layer_norm(axes = input_149_axes_0, beta = layers_11_final_layer_norm_bias_to_fp16, epsilon = var_917_to_fp16, gamma = layers_11_final_layer_norm_weight_to_fp16, x = input_147_cast_fp16)[name = tensor("input_149_cast_fp16")]; tensor layers_11_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(61077440))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62683136))), name = tensor("layers_11_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_11_fc1_bias_to_fp16 = const()[name = tensor("layers_11_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62683264)))]; tensor linear_71_cast_fp16 = linear(bias = layers_11_fc1_bias_to_fp16, weight = layers_11_fc1_weight_to_fp16_palettized, x = input_149_cast_fp16)[name = tensor("linear_71_cast_fp16")]; tensor input_151_mode_0 = const()[name = tensor("input_151_mode_0"), val = tensor("EXACT")]; tensor input_151_cast_fp16 = gelu(mode = input_151_mode_0, x = linear_71_cast_fp16)[name = tensor("input_151_cast_fp16")]; tensor layers_11_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(62690496))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64296192))), name = tensor("layers_11_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_11_fc2_bias_to_fp16 = const()[name = tensor("layers_11_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64296320)))]; tensor linear_72_cast_fp16 = linear(bias = layers_11_fc2_bias_to_fp16, weight = layers_11_fc2_weight_to_fp16_palettized, x = input_151_cast_fp16)[name = tensor("linear_72_cast_fp16")]; tensor input_153_cast_fp16 = add(x = input_147_cast_fp16, y = linear_72_cast_fp16)[name = tensor("input_153_cast_fp16")]; tensor var_984 = const()[name = tensor("op_984"), val = tensor(-1)]; tensor x_77_axes_0 = const()[name = tensor("x_77_axes_0"), val = tensor([-1])]; tensor layers_12_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_12_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64298176)))]; tensor layers_12_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64300032)))]; tensor var_987_to_fp16 = const()[name = tensor("op_987_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_77_cast_fp16 = layer_norm(axes = x_77_axes_0, beta = layers_12_self_attn_layer_norm_bias_to_fp16, epsilon = var_987_to_fp16, gamma = layers_12_self_attn_layer_norm_weight_to_fp16, x = input_153_cast_fp16)[name = tensor("x_77_cast_fp16")]; tensor layers_12_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64301888))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64703360))), name = tensor("layers_12_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_12_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64703488)))]; tensor linear_73_cast_fp16 = linear(bias = layers_12_self_attn_q_proj_bias_to_fp16, weight = layers_12_self_attn_q_proj_weight_to_fp16_palettized, x = x_77_cast_fp16)[name = tensor("linear_73_cast_fp16")]; tensor concat_50x = const()[name = tensor("concat_50x"), val = tensor([1, -1, 14, 64])]; tensor var_1008_cast_fp16 = reshape(shape = concat_50x, x = linear_73_cast_fp16)[name = tensor("op_1008_cast_fp16")]; tensor layers_12_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(64705344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65106816))), name = tensor("layers_12_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_12_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65106944)))]; tensor linear_74_cast_fp16 = linear(bias = layers_12_self_attn_k_proj_bias_to_fp16, weight = layers_12_self_attn_k_proj_weight_to_fp16_palettized, x = x_77_cast_fp16)[name = tensor("linear_74_cast_fp16")]; tensor concat_51x = const()[name = tensor("concat_51x"), val = tensor([1, -1, 14, 64])]; tensor var_1014_cast_fp16 = reshape(shape = concat_51x, x = linear_74_cast_fp16)[name = tensor("op_1014_cast_fp16")]; tensor layers_12_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65108800))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65510272))), name = tensor("layers_12_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_12_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65510400)))]; tensor linear_75_cast_fp16 = linear(bias = layers_12_self_attn_v_proj_bias_to_fp16, weight = layers_12_self_attn_v_proj_weight_to_fp16_palettized, x = x_77_cast_fp16)[name = tensor("linear_75_cast_fp16")]; tensor concat_52x = const()[name = tensor("concat_52x"), val = tensor([1, -1, 14, 64])]; tensor var_1020_cast_fp16 = reshape(shape = concat_52x, x = linear_75_cast_fp16)[name = tensor("op_1020_cast_fp16")]; tensor v_25_perm_0 = const()[name = tensor("v_25_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_1023_transpose_x_0 = const()[name = tensor("op_1023_transpose_x_0"), val = tensor(false)]; tensor var_1023_transpose_y_0 = const()[name = tensor("op_1023_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 = var_1014_cast_fp16)[name = tensor("transpose_130")]; tensor transpose_96 = transpose(perm = transpose_96_perm_0, x = var_1008_cast_fp16)[name = tensor("transpose_131")]; tensor var_1023_cast_fp16 = matmul(transpose_x = var_1023_transpose_x_0, transpose_y = var_1023_transpose_y_0, x = transpose_96, y = transpose_97)[name = tensor("op_1023_cast_fp16")]; tensor var_1024_to_fp16 = const()[name = tensor("op_1024_to_fp16"), val = tensor(0x1p-3)]; tensor input_155_cast_fp16 = mul(x = var_1023_cast_fp16, y = var_1024_to_fp16)[name = tensor("input_155_cast_fp16")]; tensor attn_25_cast_fp16 = softmax(axis = var_984, x = input_155_cast_fp16)[name = tensor("attn_25_cast_fp16")]; tensor out_25_transpose_x_0 = const()[name = tensor("out_25_transpose_x_0"), val = tensor(false)]; tensor out_25_transpose_y_0 = const()[name = tensor("out_25_transpose_y_0"), val = tensor(false)]; tensor v_25_cast_fp16 = transpose(perm = v_25_perm_0, x = var_1020_cast_fp16)[name = tensor("transpose_129")]; tensor out_25_cast_fp16 = matmul(transpose_x = out_25_transpose_x_0, transpose_y = out_25_transpose_y_0, x = attn_25_cast_fp16, y = v_25_cast_fp16)[name = tensor("out_25_cast_fp16")]; tensor var_1028_perm_0 = const()[name = tensor("op_1028_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_53x = const()[name = tensor("concat_53x"), val = tensor([1, -1, 896])]; tensor var_1028_cast_fp16 = transpose(perm = var_1028_perm_0, x = out_25_cast_fp16)[name = tensor("transpose_128")]; tensor input_157_cast_fp16 = reshape(shape = concat_53x, x = var_1028_cast_fp16)[name = tensor("input_157_cast_fp16")]; tensor layers_12_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65512256))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65913728))), name = tensor("layers_12_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_12_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_12_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65913856)))]; tensor linear_76_cast_fp16 = linear(bias = layers_12_self_attn_out_proj_bias_to_fp16, weight = layers_12_self_attn_out_proj_weight_to_fp16_palettized, x = input_157_cast_fp16)[name = tensor("linear_76_cast_fp16")]; tensor input_159_cast_fp16 = add(x = input_153_cast_fp16, y = linear_76_cast_fp16)[name = tensor("input_159_cast_fp16")]; tensor input_161_axes_0 = const()[name = tensor("input_161_axes_0"), val = tensor([-1])]; tensor layers_12_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_12_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65915712)))]; tensor layers_12_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_12_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65917568)))]; tensor input_161_cast_fp16 = layer_norm(axes = input_161_axes_0, beta = layers_12_final_layer_norm_bias_to_fp16, epsilon = var_987_to_fp16, gamma = layers_12_final_layer_norm_weight_to_fp16, x = input_159_cast_fp16)[name = tensor("input_161_cast_fp16")]; tensor layers_12_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(65919424))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67525120))), name = tensor("layers_12_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_12_fc1_bias_to_fp16 = const()[name = tensor("layers_12_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67525248)))]; tensor linear_77_cast_fp16 = linear(bias = layers_12_fc1_bias_to_fp16, weight = layers_12_fc1_weight_to_fp16_palettized, x = input_161_cast_fp16)[name = tensor("linear_77_cast_fp16")]; tensor input_163_mode_0 = const()[name = tensor("input_163_mode_0"), val = tensor("EXACT")]; tensor input_163_cast_fp16 = gelu(mode = input_163_mode_0, x = linear_77_cast_fp16)[name = tensor("input_163_cast_fp16")]; tensor layers_12_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(67532480))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69138176))), name = tensor("layers_12_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_12_fc2_bias_to_fp16 = const()[name = tensor("layers_12_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69138304)))]; tensor linear_78_cast_fp16 = linear(bias = layers_12_fc2_bias_to_fp16, weight = layers_12_fc2_weight_to_fp16_palettized, x = input_163_cast_fp16)[name = tensor("linear_78_cast_fp16")]; tensor input_165_cast_fp16 = add(x = input_159_cast_fp16, y = linear_78_cast_fp16)[name = tensor("input_165_cast_fp16")]; tensor var_1054 = const()[name = tensor("op_1054"), val = tensor(-1)]; tensor x_83_axes_0 = const()[name = tensor("x_83_axes_0"), val = tensor([-1])]; tensor layers_13_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_13_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69140160)))]; tensor layers_13_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69142016)))]; tensor var_1057_to_fp16 = const()[name = tensor("op_1057_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_83_cast_fp16 = layer_norm(axes = x_83_axes_0, beta = layers_13_self_attn_layer_norm_bias_to_fp16, epsilon = var_1057_to_fp16, gamma = layers_13_self_attn_layer_norm_weight_to_fp16, x = input_165_cast_fp16)[name = tensor("x_83_cast_fp16")]; tensor layers_13_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69143872))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69545344))), name = tensor("layers_13_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_13_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69545472)))]; tensor linear_79_cast_fp16 = linear(bias = layers_13_self_attn_q_proj_bias_to_fp16, weight = layers_13_self_attn_q_proj_weight_to_fp16_palettized, x = x_83_cast_fp16)[name = tensor("linear_79_cast_fp16")]; tensor concat_54x = const()[name = tensor("concat_54x"), val = tensor([1, -1, 14, 64])]; tensor var_1078_cast_fp16 = reshape(shape = concat_54x, x = linear_79_cast_fp16)[name = tensor("op_1078_cast_fp16")]; tensor layers_13_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69547328))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69948800))), name = tensor("layers_13_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_13_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69948928)))]; tensor linear_80_cast_fp16 = linear(bias = layers_13_self_attn_k_proj_bias_to_fp16, weight = layers_13_self_attn_k_proj_weight_to_fp16_palettized, x = x_83_cast_fp16)[name = tensor("linear_80_cast_fp16")]; tensor concat_55x = const()[name = tensor("concat_55x"), val = tensor([1, -1, 14, 64])]; tensor var_1084_cast_fp16 = reshape(shape = concat_55x, x = linear_80_cast_fp16)[name = tensor("op_1084_cast_fp16")]; tensor layers_13_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(69950784))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70352256))), name = tensor("layers_13_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_13_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70352384)))]; tensor linear_81_cast_fp16 = linear(bias = layers_13_self_attn_v_proj_bias_to_fp16, weight = layers_13_self_attn_v_proj_weight_to_fp16_palettized, x = x_83_cast_fp16)[name = tensor("linear_81_cast_fp16")]; tensor concat_56x = const()[name = tensor("concat_56x"), val = tensor([1, -1, 14, 64])]; tensor var_1090_cast_fp16 = reshape(shape = concat_56x, x = linear_81_cast_fp16)[name = tensor("op_1090_cast_fp16")]; tensor v_27_perm_0 = const()[name = tensor("v_27_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_1093_transpose_x_0 = const()[name = tensor("op_1093_transpose_x_0"), val = tensor(false)]; tensor var_1093_transpose_y_0 = const()[name = tensor("op_1093_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 = var_1084_cast_fp16)[name = tensor("transpose_126")]; tensor transpose_98 = transpose(perm = transpose_98_perm_0, x = var_1078_cast_fp16)[name = tensor("transpose_127")]; tensor var_1093_cast_fp16 = matmul(transpose_x = var_1093_transpose_x_0, transpose_y = var_1093_transpose_y_0, x = transpose_98, y = transpose_99)[name = tensor("op_1093_cast_fp16")]; tensor var_1094_to_fp16 = const()[name = tensor("op_1094_to_fp16"), val = tensor(0x1p-3)]; tensor input_167_cast_fp16 = mul(x = var_1093_cast_fp16, y = var_1094_to_fp16)[name = tensor("input_167_cast_fp16")]; tensor attn_27_cast_fp16 = softmax(axis = var_1054, x = input_167_cast_fp16)[name = tensor("attn_27_cast_fp16")]; tensor out_27_transpose_x_0 = const()[name = tensor("out_27_transpose_x_0"), val = tensor(false)]; tensor out_27_transpose_y_0 = const()[name = tensor("out_27_transpose_y_0"), val = tensor(false)]; tensor v_27_cast_fp16 = transpose(perm = v_27_perm_0, x = var_1090_cast_fp16)[name = tensor("transpose_125")]; tensor out_27_cast_fp16 = matmul(transpose_x = out_27_transpose_x_0, transpose_y = out_27_transpose_y_0, x = attn_27_cast_fp16, y = v_27_cast_fp16)[name = tensor("out_27_cast_fp16")]; tensor var_1098_perm_0 = const()[name = tensor("op_1098_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_57x = const()[name = tensor("concat_57x"), val = tensor([1, -1, 896])]; tensor var_1098_cast_fp16 = transpose(perm = var_1098_perm_0, x = out_27_cast_fp16)[name = tensor("transpose_124")]; tensor input_169_cast_fp16 = reshape(shape = concat_57x, x = var_1098_cast_fp16)[name = tensor("input_169_cast_fp16")]; tensor layers_13_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70354240))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70755712))), name = tensor("layers_13_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_13_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_13_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70755840)))]; tensor linear_82_cast_fp16 = linear(bias = layers_13_self_attn_out_proj_bias_to_fp16, weight = layers_13_self_attn_out_proj_weight_to_fp16_palettized, x = input_169_cast_fp16)[name = tensor("linear_82_cast_fp16")]; tensor input_171_cast_fp16 = add(x = input_165_cast_fp16, y = linear_82_cast_fp16)[name = tensor("input_171_cast_fp16")]; tensor input_173_axes_0 = const()[name = tensor("input_173_axes_0"), val = tensor([-1])]; tensor layers_13_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_13_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70757696)))]; tensor layers_13_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_13_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70759552)))]; tensor input_173_cast_fp16 = layer_norm(axes = input_173_axes_0, beta = layers_13_final_layer_norm_bias_to_fp16, epsilon = var_1057_to_fp16, gamma = layers_13_final_layer_norm_weight_to_fp16, x = input_171_cast_fp16)[name = tensor("input_173_cast_fp16")]; tensor layers_13_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(70761408))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72367104))), name = tensor("layers_13_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_13_fc1_bias_to_fp16 = const()[name = tensor("layers_13_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72367232)))]; tensor linear_83_cast_fp16 = linear(bias = layers_13_fc1_bias_to_fp16, weight = layers_13_fc1_weight_to_fp16_palettized, x = input_173_cast_fp16)[name = tensor("linear_83_cast_fp16")]; tensor input_175_mode_0 = const()[name = tensor("input_175_mode_0"), val = tensor("EXACT")]; tensor input_175_cast_fp16 = gelu(mode = input_175_mode_0, x = linear_83_cast_fp16)[name = tensor("input_175_cast_fp16")]; tensor layers_13_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(72374464))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73980160))), name = tensor("layers_13_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_13_fc2_bias_to_fp16 = const()[name = tensor("layers_13_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73980288)))]; tensor linear_84_cast_fp16 = linear(bias = layers_13_fc2_bias_to_fp16, weight = layers_13_fc2_weight_to_fp16_palettized, x = input_175_cast_fp16)[name = tensor("linear_84_cast_fp16")]; tensor input_177_cast_fp16 = add(x = input_171_cast_fp16, y = linear_84_cast_fp16)[name = tensor("input_177_cast_fp16")]; tensor var_1124 = const()[name = tensor("op_1124"), val = tensor(-1)]; tensor x_89_axes_0 = const()[name = tensor("x_89_axes_0"), val = tensor([-1])]; tensor layers_14_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_14_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73982144)))]; tensor layers_14_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73984000)))]; tensor var_1127_to_fp16 = const()[name = tensor("op_1127_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_89_cast_fp16 = layer_norm(axes = x_89_axes_0, beta = layers_14_self_attn_layer_norm_bias_to_fp16, epsilon = var_1127_to_fp16, gamma = layers_14_self_attn_layer_norm_weight_to_fp16, x = input_177_cast_fp16)[name = tensor("x_89_cast_fp16")]; tensor layers_14_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(73985856))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74387328))), name = tensor("layers_14_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_14_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74387456)))]; tensor linear_85_cast_fp16 = linear(bias = layers_14_self_attn_q_proj_bias_to_fp16, weight = layers_14_self_attn_q_proj_weight_to_fp16_palettized, x = x_89_cast_fp16)[name = tensor("linear_85_cast_fp16")]; tensor concat_58x = const()[name = tensor("concat_58x"), val = tensor([1, -1, 14, 64])]; tensor var_1148_cast_fp16 = reshape(shape = concat_58x, x = linear_85_cast_fp16)[name = tensor("op_1148_cast_fp16")]; tensor layers_14_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74389312))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74790784))), name = tensor("layers_14_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_14_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74790912)))]; tensor linear_86_cast_fp16 = linear(bias = layers_14_self_attn_k_proj_bias_to_fp16, weight = layers_14_self_attn_k_proj_weight_to_fp16_palettized, x = x_89_cast_fp16)[name = tensor("linear_86_cast_fp16")]; tensor concat_59x = const()[name = tensor("concat_59x"), val = tensor([1, -1, 14, 64])]; tensor var_1154_cast_fp16 = reshape(shape = concat_59x, x = linear_86_cast_fp16)[name = tensor("op_1154_cast_fp16")]; tensor layers_14_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(74792768))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75194240))), name = tensor("layers_14_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_14_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75194368)))]; tensor linear_87_cast_fp16 = linear(bias = layers_14_self_attn_v_proj_bias_to_fp16, weight = layers_14_self_attn_v_proj_weight_to_fp16_palettized, x = x_89_cast_fp16)[name = tensor("linear_87_cast_fp16")]; tensor concat_60x = const()[name = tensor("concat_60x"), val = tensor([1, -1, 14, 64])]; tensor var_1160_cast_fp16 = reshape(shape = concat_60x, x = linear_87_cast_fp16)[name = tensor("op_1160_cast_fp16")]; tensor v_29_perm_0 = const()[name = tensor("v_29_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_1163_transpose_x_0 = const()[name = tensor("op_1163_transpose_x_0"), val = tensor(false)]; tensor var_1163_transpose_y_0 = const()[name = tensor("op_1163_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 = var_1154_cast_fp16)[name = tensor("transpose_122")]; tensor transpose_100 = transpose(perm = transpose_100_perm_0, x = var_1148_cast_fp16)[name = tensor("transpose_123")]; tensor var_1163_cast_fp16 = matmul(transpose_x = var_1163_transpose_x_0, transpose_y = var_1163_transpose_y_0, x = transpose_100, y = transpose_101)[name = tensor("op_1163_cast_fp16")]; tensor var_1164_to_fp16 = const()[name = tensor("op_1164_to_fp16"), val = tensor(0x1p-3)]; tensor input_179_cast_fp16 = mul(x = var_1163_cast_fp16, y = var_1164_to_fp16)[name = tensor("input_179_cast_fp16")]; tensor attn_29_cast_fp16 = softmax(axis = var_1124, x = input_179_cast_fp16)[name = tensor("attn_29_cast_fp16")]; tensor out_29_transpose_x_0 = const()[name = tensor("out_29_transpose_x_0"), val = tensor(false)]; tensor out_29_transpose_y_0 = const()[name = tensor("out_29_transpose_y_0"), val = tensor(false)]; tensor v_29_cast_fp16 = transpose(perm = v_29_perm_0, x = var_1160_cast_fp16)[name = tensor("transpose_121")]; tensor out_29_cast_fp16 = matmul(transpose_x = out_29_transpose_x_0, transpose_y = out_29_transpose_y_0, x = attn_29_cast_fp16, y = v_29_cast_fp16)[name = tensor("out_29_cast_fp16")]; tensor var_1168_perm_0 = const()[name = tensor("op_1168_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_61x = const()[name = tensor("concat_61x"), val = tensor([1, -1, 896])]; tensor var_1168_cast_fp16 = transpose(perm = var_1168_perm_0, x = out_29_cast_fp16)[name = tensor("transpose_120")]; tensor input_181_cast_fp16 = reshape(shape = concat_61x, x = var_1168_cast_fp16)[name = tensor("input_181_cast_fp16")]; tensor layers_14_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75196224))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75597696))), name = tensor("layers_14_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_14_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_14_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75597824)))]; tensor linear_88_cast_fp16 = linear(bias = layers_14_self_attn_out_proj_bias_to_fp16, weight = layers_14_self_attn_out_proj_weight_to_fp16_palettized, x = input_181_cast_fp16)[name = tensor("linear_88_cast_fp16")]; tensor input_183_cast_fp16 = add(x = input_177_cast_fp16, y = linear_88_cast_fp16)[name = tensor("input_183_cast_fp16")]; tensor input_185_axes_0 = const()[name = tensor("input_185_axes_0"), val = tensor([-1])]; tensor layers_14_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_14_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75599680)))]; tensor layers_14_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_14_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75601536)))]; tensor input_185_cast_fp16 = layer_norm(axes = input_185_axes_0, beta = layers_14_final_layer_norm_bias_to_fp16, epsilon = var_1127_to_fp16, gamma = layers_14_final_layer_norm_weight_to_fp16, x = input_183_cast_fp16)[name = tensor("input_185_cast_fp16")]; tensor layers_14_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(75603392))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77209088))), name = tensor("layers_14_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_14_fc1_bias_to_fp16 = const()[name = tensor("layers_14_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77209216)))]; tensor linear_89_cast_fp16 = linear(bias = layers_14_fc1_bias_to_fp16, weight = layers_14_fc1_weight_to_fp16_palettized, x = input_185_cast_fp16)[name = tensor("linear_89_cast_fp16")]; tensor input_187_mode_0 = const()[name = tensor("input_187_mode_0"), val = tensor("EXACT")]; tensor input_187_cast_fp16 = gelu(mode = input_187_mode_0, x = linear_89_cast_fp16)[name = tensor("input_187_cast_fp16")]; tensor layers_14_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(77216448))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78822144))), name = tensor("layers_14_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_14_fc2_bias_to_fp16 = const()[name = tensor("layers_14_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78822272)))]; tensor linear_90_cast_fp16 = linear(bias = layers_14_fc2_bias_to_fp16, weight = layers_14_fc2_weight_to_fp16_palettized, x = input_187_cast_fp16)[name = tensor("linear_90_cast_fp16")]; tensor input_189_cast_fp16 = add(x = input_183_cast_fp16, y = linear_90_cast_fp16)[name = tensor("input_189_cast_fp16")]; tensor var_1194 = const()[name = tensor("op_1194"), val = tensor(-1)]; tensor x_95_axes_0 = const()[name = tensor("x_95_axes_0"), val = tensor([-1])]; tensor layers_15_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_15_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78824128)))]; tensor layers_15_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78825984)))]; tensor var_1197_to_fp16 = const()[name = tensor("op_1197_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_95_cast_fp16 = layer_norm(axes = x_95_axes_0, beta = layers_15_self_attn_layer_norm_bias_to_fp16, epsilon = var_1197_to_fp16, gamma = layers_15_self_attn_layer_norm_weight_to_fp16, x = input_189_cast_fp16)[name = tensor("x_95_cast_fp16")]; tensor layers_15_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(78827840))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79229312))), name = tensor("layers_15_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_15_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79229440)))]; tensor linear_91_cast_fp16 = linear(bias = layers_15_self_attn_q_proj_bias_to_fp16, weight = layers_15_self_attn_q_proj_weight_to_fp16_palettized, x = x_95_cast_fp16)[name = tensor("linear_91_cast_fp16")]; tensor concat_62x = const()[name = tensor("concat_62x"), val = tensor([1, -1, 14, 64])]; tensor var_1218_cast_fp16 = reshape(shape = concat_62x, x = linear_91_cast_fp16)[name = tensor("op_1218_cast_fp16")]; tensor layers_15_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79231296))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79632768))), name = tensor("layers_15_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_15_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79632896)))]; tensor linear_92_cast_fp16 = linear(bias = layers_15_self_attn_k_proj_bias_to_fp16, weight = layers_15_self_attn_k_proj_weight_to_fp16_palettized, x = x_95_cast_fp16)[name = tensor("linear_92_cast_fp16")]; tensor concat_63x = const()[name = tensor("concat_63x"), val = tensor([1, -1, 14, 64])]; tensor var_1224_cast_fp16 = reshape(shape = concat_63x, x = linear_92_cast_fp16)[name = tensor("op_1224_cast_fp16")]; tensor layers_15_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(79634752))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80036224))), name = tensor("layers_15_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_15_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80036352)))]; tensor linear_93_cast_fp16 = linear(bias = layers_15_self_attn_v_proj_bias_to_fp16, weight = layers_15_self_attn_v_proj_weight_to_fp16_palettized, x = x_95_cast_fp16)[name = tensor("linear_93_cast_fp16")]; tensor concat_64x = const()[name = tensor("concat_64x"), val = tensor([1, -1, 14, 64])]; tensor var_1230_cast_fp16 = reshape(shape = concat_64x, x = linear_93_cast_fp16)[name = tensor("op_1230_cast_fp16")]; tensor v_31_perm_0 = const()[name = tensor("v_31_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_1233_transpose_x_0 = const()[name = tensor("op_1233_transpose_x_0"), val = tensor(false)]; tensor var_1233_transpose_y_0 = const()[name = tensor("op_1233_transpose_y_0"), val = tensor(false)]; tensor transpose_102_perm_0 = const()[name = tensor("transpose_102_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_103_perm_0 = const()[name = tensor("transpose_103_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_103 = transpose(perm = transpose_103_perm_0, x = var_1224_cast_fp16)[name = tensor("transpose_118")]; tensor transpose_102 = transpose(perm = transpose_102_perm_0, x = var_1218_cast_fp16)[name = tensor("transpose_119")]; tensor var_1233_cast_fp16 = matmul(transpose_x = var_1233_transpose_x_0, transpose_y = var_1233_transpose_y_0, x = transpose_102, y = transpose_103)[name = tensor("op_1233_cast_fp16")]; tensor var_1234_to_fp16 = const()[name = tensor("op_1234_to_fp16"), val = tensor(0x1p-3)]; tensor input_191_cast_fp16 = mul(x = var_1233_cast_fp16, y = var_1234_to_fp16)[name = tensor("input_191_cast_fp16")]; tensor attn_31_cast_fp16 = softmax(axis = var_1194, x = input_191_cast_fp16)[name = tensor("attn_31_cast_fp16")]; tensor out_31_transpose_x_0 = const()[name = tensor("out_31_transpose_x_0"), val = tensor(false)]; tensor out_31_transpose_y_0 = const()[name = tensor("out_31_transpose_y_0"), val = tensor(false)]; tensor v_31_cast_fp16 = transpose(perm = v_31_perm_0, x = var_1230_cast_fp16)[name = tensor("transpose_117")]; tensor out_31_cast_fp16 = matmul(transpose_x = out_31_transpose_x_0, transpose_y = out_31_transpose_y_0, x = attn_31_cast_fp16, y = v_31_cast_fp16)[name = tensor("out_31_cast_fp16")]; tensor var_1238_perm_0 = const()[name = tensor("op_1238_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_65x = const()[name = tensor("concat_65x"), val = tensor([1, -1, 896])]; tensor var_1238_cast_fp16 = transpose(perm = var_1238_perm_0, x = out_31_cast_fp16)[name = tensor("transpose_116")]; tensor input_193_cast_fp16 = reshape(shape = concat_65x, x = var_1238_cast_fp16)[name = tensor("input_193_cast_fp16")]; tensor layers_15_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80038208))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80439680))), name = tensor("layers_15_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_15_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_15_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80439808)))]; tensor linear_94_cast_fp16 = linear(bias = layers_15_self_attn_out_proj_bias_to_fp16, weight = layers_15_self_attn_out_proj_weight_to_fp16_palettized, x = input_193_cast_fp16)[name = tensor("linear_94_cast_fp16")]; tensor input_195_cast_fp16 = add(x = input_189_cast_fp16, y = linear_94_cast_fp16)[name = tensor("input_195_cast_fp16")]; tensor input_197_axes_0 = const()[name = tensor("input_197_axes_0"), val = tensor([-1])]; tensor layers_15_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_15_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80441664)))]; tensor layers_15_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_15_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80443520)))]; tensor input_197_cast_fp16 = layer_norm(axes = input_197_axes_0, beta = layers_15_final_layer_norm_bias_to_fp16, epsilon = var_1197_to_fp16, gamma = layers_15_final_layer_norm_weight_to_fp16, x = input_195_cast_fp16)[name = tensor("input_197_cast_fp16")]; tensor layers_15_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(80445376))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82051072))), name = tensor("layers_15_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_15_fc1_bias_to_fp16 = const()[name = tensor("layers_15_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82051200)))]; tensor linear_95_cast_fp16 = linear(bias = layers_15_fc1_bias_to_fp16, weight = layers_15_fc1_weight_to_fp16_palettized, x = input_197_cast_fp16)[name = tensor("linear_95_cast_fp16")]; tensor input_199_mode_0 = const()[name = tensor("input_199_mode_0"), val = tensor("EXACT")]; tensor input_199_cast_fp16 = gelu(mode = input_199_mode_0, x = linear_95_cast_fp16)[name = tensor("input_199_cast_fp16")]; tensor layers_15_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(82058432))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83664128))), name = tensor("layers_15_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_15_fc2_bias_to_fp16 = const()[name = tensor("layers_15_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83664256)))]; tensor linear_96_cast_fp16 = linear(bias = layers_15_fc2_bias_to_fp16, weight = layers_15_fc2_weight_to_fp16_palettized, x = input_199_cast_fp16)[name = tensor("linear_96_cast_fp16")]; tensor input_201_cast_fp16 = add(x = input_195_cast_fp16, y = linear_96_cast_fp16)[name = tensor("input_201_cast_fp16")]; tensor var_1264 = const()[name = tensor("op_1264"), val = tensor(-1)]; tensor x_101_axes_0 = const()[name = tensor("x_101_axes_0"), val = tensor([-1])]; tensor layers_16_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_16_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83666112)))]; tensor layers_16_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83667968)))]; tensor var_1267_to_fp16 = const()[name = tensor("op_1267_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_101_cast_fp16 = layer_norm(axes = x_101_axes_0, beta = layers_16_self_attn_layer_norm_bias_to_fp16, epsilon = var_1267_to_fp16, gamma = layers_16_self_attn_layer_norm_weight_to_fp16, x = input_201_cast_fp16)[name = tensor("x_101_cast_fp16")]; tensor layers_16_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(83669824))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84071296))), name = tensor("layers_16_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_16_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84071424)))]; tensor linear_97_cast_fp16 = linear(bias = layers_16_self_attn_q_proj_bias_to_fp16, weight = layers_16_self_attn_q_proj_weight_to_fp16_palettized, x = x_101_cast_fp16)[name = tensor("linear_97_cast_fp16")]; tensor concat_66x = const()[name = tensor("concat_66x"), val = tensor([1, -1, 14, 64])]; tensor var_1288_cast_fp16 = reshape(shape = concat_66x, x = linear_97_cast_fp16)[name = tensor("op_1288_cast_fp16")]; tensor layers_16_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84073280))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84474752))), name = tensor("layers_16_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_16_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84474880)))]; tensor linear_98_cast_fp16 = linear(bias = layers_16_self_attn_k_proj_bias_to_fp16, weight = layers_16_self_attn_k_proj_weight_to_fp16_palettized, x = x_101_cast_fp16)[name = tensor("linear_98_cast_fp16")]; tensor concat_67x = const()[name = tensor("concat_67x"), val = tensor([1, -1, 14, 64])]; tensor var_1294_cast_fp16 = reshape(shape = concat_67x, x = linear_98_cast_fp16)[name = tensor("op_1294_cast_fp16")]; tensor layers_16_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84476736))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84878208))), name = tensor("layers_16_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_16_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84878336)))]; tensor linear_99_cast_fp16 = linear(bias = layers_16_self_attn_v_proj_bias_to_fp16, weight = layers_16_self_attn_v_proj_weight_to_fp16_palettized, x = x_101_cast_fp16)[name = tensor("linear_99_cast_fp16")]; tensor concat_68x = const()[name = tensor("concat_68x"), val = tensor([1, -1, 14, 64])]; tensor var_1300_cast_fp16 = reshape(shape = concat_68x, x = linear_99_cast_fp16)[name = tensor("op_1300_cast_fp16")]; tensor v_33_perm_0 = const()[name = tensor("v_33_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_1303_transpose_x_0 = const()[name = tensor("op_1303_transpose_x_0"), val = tensor(false)]; tensor var_1303_transpose_y_0 = const()[name = tensor("op_1303_transpose_y_0"), val = tensor(false)]; tensor transpose_104_perm_0 = const()[name = tensor("transpose_104_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_105_perm_0 = const()[name = tensor("transpose_105_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_105 = transpose(perm = transpose_105_perm_0, x = var_1294_cast_fp16)[name = tensor("transpose_114")]; tensor transpose_104 = transpose(perm = transpose_104_perm_0, x = var_1288_cast_fp16)[name = tensor("transpose_115")]; tensor var_1303_cast_fp16 = matmul(transpose_x = var_1303_transpose_x_0, transpose_y = var_1303_transpose_y_0, x = transpose_104, y = transpose_105)[name = tensor("op_1303_cast_fp16")]; tensor var_1304_to_fp16 = const()[name = tensor("op_1304_to_fp16"), val = tensor(0x1p-3)]; tensor input_203_cast_fp16 = mul(x = var_1303_cast_fp16, y = var_1304_to_fp16)[name = tensor("input_203_cast_fp16")]; tensor attn_33_cast_fp16 = softmax(axis = var_1264, x = input_203_cast_fp16)[name = tensor("attn_33_cast_fp16")]; tensor out_33_transpose_x_0 = const()[name = tensor("out_33_transpose_x_0"), val = tensor(false)]; tensor out_33_transpose_y_0 = const()[name = tensor("out_33_transpose_y_0"), val = tensor(false)]; tensor v_33_cast_fp16 = transpose(perm = v_33_perm_0, x = var_1300_cast_fp16)[name = tensor("transpose_113")]; tensor out_33_cast_fp16 = matmul(transpose_x = out_33_transpose_x_0, transpose_y = out_33_transpose_y_0, x = attn_33_cast_fp16, y = v_33_cast_fp16)[name = tensor("out_33_cast_fp16")]; tensor var_1308_perm_0 = const()[name = tensor("op_1308_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_69x = const()[name = tensor("concat_69x"), val = tensor([1, -1, 896])]; tensor var_1308_cast_fp16 = transpose(perm = var_1308_perm_0, x = out_33_cast_fp16)[name = tensor("transpose_112")]; tensor input_205_cast_fp16 = reshape(shape = concat_69x, x = var_1308_cast_fp16)[name = tensor("input_205_cast_fp16")]; tensor layers_16_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(84880192))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85281664))), name = tensor("layers_16_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_16_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_16_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85281792)))]; tensor linear_100_cast_fp16 = linear(bias = layers_16_self_attn_out_proj_bias_to_fp16, weight = layers_16_self_attn_out_proj_weight_to_fp16_palettized, x = input_205_cast_fp16)[name = tensor("linear_100_cast_fp16")]; tensor input_207_cast_fp16 = add(x = input_201_cast_fp16, y = linear_100_cast_fp16)[name = tensor("input_207_cast_fp16")]; tensor input_209_axes_0 = const()[name = tensor("input_209_axes_0"), val = tensor([-1])]; tensor layers_16_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_16_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85283648)))]; tensor layers_16_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_16_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85285504)))]; tensor input_209_cast_fp16 = layer_norm(axes = input_209_axes_0, beta = layers_16_final_layer_norm_bias_to_fp16, epsilon = var_1267_to_fp16, gamma = layers_16_final_layer_norm_weight_to_fp16, x = input_207_cast_fp16)[name = tensor("input_209_cast_fp16")]; tensor layers_16_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(85287360))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86893056))), name = tensor("layers_16_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_16_fc1_bias_to_fp16 = const()[name = tensor("layers_16_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86893184)))]; tensor linear_101_cast_fp16 = linear(bias = layers_16_fc1_bias_to_fp16, weight = layers_16_fc1_weight_to_fp16_palettized, x = input_209_cast_fp16)[name = tensor("linear_101_cast_fp16")]; tensor input_211_mode_0 = const()[name = tensor("input_211_mode_0"), val = tensor("EXACT")]; tensor input_211_cast_fp16 = gelu(mode = input_211_mode_0, x = linear_101_cast_fp16)[name = tensor("input_211_cast_fp16")]; tensor layers_16_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(86900416))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88506112))), name = tensor("layers_16_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_16_fc2_bias_to_fp16 = const()[name = tensor("layers_16_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88506240)))]; tensor linear_102_cast_fp16 = linear(bias = layers_16_fc2_bias_to_fp16, weight = layers_16_fc2_weight_to_fp16_palettized, x = input_211_cast_fp16)[name = tensor("linear_102_cast_fp16")]; tensor input_213_cast_fp16 = add(x = input_207_cast_fp16, y = linear_102_cast_fp16)[name = tensor("input_213_cast_fp16")]; tensor var_1334 = const()[name = tensor("op_1334"), val = tensor(-1)]; tensor x_107_axes_0 = const()[name = tensor("x_107_axes_0"), val = tensor([-1])]; tensor layers_17_self_attn_layer_norm_weight_to_fp16 = const()[name = tensor("layers_17_self_attn_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88508096)))]; tensor layers_17_self_attn_layer_norm_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88509952)))]; tensor var_1337_to_fp16 = const()[name = tensor("op_1337_to_fp16"), val = tensor(0x1.5p-17)]; tensor x_107_cast_fp16 = layer_norm(axes = x_107_axes_0, beta = layers_17_self_attn_layer_norm_bias_to_fp16, epsilon = var_1337_to_fp16, gamma = layers_17_self_attn_layer_norm_weight_to_fp16, x = input_213_cast_fp16)[name = tensor("x_107_cast_fp16")]; tensor layers_17_self_attn_q_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88511808))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88913280))), name = tensor("layers_17_self_attn_q_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_17_self_attn_q_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_q_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88913408)))]; tensor linear_103_cast_fp16 = linear(bias = layers_17_self_attn_q_proj_bias_to_fp16, weight = layers_17_self_attn_q_proj_weight_to_fp16_palettized, x = x_107_cast_fp16)[name = tensor("linear_103_cast_fp16")]; tensor concat_70x = const()[name = tensor("concat_70x"), val = tensor([1, -1, 14, 64])]; tensor var_1358_cast_fp16 = reshape(shape = concat_70x, x = linear_103_cast_fp16)[name = tensor("op_1358_cast_fp16")]; tensor layers_17_self_attn_k_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(88915264))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89316736))), name = tensor("layers_17_self_attn_k_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_17_self_attn_k_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_k_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89316864)))]; tensor linear_104_cast_fp16 = linear(bias = layers_17_self_attn_k_proj_bias_to_fp16, weight = layers_17_self_attn_k_proj_weight_to_fp16_palettized, x = x_107_cast_fp16)[name = tensor("linear_104_cast_fp16")]; tensor concat_71x = const()[name = tensor("concat_71x"), val = tensor([1, -1, 14, 64])]; tensor var_1364_cast_fp16 = reshape(shape = concat_71x, x = linear_104_cast_fp16)[name = tensor("op_1364_cast_fp16")]; tensor layers_17_self_attn_v_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89318720))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89720192))), name = tensor("layers_17_self_attn_v_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_17_self_attn_v_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_v_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89720320)))]; tensor linear_105_cast_fp16 = linear(bias = layers_17_self_attn_v_proj_bias_to_fp16, weight = layers_17_self_attn_v_proj_weight_to_fp16_palettized, x = x_107_cast_fp16)[name = tensor("linear_105_cast_fp16")]; tensor concat_72x = const()[name = tensor("concat_72x"), val = tensor([1, -1, 14, 64])]; tensor var_1370_cast_fp16 = reshape(shape = concat_72x, x = linear_105_cast_fp16)[name = tensor("op_1370_cast_fp16")]; tensor v_perm_0 = const()[name = tensor("v_perm_0"), val = tensor([0, 2, -3, -1])]; tensor var_1373_transpose_x_0 = const()[name = tensor("op_1373_transpose_x_0"), val = tensor(false)]; tensor var_1373_transpose_y_0 = const()[name = tensor("op_1373_transpose_y_0"), val = tensor(false)]; tensor transpose_106_perm_0 = const()[name = tensor("transpose_106_perm_0"), val = tensor([0, 2, -3, -1])]; tensor transpose_107_perm_0 = const()[name = tensor("transpose_107_perm_0"), val = tensor([0, 2, -1, -3])]; tensor transpose_107 = transpose(perm = transpose_107_perm_0, x = var_1364_cast_fp16)[name = tensor("transpose_110")]; tensor transpose_106 = transpose(perm = transpose_106_perm_0, x = var_1358_cast_fp16)[name = tensor("transpose_111")]; tensor var_1373_cast_fp16 = matmul(transpose_x = var_1373_transpose_x_0, transpose_y = var_1373_transpose_y_0, x = transpose_106, y = transpose_107)[name = tensor("op_1373_cast_fp16")]; tensor var_1374_to_fp16 = const()[name = tensor("op_1374_to_fp16"), val = tensor(0x1p-3)]; tensor input_215_cast_fp16 = mul(x = var_1373_cast_fp16, y = var_1374_to_fp16)[name = tensor("input_215_cast_fp16")]; tensor attn_cast_fp16 = softmax(axis = var_1334, x = input_215_cast_fp16)[name = tensor("attn_cast_fp16")]; tensor out_transpose_x_0 = const()[name = tensor("out_transpose_x_0"), val = tensor(false)]; tensor out_transpose_y_0 = const()[name = tensor("out_transpose_y_0"), val = tensor(false)]; tensor v_cast_fp16 = transpose(perm = v_perm_0, x = var_1370_cast_fp16)[name = tensor("transpose_109")]; tensor out_cast_fp16 = matmul(transpose_x = out_transpose_x_0, transpose_y = out_transpose_y_0, x = attn_cast_fp16, y = v_cast_fp16)[name = tensor("out_cast_fp16")]; tensor var_1378_perm_0 = const()[name = tensor("op_1378_perm_0"), val = tensor([0, 2, 1, 3])]; tensor concat_73x = const()[name = tensor("concat_73x"), val = tensor([1, -1, 896])]; tensor var_1378_cast_fp16 = transpose(perm = var_1378_perm_0, x = out_cast_fp16)[name = tensor("transpose_108")]; tensor input_217_cast_fp16 = reshape(shape = concat_73x, x = var_1378_cast_fp16)[name = tensor("input_217_cast_fp16")]; tensor layers_17_self_attn_out_proj_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(89722176))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90123648))), name = tensor("layers_17_self_attn_out_proj_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor layers_17_self_attn_out_proj_bias_to_fp16 = const()[name = tensor("layers_17_self_attn_out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90123776)))]; tensor linear_106_cast_fp16 = linear(bias = layers_17_self_attn_out_proj_bias_to_fp16, weight = layers_17_self_attn_out_proj_weight_to_fp16_palettized, x = input_217_cast_fp16)[name = tensor("linear_106_cast_fp16")]; tensor input_219_cast_fp16 = add(x = input_213_cast_fp16, y = linear_106_cast_fp16)[name = tensor("input_219_cast_fp16")]; tensor input_221_axes_0 = const()[name = tensor("input_221_axes_0"), val = tensor([-1])]; tensor layers_17_final_layer_norm_weight_to_fp16 = const()[name = tensor("layers_17_final_layer_norm_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90125632)))]; tensor layers_17_final_layer_norm_bias_to_fp16 = const()[name = tensor("layers_17_final_layer_norm_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90127488)))]; tensor input_221_cast_fp16 = layer_norm(axes = input_221_axes_0, beta = layers_17_final_layer_norm_bias_to_fp16, epsilon = var_1337_to_fp16, gamma = layers_17_final_layer_norm_weight_to_fp16, x = input_219_cast_fp16)[name = tensor("input_221_cast_fp16")]; tensor layers_17_fc1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(90129344))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91735040))), name = tensor("layers_17_fc1_weight_to_fp16_palettized"), shape = tensor([3584, 896])]; tensor layers_17_fc1_bias_to_fp16 = const()[name = tensor("layers_17_fc1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91735168)))]; tensor linear_107_cast_fp16 = linear(bias = layers_17_fc1_bias_to_fp16, weight = layers_17_fc1_weight_to_fp16_palettized, x = input_221_cast_fp16)[name = tensor("linear_107_cast_fp16")]; tensor input_223_mode_0 = const()[name = tensor("input_223_mode_0"), val = tensor("EXACT")]; tensor input_223_cast_fp16 = gelu(mode = input_223_mode_0, x = linear_107_cast_fp16)[name = tensor("input_223_cast_fp16")]; tensor layers_17_fc2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(91742400))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93348096))), name = tensor("layers_17_fc2_weight_to_fp16_palettized"), shape = tensor([896, 3584])]; tensor layers_17_fc2_bias_to_fp16 = const()[name = tensor("layers_17_fc2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93348224)))]; tensor linear_108_cast_fp16 = linear(bias = layers_17_fc2_bias_to_fp16, weight = layers_17_fc2_weight_to_fp16_palettized, x = input_223_cast_fp16)[name = tensor("linear_108_cast_fp16")]; tensor input_225_cast_fp16 = add(x = input_219_cast_fp16, y = linear_108_cast_fp16)[name = tensor("input_225_cast_fp16")]; tensor input_227_axes_0 = const()[name = tensor("input_227_axes_0"), val = tensor([-1])]; tensor ln_post_weight_to_fp16 = const()[name = tensor("ln_post_weight_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93350080)))]; tensor ln_post_bias_to_fp16 = const()[name = tensor("ln_post_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93351936)))]; tensor var_1398_to_fp16 = const()[name = tensor("op_1398_to_fp16"), val = tensor(0x1.5p-17)]; tensor input_227_cast_fp16 = layer_norm(axes = input_227_axes_0, beta = ln_post_bias_to_fp16, epsilon = var_1398_to_fp16, gamma = ln_post_weight_to_fp16, x = input_225_cast_fp16)[name = tensor("input_227_cast_fp16")]; tensor proj1_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93353792))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93755264))), name = tensor("proj1_weight_to_fp16_palettized"), shape = tensor([896, 896])]; tensor proj1_bias_to_fp16 = const()[name = tensor("proj1_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93755392)))]; tensor linear_109_cast_fp16 = linear(bias = proj1_bias_to_fp16, weight = proj1_weight_to_fp16_palettized, x = input_227_cast_fp16)[name = tensor("linear_109_cast_fp16")]; tensor input_mode_0 = const()[name = tensor("input_mode_0"), val = tensor("EXACT")]; tensor input_cast_fp16 = gelu(mode = input_mode_0, x = linear_109_cast_fp16)[name = tensor("input_cast_fp16")]; tensor proj2_weight_to_fp16_palettized = constexpr_lut_to_dense()[indices = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(93757248))), lut = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94216064))), name = tensor("proj2_weight_to_fp16_palettized"), shape = tensor([1024, 896])]; tensor proj2_bias_to_fp16 = const()[name = tensor("proj2_bias_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/weight.bin"), offset = tensor(94216192)))]; tensor audio_embeddings = linear(bias = proj2_bias_to_fp16, weight = proj2_weight_to_fp16_palettized, x = input_cast_fp16)[name = tensor("linear_110_cast_fp16")]; } -> (audio_embeddings); }