program(1.3) [buildInfo = dict({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.25.1"}})] { func infer(tensor hidden_states) { tensor var_37 = const()[name = string("op_37"), val = tensor([0, 2, 1])]; tensor input_axes_0 = const()[name = string("input_axes_0"), val = tensor([2])]; tensor var_38_cast_fp16 = transpose(perm = var_37, x = hidden_states)[name = string("transpose_16")]; tensor input_cast_fp16 = expand_dims(axes = input_axes_0, x = var_38_cast_fp16)[name = string("input_cast_fp16")]; string var_51_pad_type_0 = const()[name = string("op_51_pad_type_0"), val = string("valid")]; tensor var_51_strides_0 = const()[name = string("op_51_strides_0"), val = tensor([1, 1])]; tensor var_51_pad_0 = const()[name = string("op_51_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_51_dilations_0 = const()[name = string("op_51_dilations_0"), val = tensor([1, 1])]; int32 var_51_groups_0 = const()[name = string("op_51_groups_0"), val = int32(1)]; tensor heads_0_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19447936))))[name = string("heads_0_weight_promoted_to_fp16_palettized")]; tensor var_51_cast_fp16 = conv(dilations = var_51_dilations_0, groups = var_51_groups_0, pad = var_51_pad_0, pad_type = var_51_pad_type_0, strides = var_51_strides_0, weight = heads_0_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_51_cast_fp16")]; tensor var_53_axes_0 = const()[name = string("op_53_axes_0"), val = tensor([2])]; tensor var_53_cast_fp16 = squeeze(axes = var_53_axes_0, x = var_51_cast_fp16)[name = string("op_53_cast_fp16")]; tensor var_56_perm_0 = const()[name = string("op_56_perm_0"), val = tensor([0, 2, 1])]; string var_67_pad_type_0 = const()[name = string("op_67_pad_type_0"), val = string("valid")]; tensor var_67_strides_0 = const()[name = string("op_67_strides_0"), val = tensor([1, 1])]; tensor var_67_pad_0 = const()[name = string("op_67_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_67_dilations_0 = const()[name = string("op_67_dilations_0"), val = tensor([1, 1])]; int32 var_67_groups_0 = const()[name = string("op_67_groups_0"), val = int32(1)]; tensor heads_1_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20055744))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39503616))))[name = string("heads_1_weight_promoted_to_fp16_palettized")]; tensor var_67_cast_fp16 = conv(dilations = var_67_dilations_0, groups = var_67_groups_0, pad = var_67_pad_0, pad_type = var_67_pad_type_0, strides = var_67_strides_0, weight = heads_1_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_67_cast_fp16")]; tensor var_69_axes_0 = const()[name = string("op_69_axes_0"), val = tensor([2])]; tensor var_69_cast_fp16 = squeeze(axes = var_69_axes_0, x = var_67_cast_fp16)[name = string("op_69_cast_fp16")]; tensor var_72_perm_0 = const()[name = string("op_72_perm_0"), val = tensor([0, 2, 1])]; string var_83_pad_type_0 = const()[name = string("op_83_pad_type_0"), val = string("valid")]; tensor var_83_strides_0 = const()[name = string("op_83_strides_0"), val = tensor([1, 1])]; tensor var_83_pad_0 = const()[name = string("op_83_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_83_dilations_0 = const()[name = string("op_83_dilations_0"), val = tensor([1, 1])]; int32 var_83_groups_0 = const()[name = string("op_83_groups_0"), val = int32(1)]; tensor heads_2_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40111424))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59559296))))[name = string("heads_2_weight_promoted_to_fp16_palettized")]; tensor var_83_cast_fp16 = conv(dilations = var_83_dilations_0, groups = var_83_groups_0, pad = var_83_pad_0, pad_type = var_83_pad_type_0, strides = var_83_strides_0, weight = heads_2_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_83_cast_fp16")]; tensor var_85_axes_0 = const()[name = string("op_85_axes_0"), val = tensor([2])]; tensor var_85_cast_fp16 = squeeze(axes = var_85_axes_0, x = var_83_cast_fp16)[name = string("op_85_cast_fp16")]; tensor var_88_perm_0 = const()[name = string("op_88_perm_0"), val = tensor([0, 2, 1])]; string var_99_pad_type_0 = const()[name = string("op_99_pad_type_0"), val = string("valid")]; tensor var_99_strides_0 = const()[name = string("op_99_strides_0"), val = tensor([1, 1])]; tensor var_99_pad_0 = const()[name = string("op_99_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_99_dilations_0 = const()[name = string("op_99_dilations_0"), val = tensor([1, 1])]; int32 var_99_groups_0 = const()[name = string("op_99_groups_0"), val = int32(1)]; tensor heads_3_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(60167104))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(79614976))))[name = string("heads_3_weight_promoted_to_fp16_palettized")]; tensor var_99_cast_fp16 = conv(dilations = var_99_dilations_0, groups = var_99_groups_0, pad = var_99_pad_0, pad_type = var_99_pad_type_0, strides = var_99_strides_0, weight = heads_3_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_99_cast_fp16")]; tensor var_101_axes_0 = const()[name = string("op_101_axes_0"), val = tensor([2])]; tensor var_101_cast_fp16 = squeeze(axes = var_101_axes_0, x = var_99_cast_fp16)[name = string("op_101_cast_fp16")]; tensor var_104_perm_0 = const()[name = string("op_104_perm_0"), val = tensor([0, 2, 1])]; string var_115_pad_type_0 = const()[name = string("op_115_pad_type_0"), val = string("valid")]; tensor var_115_strides_0 = const()[name = string("op_115_strides_0"), val = tensor([1, 1])]; tensor var_115_pad_0 = const()[name = string("op_115_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_115_dilations_0 = const()[name = string("op_115_dilations_0"), val = tensor([1, 1])]; int32 var_115_groups_0 = const()[name = string("op_115_groups_0"), val = int32(1)]; tensor heads_4_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80222784))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(99670656))))[name = string("heads_4_weight_promoted_to_fp16_palettized")]; tensor var_115_cast_fp16 = conv(dilations = var_115_dilations_0, groups = var_115_groups_0, pad = var_115_pad_0, pad_type = var_115_pad_type_0, strides = var_115_strides_0, weight = heads_4_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_115_cast_fp16")]; tensor var_117_axes_0 = const()[name = string("op_117_axes_0"), val = tensor([2])]; tensor var_117_cast_fp16 = squeeze(axes = var_117_axes_0, x = var_115_cast_fp16)[name = string("op_117_cast_fp16")]; tensor var_120_perm_0 = const()[name = string("op_120_perm_0"), val = tensor([0, 2, 1])]; string var_131_pad_type_0 = const()[name = string("op_131_pad_type_0"), val = string("valid")]; tensor var_131_strides_0 = const()[name = string("op_131_strides_0"), val = tensor([1, 1])]; tensor var_131_pad_0 = const()[name = string("op_131_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_131_dilations_0 = const()[name = string("op_131_dilations_0"), val = tensor([1, 1])]; int32 var_131_groups_0 = const()[name = string("op_131_groups_0"), val = int32(1)]; tensor heads_5_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(100278464))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(119726336))))[name = string("heads_5_weight_promoted_to_fp16_palettized")]; tensor var_131_cast_fp16 = conv(dilations = var_131_dilations_0, groups = var_131_groups_0, pad = var_131_pad_0, pad_type = var_131_pad_type_0, strides = var_131_strides_0, weight = heads_5_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_131_cast_fp16")]; tensor var_133_axes_0 = const()[name = string("op_133_axes_0"), val = tensor([2])]; tensor var_133_cast_fp16 = squeeze(axes = var_133_axes_0, x = var_131_cast_fp16)[name = string("op_133_cast_fp16")]; tensor var_136_perm_0 = const()[name = string("op_136_perm_0"), val = tensor([0, 2, 1])]; string var_147_pad_type_0 = const()[name = string("op_147_pad_type_0"), val = string("valid")]; tensor var_147_strides_0 = const()[name = string("op_147_strides_0"), val = tensor([1, 1])]; tensor var_147_pad_0 = const()[name = string("op_147_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_147_dilations_0 = const()[name = string("op_147_dilations_0"), val = tensor([1, 1])]; int32 var_147_groups_0 = const()[name = string("op_147_groups_0"), val = int32(1)]; tensor heads_6_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(120334144))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(139782016))))[name = string("heads_6_weight_promoted_to_fp16_palettized")]; tensor var_147_cast_fp16 = conv(dilations = var_147_dilations_0, groups = var_147_groups_0, pad = var_147_pad_0, pad_type = var_147_pad_type_0, strides = var_147_strides_0, weight = heads_6_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_147_cast_fp16")]; tensor var_149_axes_0 = const()[name = string("op_149_axes_0"), val = tensor([2])]; tensor var_149_cast_fp16 = squeeze(axes = var_149_axes_0, x = var_147_cast_fp16)[name = string("op_149_cast_fp16")]; tensor var_152_perm_0 = const()[name = string("op_152_perm_0"), val = tensor([0, 2, 1])]; string var_163_pad_type_0 = const()[name = string("op_163_pad_type_0"), val = string("valid")]; tensor var_163_strides_0 = const()[name = string("op_163_strides_0"), val = tensor([1, 1])]; tensor var_163_pad_0 = const()[name = string("op_163_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_163_dilations_0 = const()[name = string("op_163_dilations_0"), val = tensor([1, 1])]; int32 var_163_groups_0 = const()[name = string("op_163_groups_0"), val = int32(1)]; tensor heads_7_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(140389824))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(159837696))))[name = string("heads_7_weight_promoted_to_fp16_palettized")]; tensor var_163_cast_fp16 = conv(dilations = var_163_dilations_0, groups = var_163_groups_0, pad = var_163_pad_0, pad_type = var_163_pad_type_0, strides = var_163_strides_0, weight = heads_7_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_163_cast_fp16")]; tensor var_165_axes_0 = const()[name = string("op_165_axes_0"), val = tensor([2])]; tensor var_165_cast_fp16 = squeeze(axes = var_165_axes_0, x = var_163_cast_fp16)[name = string("op_165_cast_fp16")]; tensor var_168_perm_0 = const()[name = string("op_168_perm_0"), val = tensor([0, 2, 1])]; string var_179_pad_type_0 = const()[name = string("op_179_pad_type_0"), val = string("valid")]; tensor var_179_strides_0 = const()[name = string("op_179_strides_0"), val = tensor([1, 1])]; tensor var_179_pad_0 = const()[name = string("op_179_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_179_dilations_0 = const()[name = string("op_179_dilations_0"), val = tensor([1, 1])]; int32 var_179_groups_0 = const()[name = string("op_179_groups_0"), val = int32(1)]; tensor heads_8_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(160445504))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(179893376))))[name = string("heads_8_weight_promoted_to_fp16_palettized")]; tensor var_179_cast_fp16 = conv(dilations = var_179_dilations_0, groups = var_179_groups_0, pad = var_179_pad_0, pad_type = var_179_pad_type_0, strides = var_179_strides_0, weight = heads_8_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_179_cast_fp16")]; tensor var_181_axes_0 = const()[name = string("op_181_axes_0"), val = tensor([2])]; tensor var_181_cast_fp16 = squeeze(axes = var_181_axes_0, x = var_179_cast_fp16)[name = string("op_181_cast_fp16")]; tensor var_184_perm_0 = const()[name = string("op_184_perm_0"), val = tensor([0, 2, 1])]; string var_195_pad_type_0 = const()[name = string("op_195_pad_type_0"), val = string("valid")]; tensor var_195_strides_0 = const()[name = string("op_195_strides_0"), val = tensor([1, 1])]; tensor var_195_pad_0 = const()[name = string("op_195_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_195_dilations_0 = const()[name = string("op_195_dilations_0"), val = tensor([1, 1])]; int32 var_195_groups_0 = const()[name = string("op_195_groups_0"), val = int32(1)]; tensor heads_9_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(180501184))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(199949056))))[name = string("heads_9_weight_promoted_to_fp16_palettized")]; tensor var_195_cast_fp16 = conv(dilations = var_195_dilations_0, groups = var_195_groups_0, pad = var_195_pad_0, pad_type = var_195_pad_type_0, strides = var_195_strides_0, weight = heads_9_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_195_cast_fp16")]; tensor var_197_axes_0 = const()[name = string("op_197_axes_0"), val = tensor([2])]; tensor var_197_cast_fp16 = squeeze(axes = var_197_axes_0, x = var_195_cast_fp16)[name = string("op_197_cast_fp16")]; tensor var_200_perm_0 = const()[name = string("op_200_perm_0"), val = tensor([0, 2, 1])]; string var_211_pad_type_0 = const()[name = string("op_211_pad_type_0"), val = string("valid")]; tensor var_211_strides_0 = const()[name = string("op_211_strides_0"), val = tensor([1, 1])]; tensor var_211_pad_0 = const()[name = string("op_211_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_211_dilations_0 = const()[name = string("op_211_dilations_0"), val = tensor([1, 1])]; int32 var_211_groups_0 = const()[name = string("op_211_groups_0"), val = int32(1)]; tensor heads_10_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(200556864))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(220004736))))[name = string("heads_10_weight_promoted_to_fp16_palettized")]; tensor var_211_cast_fp16 = conv(dilations = var_211_dilations_0, groups = var_211_groups_0, pad = var_211_pad_0, pad_type = var_211_pad_type_0, strides = var_211_strides_0, weight = heads_10_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_211_cast_fp16")]; tensor var_213_axes_0 = const()[name = string("op_213_axes_0"), val = tensor([2])]; tensor var_213_cast_fp16 = squeeze(axes = var_213_axes_0, x = var_211_cast_fp16)[name = string("op_213_cast_fp16")]; tensor var_216_perm_0 = const()[name = string("op_216_perm_0"), val = tensor([0, 2, 1])]; string var_227_pad_type_0 = const()[name = string("op_227_pad_type_0"), val = string("valid")]; tensor var_227_strides_0 = const()[name = string("op_227_strides_0"), val = tensor([1, 1])]; tensor var_227_pad_0 = const()[name = string("op_227_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_227_dilations_0 = const()[name = string("op_227_dilations_0"), val = tensor([1, 1])]; int32 var_227_groups_0 = const()[name = string("op_227_groups_0"), val = int32(1)]; tensor heads_11_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(220612544))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(240060416))))[name = string("heads_11_weight_promoted_to_fp16_palettized")]; tensor var_227_cast_fp16 = conv(dilations = var_227_dilations_0, groups = var_227_groups_0, pad = var_227_pad_0, pad_type = var_227_pad_type_0, strides = var_227_strides_0, weight = heads_11_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_227_cast_fp16")]; tensor var_229_axes_0 = const()[name = string("op_229_axes_0"), val = tensor([2])]; tensor var_229_cast_fp16 = squeeze(axes = var_229_axes_0, x = var_227_cast_fp16)[name = string("op_229_cast_fp16")]; tensor var_232_perm_0 = const()[name = string("op_232_perm_0"), val = tensor([0, 2, 1])]; string var_243_pad_type_0 = const()[name = string("op_243_pad_type_0"), val = string("valid")]; tensor var_243_strides_0 = const()[name = string("op_243_strides_0"), val = tensor([1, 1])]; tensor var_243_pad_0 = const()[name = string("op_243_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_243_dilations_0 = const()[name = string("op_243_dilations_0"), val = tensor([1, 1])]; int32 var_243_groups_0 = const()[name = string("op_243_groups_0"), val = int32(1)]; tensor heads_12_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(240668224))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(260116096))))[name = string("heads_12_weight_promoted_to_fp16_palettized")]; tensor var_243_cast_fp16 = conv(dilations = var_243_dilations_0, groups = var_243_groups_0, pad = var_243_pad_0, pad_type = var_243_pad_type_0, strides = var_243_strides_0, weight = heads_12_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_243_cast_fp16")]; tensor var_245_axes_0 = const()[name = string("op_245_axes_0"), val = tensor([2])]; tensor var_245_cast_fp16 = squeeze(axes = var_245_axes_0, x = var_243_cast_fp16)[name = string("op_245_cast_fp16")]; tensor var_248_perm_0 = const()[name = string("op_248_perm_0"), val = tensor([0, 2, 1])]; string var_259_pad_type_0 = const()[name = string("op_259_pad_type_0"), val = string("valid")]; tensor var_259_strides_0 = const()[name = string("op_259_strides_0"), val = tensor([1, 1])]; tensor var_259_pad_0 = const()[name = string("op_259_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_259_dilations_0 = const()[name = string("op_259_dilations_0"), val = tensor([1, 1])]; int32 var_259_groups_0 = const()[name = string("op_259_groups_0"), val = int32(1)]; tensor heads_13_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(260723904))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(280171776))))[name = string("heads_13_weight_promoted_to_fp16_palettized")]; tensor var_259_cast_fp16 = conv(dilations = var_259_dilations_0, groups = var_259_groups_0, pad = var_259_pad_0, pad_type = var_259_pad_type_0, strides = var_259_strides_0, weight = heads_13_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_259_cast_fp16")]; tensor var_261_axes_0 = const()[name = string("op_261_axes_0"), val = tensor([2])]; tensor var_261_cast_fp16 = squeeze(axes = var_261_axes_0, x = var_259_cast_fp16)[name = string("op_261_cast_fp16")]; tensor var_264_perm_0 = const()[name = string("op_264_perm_0"), val = tensor([0, 2, 1])]; string var_275_pad_type_0 = const()[name = string("op_275_pad_type_0"), val = string("valid")]; tensor var_275_strides_0 = const()[name = string("op_275_strides_0"), val = tensor([1, 1])]; tensor var_275_pad_0 = const()[name = string("op_275_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_275_dilations_0 = const()[name = string("op_275_dilations_0"), val = tensor([1, 1])]; int32 var_275_groups_0 = const()[name = string("op_275_groups_0"), val = int32(1)]; tensor heads_14_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(280779584))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(300227456))))[name = string("heads_14_weight_promoted_to_fp16_palettized")]; tensor var_275_cast_fp16 = conv(dilations = var_275_dilations_0, groups = var_275_groups_0, pad = var_275_pad_0, pad_type = var_275_pad_type_0, strides = var_275_strides_0, weight = heads_14_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_275_cast_fp16")]; tensor var_277_axes_0 = const()[name = string("op_277_axes_0"), val = tensor([2])]; tensor var_277_cast_fp16 = squeeze(axes = var_277_axes_0, x = var_275_cast_fp16)[name = string("op_277_cast_fp16")]; tensor var_280_perm_0 = const()[name = string("op_280_perm_0"), val = tensor([0, 2, 1])]; string var_291_pad_type_0 = const()[name = string("op_291_pad_type_0"), val = string("valid")]; tensor var_291_strides_0 = const()[name = string("op_291_strides_0"), val = tensor([1, 1])]; tensor var_291_pad_0 = const()[name = string("op_291_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_291_dilations_0 = const()[name = string("op_291_dilations_0"), val = tensor([1, 1])]; int32 var_291_groups_0 = const()[name = string("op_291_groups_0"), val = int32(1)]; tensor heads_15_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(300835264))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320283136))))[name = string("heads_15_weight_promoted_to_fp16_palettized")]; tensor var_291_cast_fp16 = conv(dilations = var_291_dilations_0, groups = var_291_groups_0, pad = var_291_pad_0, pad_type = var_291_pad_type_0, strides = var_291_strides_0, weight = heads_15_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_291_cast_fp16")]; tensor var_293_axes_0 = const()[name = string("op_293_axes_0"), val = tensor([2])]; tensor var_293_cast_fp16 = squeeze(axes = var_293_axes_0, x = var_291_cast_fp16)[name = string("op_293_cast_fp16")]; tensor var_296_perm_0 = const()[name = string("op_296_perm_0"), val = tensor([0, 2, 1])]; tensor logits1 = transpose(perm = var_56_perm_0, x = var_53_cast_fp16)[name = string("transpose_0")]; tensor logits2 = transpose(perm = var_72_perm_0, x = var_69_cast_fp16)[name = string("transpose_1")]; tensor logits3 = transpose(perm = var_88_perm_0, x = var_85_cast_fp16)[name = string("transpose_2")]; tensor logits4 = transpose(perm = var_104_perm_0, x = var_101_cast_fp16)[name = string("transpose_3")]; tensor logits5 = transpose(perm = var_120_perm_0, x = var_117_cast_fp16)[name = string("transpose_4")]; tensor logits6 = transpose(perm = var_136_perm_0, x = var_133_cast_fp16)[name = string("transpose_5")]; tensor logits7 = transpose(perm = var_152_perm_0, x = var_149_cast_fp16)[name = string("transpose_6")]; tensor logits8 = transpose(perm = var_168_perm_0, x = var_165_cast_fp16)[name = string("transpose_7")]; tensor logits9 = transpose(perm = var_184_perm_0, x = var_181_cast_fp16)[name = string("transpose_8")]; tensor logits10 = transpose(perm = var_200_perm_0, x = var_197_cast_fp16)[name = string("transpose_9")]; tensor logits11 = transpose(perm = var_216_perm_0, x = var_213_cast_fp16)[name = string("transpose_10")]; tensor logits12 = transpose(perm = var_232_perm_0, x = var_229_cast_fp16)[name = string("transpose_11")]; tensor logits13 = transpose(perm = var_248_perm_0, x = var_245_cast_fp16)[name = string("transpose_12")]; tensor logits14 = transpose(perm = var_264_perm_0, x = var_261_cast_fp16)[name = string("transpose_13")]; tensor logits15 = transpose(perm = var_280_perm_0, x = var_277_cast_fp16)[name = string("transpose_14")]; tensor logits16 = transpose(perm = var_296_perm_0, x = var_293_cast_fp16)[name = string("transpose_15")]; } -> (logits1, logits2, logits3, logits4, logits5, logits6, logits7, logits8, logits9, logits10, logits11, logits12, logits13, logits14, logits15, logits16); func verify(tensor hidden_states) { tensor var_40 = const()[name = string("op_40"), val = tensor([0, 2, 1])]; tensor input_axes_0 = const()[name = string("input_axes_0"), val = tensor([2])]; tensor var_41_cast_fp16 = transpose(perm = var_40, x = hidden_states)[name = string("transpose_3")]; tensor input_cast_fp16 = expand_dims(axes = input_axes_0, x = var_41_cast_fp16)[name = string("input_cast_fp16")]; string var_54_pad_type_0 = const()[name = string("op_54_pad_type_0"), val = string("valid")]; tensor var_54_strides_0 = const()[name = string("op_54_strides_0"), val = tensor([1, 1])]; tensor var_54_pad_0 = const()[name = string("op_54_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_54_dilations_0 = const()[name = string("op_54_dilations_0"), val = tensor([1, 1])]; int32 var_54_groups_0 = const()[name = string("op_54_groups_0"), val = int32(1)]; tensor heads_0_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19447936))))[name = string("heads_0_weight_promoted_to_fp16_palettized")]; tensor var_54_cast_fp16 = conv(dilations = var_54_dilations_0, groups = var_54_groups_0, pad = var_54_pad_0, pad_type = var_54_pad_type_0, strides = var_54_strides_0, weight = heads_0_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_54_cast_fp16")]; tensor var_56_axes_0 = const()[name = string("op_56_axes_0"), val = tensor([2])]; tensor var_56_cast_fp16 = squeeze(axes = var_56_axes_0, x = var_54_cast_fp16)[name = string("op_56_cast_fp16")]; bool var_62 = const()[name = string("op_62"), val = bool(true)]; tensor const_97 = const()[name = string("const_97"), val = tensor([1])]; tensor best_1_cast_fp16 = reduce_max(axes = const_97, keep_dims = var_62, x = var_56_cast_fp16)[name = string("best_1_cast_fp16")]; tensor var_65_cast_fp16 = sub(x = best_1_cast_fp16, y = var_56_cast_fp16)[name = string("op_65_cast_fp16")]; fp16 var_66_to_fp16 = const()[name = string("op_66_to_fp16"), val = fp16(0x1p+6)]; tensor var_67_cast_fp16 = mul(x = var_65_cast_fp16, y = var_66_to_fp16)[name = string("op_67_cast_fp16")]; fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(-inf)]; fp16 var_69_to_fp16 = const()[name = string("op_69_to_fp16"), val = fp16(0x1p+0)]; tensor clip_0_cast_fp16 = clip(alpha = const_0_to_fp16, beta = var_69_to_fp16, x = var_67_cast_fp16)[name = string("clip_0_cast_fp16")]; fp16 var_71_to_fp16 = const()[name = string("op_71_to_fp16"), val = fp16(0x1p+6)]; tensor var_72_cast_fp16 = mul(x = clip_0_cast_fp16, y = var_71_to_fp16)[name = string("op_72_cast_fp16")]; fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(-inf)]; fp16 var_74_to_fp16 = const()[name = string("op_74_to_fp16"), val = fp16(0x1p+0)]; tensor clip_1_cast_fp16 = clip(alpha = const_1_to_fp16, beta = var_74_to_fp16, x = var_72_cast_fp16)[name = string("clip_1_cast_fp16")]; fp16 var_76_to_fp16 = const()[name = string("op_76_to_fp16"), val = fp16(0x1p+6)]; tensor var_77_cast_fp16 = mul(x = clip_1_cast_fp16, y = var_76_to_fp16)[name = string("op_77_cast_fp16")]; fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(-inf)]; fp16 var_79_to_fp16 = const()[name = string("op_79_to_fp16"), val = fp16(0x1p+0)]; tensor clip_2_cast_fp16 = clip(alpha = const_2_to_fp16, beta = var_79_to_fp16, x = var_77_cast_fp16)[name = string("clip_2_cast_fp16")]; fp16 var_81_to_fp16 = const()[name = string("op_81_to_fp16"), val = fp16(0x1p+0)]; tensor at_max_1_cast_fp16 = sub(x = var_81_to_fp16, y = clip_2_cast_fp16)[name = string("at_max_1_cast_fp16")]; tensor const_98_to_fp16 = const()[name = string("const_98_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320890944)))]; tensor var_84_cast_fp16 = mul(x = at_max_1_cast_fp16, y = const_98_to_fp16)[name = string("op_84_cast_fp16")]; bool var_87 = const()[name = string("op_87"), val = bool(true)]; tensor const_99 = const()[name = string("const_99"), val = tensor([1])]; tensor var_88_cast_fp16 = reduce_max(axes = const_99, keep_dims = var_87, x = var_84_cast_fp16)[name = string("op_88_cast_fp16")]; fp16 var_89_promoted_to_fp16 = const()[name = string("op_89_promoted_to_fp16"), val = fp16(0x1.28p+7)]; tensor hi_1_cast_fp16 = sub(x = var_89_promoted_to_fp16, y = var_88_cast_fp16)[name = string("hi_1_cast_fp16")]; tensor const_100_to_fp16 = const()[name = string("const_100_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320910016)))]; tensor var_93_cast_fp16 = sub(x = const_100_to_fp16, y = hi_1_cast_fp16)[name = string("op_93_cast_fp16")]; tensor var_94_cast_fp16 = abs(x = var_93_cast_fp16)[name = string("op_94_cast_fp16")]; fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(-inf)]; fp16 var_96_to_fp16 = const()[name = string("op_96_to_fp16"), val = fp16(0x1p+0)]; tensor clip_3_cast_fp16 = clip(alpha = const_3_to_fp16, beta = var_96_to_fp16, x = var_94_cast_fp16)[name = string("clip_3_cast_fp16")]; fp16 var_98_to_fp16 = const()[name = string("op_98_to_fp16"), val = fp16(0x1p+0)]; tensor in_block_1_cast_fp16 = sub(x = var_98_to_fp16, y = clip_3_cast_fp16)[name = string("in_block_1_cast_fp16")]; tensor var_101_cast_fp16 = mul(x = at_max_1_cast_fp16, y = in_block_1_cast_fp16)[name = string("op_101_cast_fp16")]; tensor const_101_to_fp16 = const()[name = string("const_101_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(320929088)))]; tensor var_102_cast_fp16 = mul(x = var_101_cast_fp16, y = const_101_to_fp16)[name = string("op_102_cast_fp16")]; bool var_105 = const()[name = string("op_105"), val = bool(true)]; tensor const_102 = const()[name = string("const_102"), val = tensor([1])]; tensor var_106_cast_fp16 = reduce_max(axes = const_102, keep_dims = var_105, x = var_102_cast_fp16)[name = string("op_106_cast_fp16")]; fp16 var_107_promoted_to_fp16 = const()[name = string("op_107_promoted_to_fp16"), val = fp16(0x1.f8p+5)]; tensor var_109_cast_fp16 = sub(x = var_107_promoted_to_fp16, y = var_106_cast_fp16)[name = string("op_109_cast_fp16")]; string var_120_pad_type_0 = const()[name = string("op_120_pad_type_0"), val = string("valid")]; tensor var_120_strides_0 = const()[name = string("op_120_strides_0"), val = tensor([1, 1])]; tensor var_120_pad_0 = const()[name = string("op_120_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_120_dilations_0 = const()[name = string("op_120_dilations_0"), val = tensor([1, 1])]; int32 var_120_groups_0 = const()[name = string("op_120_groups_0"), val = int32(1)]; tensor heads_1_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20055744))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(39503616))))[name = string("heads_1_weight_promoted_to_fp16_palettized")]; tensor var_120_cast_fp16 = conv(dilations = var_120_dilations_0, groups = var_120_groups_0, pad = var_120_pad_0, pad_type = var_120_pad_type_0, strides = var_120_strides_0, weight = heads_1_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_120_cast_fp16")]; tensor var_122_axes_0 = const()[name = string("op_122_axes_0"), val = tensor([2])]; tensor var_122_cast_fp16 = squeeze(axes = var_122_axes_0, x = var_120_cast_fp16)[name = string("op_122_cast_fp16")]; bool var_128 = const()[name = string("op_128"), val = bool(true)]; tensor const_64 = const()[name = string("const_64"), val = tensor([1])]; tensor best_3_cast_fp16 = reduce_max(axes = const_64, keep_dims = var_128, x = var_122_cast_fp16)[name = string("best_3_cast_fp16")]; tensor var_131_cast_fp16 = sub(x = best_3_cast_fp16, y = var_122_cast_fp16)[name = string("op_131_cast_fp16")]; fp16 var_132_to_fp16 = const()[name = string("op_132_to_fp16"), val = fp16(0x1p+6)]; tensor var_133_cast_fp16 = mul(x = var_131_cast_fp16, y = var_132_to_fp16)[name = string("op_133_cast_fp16")]; fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(-inf)]; fp16 var_135_to_fp16 = const()[name = string("op_135_to_fp16"), val = fp16(0x1p+0)]; tensor clip_4_cast_fp16 = clip(alpha = const_4_to_fp16, beta = var_135_to_fp16, x = var_133_cast_fp16)[name = string("clip_4_cast_fp16")]; fp16 var_137_to_fp16 = const()[name = string("op_137_to_fp16"), val = fp16(0x1p+6)]; tensor var_138_cast_fp16 = mul(x = clip_4_cast_fp16, y = var_137_to_fp16)[name = string("op_138_cast_fp16")]; fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(-inf)]; fp16 var_140_to_fp16 = const()[name = string("op_140_to_fp16"), val = fp16(0x1p+0)]; tensor clip_5_cast_fp16 = clip(alpha = const_5_to_fp16, beta = var_140_to_fp16, x = var_138_cast_fp16)[name = string("clip_5_cast_fp16")]; fp16 var_142_to_fp16 = const()[name = string("op_142_to_fp16"), val = fp16(0x1p+6)]; tensor var_143_cast_fp16 = mul(x = clip_5_cast_fp16, y = var_142_to_fp16)[name = string("op_143_cast_fp16")]; fp16 const_6_to_fp16 = const()[name = string("const_6_to_fp16"), val = fp16(-inf)]; fp16 var_145_to_fp16 = const()[name = string("op_145_to_fp16"), val = fp16(0x1p+0)]; tensor clip_6_cast_fp16 = clip(alpha = const_6_to_fp16, beta = var_145_to_fp16, x = var_143_cast_fp16)[name = string("clip_6_cast_fp16")]; fp16 var_147_to_fp16 = const()[name = string("op_147_to_fp16"), val = fp16(0x1p+0)]; tensor at_max_3_cast_fp16 = sub(x = var_147_to_fp16, y = clip_6_cast_fp16)[name = string("at_max_3_cast_fp16")]; tensor var_150_cast_fp16 = mul(x = at_max_3_cast_fp16, y = const_98_to_fp16)[name = string("op_150_cast_fp16")]; bool var_153 = const()[name = string("op_153"), val = bool(true)]; tensor const_66 = const()[name = string("const_66"), val = tensor([1])]; tensor var_154_cast_fp16 = reduce_max(axes = const_66, keep_dims = var_153, x = var_150_cast_fp16)[name = string("op_154_cast_fp16")]; fp16 var_155_promoted_to_fp16 = const()[name = string("op_155_promoted_to_fp16"), val = fp16(0x1.28p+7)]; tensor hi_3_cast_fp16 = sub(x = var_155_promoted_to_fp16, y = var_154_cast_fp16)[name = string("hi_3_cast_fp16")]; tensor var_159_cast_fp16 = sub(x = const_100_to_fp16, y = hi_3_cast_fp16)[name = string("op_159_cast_fp16")]; tensor var_160_cast_fp16 = abs(x = var_159_cast_fp16)[name = string("op_160_cast_fp16")]; fp16 const_7_to_fp16 = const()[name = string("const_7_to_fp16"), val = fp16(-inf)]; fp16 var_162_to_fp16 = const()[name = string("op_162_to_fp16"), val = fp16(0x1p+0)]; tensor clip_7_cast_fp16 = clip(alpha = const_7_to_fp16, beta = var_162_to_fp16, x = var_160_cast_fp16)[name = string("clip_7_cast_fp16")]; fp16 var_164_to_fp16 = const()[name = string("op_164_to_fp16"), val = fp16(0x1p+0)]; tensor in_block_3_cast_fp16 = sub(x = var_164_to_fp16, y = clip_7_cast_fp16)[name = string("in_block_3_cast_fp16")]; tensor var_167_cast_fp16 = mul(x = at_max_3_cast_fp16, y = in_block_3_cast_fp16)[name = string("op_167_cast_fp16")]; tensor var_168_cast_fp16 = mul(x = var_167_cast_fp16, y = const_101_to_fp16)[name = string("op_168_cast_fp16")]; bool var_171 = const()[name = string("op_171"), val = bool(true)]; tensor const_69 = const()[name = string("const_69"), val = tensor([1])]; tensor var_172_cast_fp16 = reduce_max(axes = const_69, keep_dims = var_171, x = var_168_cast_fp16)[name = string("op_172_cast_fp16")]; fp16 var_173_promoted_to_fp16 = const()[name = string("op_173_promoted_to_fp16"), val = fp16(0x1.f8p+5)]; tensor var_175_cast_fp16 = sub(x = var_173_promoted_to_fp16, y = var_172_cast_fp16)[name = string("op_175_cast_fp16")]; string var_186_pad_type_0 = const()[name = string("op_186_pad_type_0"), val = string("valid")]; tensor var_186_strides_0 = const()[name = string("op_186_strides_0"), val = tensor([1, 1])]; tensor var_186_pad_0 = const()[name = string("op_186_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_186_dilations_0 = const()[name = string("op_186_dilations_0"), val = tensor([1, 1])]; int32 var_186_groups_0 = const()[name = string("op_186_groups_0"), val = int32(1)]; tensor heads_2_weight_promoted_to_fp16_palettized = constexpr_lut_to_dense(indices = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(40111424))), lut = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(59559296))))[name = string("heads_2_weight_promoted_to_fp16_palettized")]; tensor var_186_cast_fp16 = conv(dilations = var_186_dilations_0, groups = var_186_groups_0, pad = var_186_pad_0, pad_type = var_186_pad_type_0, strides = var_186_strides_0, weight = heads_2_weight_promoted_to_fp16_palettized, x = input_cast_fp16)[name = string("op_186_cast_fp16")]; tensor var_188_axes_0 = const()[name = string("op_188_axes_0"), val = tensor([2])]; tensor var_188_cast_fp16 = squeeze(axes = var_188_axes_0, x = var_186_cast_fp16)[name = string("op_188_cast_fp16")]; bool var_194 = const()[name = string("op_194"), val = bool(true)]; tensor const_145 = const()[name = string("const_145"), val = tensor([1])]; tensor best_5_cast_fp16 = reduce_max(axes = const_145, keep_dims = var_194, x = var_188_cast_fp16)[name = string("best_5_cast_fp16")]; tensor var_197_cast_fp16 = sub(x = best_5_cast_fp16, y = var_188_cast_fp16)[name = string("op_197_cast_fp16")]; fp16 var_198_to_fp16 = const()[name = string("op_198_to_fp16"), val = fp16(0x1p+6)]; tensor var_199_cast_fp16 = mul(x = var_197_cast_fp16, y = var_198_to_fp16)[name = string("op_199_cast_fp16")]; fp16 const_8_to_fp16 = const()[name = string("const_8_to_fp16"), val = fp16(-inf)]; fp16 var_201_to_fp16 = const()[name = string("op_201_to_fp16"), val = fp16(0x1p+0)]; tensor clip_8_cast_fp16 = clip(alpha = const_8_to_fp16, beta = var_201_to_fp16, x = var_199_cast_fp16)[name = string("clip_8_cast_fp16")]; fp16 var_203_to_fp16 = const()[name = string("op_203_to_fp16"), val = fp16(0x1p+6)]; tensor var_204_cast_fp16 = mul(x = clip_8_cast_fp16, y = var_203_to_fp16)[name = string("op_204_cast_fp16")]; fp16 const_9_to_fp16 = const()[name = string("const_9_to_fp16"), val = fp16(-inf)]; fp16 var_206_to_fp16 = const()[name = string("op_206_to_fp16"), val = fp16(0x1p+0)]; tensor clip_9_cast_fp16 = clip(alpha = const_9_to_fp16, beta = var_206_to_fp16, x = var_204_cast_fp16)[name = string("clip_9_cast_fp16")]; fp16 var_208_to_fp16 = const()[name = string("op_208_to_fp16"), val = fp16(0x1p+6)]; tensor var_209_cast_fp16 = mul(x = clip_9_cast_fp16, y = var_208_to_fp16)[name = string("op_209_cast_fp16")]; fp16 const_10_to_fp16 = const()[name = string("const_10_to_fp16"), val = fp16(-inf)]; fp16 var_211_to_fp16 = const()[name = string("op_211_to_fp16"), val = fp16(0x1p+0)]; tensor clip_10_cast_fp16 = clip(alpha = const_10_to_fp16, beta = var_211_to_fp16, x = var_209_cast_fp16)[name = string("clip_10_cast_fp16")]; fp16 var_213_to_fp16 = const()[name = string("op_213_to_fp16"), val = fp16(0x1p+0)]; tensor at_max_5_cast_fp16 = sub(x = var_213_to_fp16, y = clip_10_cast_fp16)[name = string("at_max_5_cast_fp16")]; tensor var_216_cast_fp16 = mul(x = at_max_5_cast_fp16, y = const_98_to_fp16)[name = string("op_216_cast_fp16")]; bool var_219 = const()[name = string("op_219"), val = bool(true)]; tensor const_147 = const()[name = string("const_147"), val = tensor([1])]; tensor var_220_cast_fp16 = reduce_max(axes = const_147, keep_dims = var_219, x = var_216_cast_fp16)[name = string("op_220_cast_fp16")]; fp16 var_221_promoted_to_fp16 = const()[name = string("op_221_promoted_to_fp16"), val = fp16(0x1.28p+7)]; tensor hi_5_cast_fp16 = sub(x = var_221_promoted_to_fp16, y = var_220_cast_fp16)[name = string("hi_5_cast_fp16")]; tensor var_225_cast_fp16 = sub(x = const_100_to_fp16, y = hi_5_cast_fp16)[name = string("op_225_cast_fp16")]; tensor var_226_cast_fp16 = abs(x = var_225_cast_fp16)[name = string("op_226_cast_fp16")]; fp16 const_11_to_fp16 = const()[name = string("const_11_to_fp16"), val = fp16(-inf)]; fp16 var_228_to_fp16 = const()[name = string("op_228_to_fp16"), val = fp16(0x1p+0)]; tensor clip_11_cast_fp16 = clip(alpha = const_11_to_fp16, beta = var_228_to_fp16, x = var_226_cast_fp16)[name = string("clip_11_cast_fp16")]; fp16 var_230_to_fp16 = const()[name = string("op_230_to_fp16"), val = fp16(0x1p+0)]; tensor in_block_5_cast_fp16 = sub(x = var_230_to_fp16, y = clip_11_cast_fp16)[name = string("in_block_5_cast_fp16")]; tensor var_233_cast_fp16 = mul(x = at_max_5_cast_fp16, y = in_block_5_cast_fp16)[name = string("op_233_cast_fp16")]; tensor var_234_cast_fp16 = mul(x = var_233_cast_fp16, y = const_101_to_fp16)[name = string("op_234_cast_fp16")]; bool var_237 = const()[name = string("op_237"), val = bool(true)]; tensor const_150 = const()[name = string("const_150"), val = tensor([1])]; tensor var_238_cast_fp16 = reduce_max(axes = const_150, keep_dims = var_237, x = var_234_cast_fp16)[name = string("op_238_cast_fp16")]; fp16 var_239_promoted_to_fp16 = const()[name = string("op_239_promoted_to_fp16"), val = fp16(0x1.f8p+5)]; tensor var_241_cast_fp16 = sub(x = var_239_promoted_to_fp16, y = var_238_cast_fp16)[name = string("op_241_cast_fp16")]; string var_252_pad_type_0 = const()[name = string("op_252_pad_type_0"), val = string("valid")]; tensor var_252_strides_0 = const()[name = string("op_252_strides_0"), val = tensor([1, 1])]; tensor var_252_pad_0 = const()[name = string("op_252_pad_0"), val = tensor([0, 0, 0, 0])]; tensor