program(1.3) [buildInfo = dict({{"coremlc-component-MIL", "3402.3.2"}, {"coremlc-version", "3402.5.1"}, {"mldb_token", "mldb-7mar5v7y6j"}})] { func main(pixel_buffer image) { tensor img_tensor_raw = pixel_buffer_to_tensor(input=image); tensor img_tensor_sliced = slice_by_index(x = img_tensor_raw, begin = tensor([0, 0, 0]), end = tensor([3, 0, 0]), end_mask = tensor([false, true, true])); tensor img_bgr_batch = expand_dims(axes = tensor([0]), x = img_tensor_sliced); string image_to_fp16_dtype_0 = const()[name = string("image_to_fp16_dtype_0"), val = string("fp16")]; tensor image_to_fp16 = cast(dtype = image_to_fp16_dtype_0, x = img_bgr_batch)[name = string("cast_0")]; fp16 image__scaled___y_0 = const()[name = string("image__scaled___y_0"), val = fp16(0x1.01p-8)]; tensor image__scaled__ = mul(x = image_to_fp16, y = image__scaled___y_0)[name = string("image__scaled__")]; tensor stage0_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(64))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1472))))[name = string("stage0_reparam_conv_weight_cast_fp16")]; tensor stage1_0_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1664))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(2176))))[name = string("stage1_0_reparam_conv_weight_cast_fp16")]; tensor stage1_1_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(2368))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(4736))))[name = string("stage1_1_reparam_conv_weight_cast_fp16")]; tensor stage1_2_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(4928))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(5440))))[name = string("stage1_2_reparam_conv_weight_cast_fp16")]; tensor stage1_3_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(5632))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(8000))))[name = string("stage1_3_reparam_conv_weight_cast_fp16")]; tensor stage2_0_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(8192))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(8704))))[name = string("stage2_0_reparam_conv_weight_cast_fp16")]; tensor stage2_1_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(8896))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(15104))))[name = string("stage2_1_reparam_conv_weight_cast_fp16")]; tensor stage2_2_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(15424))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(16640))))[name = string("stage2_2_reparam_conv_weight_cast_fp16")]; tensor stage2_3_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(16960))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(33408))))[name = string("stage2_3_reparam_conv_weight_cast_fp16")]; tensor stage2_4_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(33728))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(34944))))[name = string("stage2_4_reparam_conv_weight_cast_fp16")]; tensor stage2_5_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(35264))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(51712))))[name = string("stage2_5_reparam_conv_weight_cast_fp16")]; tensor stage2_6_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(52032))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(53248))))[name = string("stage2_6_reparam_conv_weight_cast_fp16")]; tensor stage2_7_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(53568))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(70016))))[name = string("stage2_7_reparam_conv_weight_cast_fp16")]; tensor stage2_8_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(70336))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(71552))))[name = string("stage2_8_reparam_conv_weight_cast_fp16")]; tensor stage2_9_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(71872))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(88320))))[name = string("stage2_9_reparam_conv_weight_cast_fp16")]; tensor stage2_10_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(88640))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(89856))))[name = string("stage2_10_reparam_conv_weight_cast_fp16")]; tensor stage2_11_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(90176))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(106624))))[name = string("stage2_11_reparam_conv_weight_cast_fp16")]; tensor stage2_12_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(106944))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(108160))))[name = string("stage2_12_reparam_conv_weight_cast_fp16")]; tensor stage2_13_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(108480))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(124928))))[name = string("stage2_13_reparam_conv_weight_cast_fp16")]; tensor stage2_14_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(125248))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(126464))))[name = string("stage2_14_reparam_conv_weight_cast_fp16")]; tensor stage2_15_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(126784))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(143232))))[name = string("stage2_15_reparam_conv_weight_cast_fp16")]; tensor stage3_0_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(143552))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(144768))))[name = string("stage3_0_reparam_conv_weight_cast_fp16")]; tensor stage3_1_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(145088))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(177920))))[name = string("stage3_1_reparam_conv_weight_cast_fp16")]; tensor stage3_2_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(178496))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(180864))))[name = string("stage3_2_reparam_conv_weight_cast_fp16")]; tensor stage3_3_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(181440))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(247040))))[name = string("stage3_3_reparam_conv_weight_cast_fp16")]; tensor stage3_4_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(247616))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(249984))))[name = string("stage3_4_reparam_conv_weight_cast_fp16")]; tensor stage3_5_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(250560))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(316160))))[name = string("stage3_5_reparam_conv_weight_cast_fp16")]; tensor stage3_6_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(316736))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(319104))))[name = string("stage3_6_reparam_conv_weight_cast_fp16")]; tensor stage3_7_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(319680))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(385280))))[name = string("stage3_7_reparam_conv_weight_cast_fp16")]; tensor stage3_8_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(385856))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(388224))))[name = string("stage3_8_reparam_conv_weight_cast_fp16")]; tensor stage3_9_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(388800))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(454400))))[name = string("stage3_9_reparam_conv_weight_cast_fp16")]; tensor stage3_10_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(454976))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(457344))))[name = string("stage3_10_reparam_conv_weight_cast_fp16")]; tensor stage3_11_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(457920))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(523520))))[name = string("stage3_11_reparam_conv_weight_cast_fp16")]; tensor stage3_12_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(524096))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(526464))))[name = string("stage3_12_reparam_conv_weight_cast_fp16")]; tensor stage3_13_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(527040))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(592640))))[name = string("stage3_13_reparam_conv_weight_cast_fp16")]; tensor stage3_14_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(593216))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(595584))))[name = string("stage3_14_reparam_conv_weight_cast_fp16")]; tensor stage3_15_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(596160))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(661760))))[name = string("stage3_15_reparam_conv_weight_cast_fp16")]; tensor stage3_16_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(662336))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(664704))))[name = string("stage3_16_reparam_conv_weight_cast_fp16")]; tensor stage3_17_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(665280))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(730880))))[name = string("stage3_17_reparam_conv_weight_cast_fp16")]; tensor stage3_18_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(731456))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(733824))))[name = string("stage3_18_reparam_conv_weight_cast_fp16")]; tensor stage3_19_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(734400))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(800000))))[name = string("stage3_19_reparam_conv_weight_cast_fp16")]; tensor stage4_0_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(800576))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(802944))))[name = string("stage4_0_reparam_conv_weight_cast_fp16")]; tensor stage4_1_reparam_conv_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(803520))), scale = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1065728))))[name = string("stage4_1_reparam_conv_weight_cast_fp16")]; tensor linear_weight_cast_fp16 = constexpr_blockwise_shift_scale(data = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1067840))), scale = tensor([[0x1.6ecp-10]]))[name = string("linear_weight_cast_fp16")]; string input_1_pad_type_0 = const()[name = string("input_1_pad_type_0"), val = string("custom")]; tensor input_1_pad_0 = const()[name = string("input_1_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_1_strides_0 = const()[name = string("input_1_strides_0"), val = tensor([2, 2])]; tensor input_1_dilations_0 = const()[name = string("input_1_dilations_0"), val = tensor([1, 1])]; int32 input_1_groups_0 = const()[name = string("input_1_groups_0"), val = int32(1)]; tensor stage0_reparam_conv_bias_to_fp16 = const()[name = string("stage0_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1068928)))]; fp16 quantize_0_scale_1 = const()[name = string("quantize_0_scale_1"), val = fp16(0x1.02p-7)]; string quantize_0_output_dtype_1 = const()[name = string("quantize_0_output_dtype_1"), val = string("int8")]; tensor quantize_0 = quantize(input = image__scaled__, output_dtype = quantize_0_output_dtype_1, scale = quantize_0_scale_1)[name = string("quantize_0")]; fp16 dequantize_0_scale_1 = const()[name = string("dequantize_0_scale_1"), val = fp16(0x1.02p-7)]; tensor dequantize_0 = dequantize(input = quantize_0, scale = dequantize_0_scale_1)[name = string("dequantize_0")]; tensor input_1_cast_fp16 = conv(bias = stage0_reparam_conv_bias_to_fp16, dilations = input_1_dilations_0, groups = input_1_groups_0, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = input_1_strides_0, weight = stage0_reparam_conv_weight_cast_fp16, x = dequantize_0)[name = string("input_1_cast_fp16")]; tensor input_3_cast_fp16 = relu(x = input_1_cast_fp16)[name = string("input_3_cast_fp16")]; string input_5_pad_type_0 = const()[name = string("input_5_pad_type_0"), val = string("custom")]; tensor input_5_pad_0 = const()[name = string("input_5_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_5_strides_0 = const()[name = string("input_5_strides_0"), val = tensor([2, 2])]; int32 input_5_groups_0 = const()[name = string("input_5_groups_0"), val = int32(48)]; tensor input_5_dilations_0 = const()[name = string("input_5_dilations_0"), val = tensor([1, 1])]; tensor stage1_0_reparam_conv_bias_to_fp16 = const()[name = string("stage1_0_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1069120)))]; fp16 quantize_1_scale_1 = const()[name = string("quantize_1_scale_1"), val = fp16(0x1.538p-8)]; string quantize_1_output_dtype_1 = const()[name = string("quantize_1_output_dtype_1"), val = string("int8")]; tensor quantize_1 = quantize(input = input_3_cast_fp16, output_dtype = quantize_1_output_dtype_1, scale = quantize_1_scale_1)[name = string("quantize_1")]; fp16 dequantize_1_scale_1 = const()[name = string("dequantize_1_scale_1"), val = fp16(0x1.538p-8)]; tensor dequantize_1 = dequantize(input = quantize_1, scale = dequantize_1_scale_1)[name = string("dequantize_1")]; tensor input_5_cast_fp16 = conv(bias = stage1_0_reparam_conv_bias_to_fp16, dilations = input_5_dilations_0, groups = input_5_groups_0, pad = input_5_pad_0, pad_type = input_5_pad_type_0, strides = input_5_strides_0, weight = stage1_0_reparam_conv_weight_cast_fp16, x = dequantize_1)[name = string("input_5_cast_fp16")]; tensor input_7_cast_fp16 = relu(x = input_5_cast_fp16)[name = string("input_7_cast_fp16")]; string input_9_pad_type_0 = const()[name = string("input_9_pad_type_0"), val = string("valid")]; tensor input_9_strides_0 = const()[name = string("input_9_strides_0"), val = tensor([1, 1])]; tensor input_9_pad_0 = const()[name = string("input_9_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_9_dilations_0 = const()[name = string("input_9_dilations_0"), val = tensor([1, 1])]; int32 input_9_groups_0 = const()[name = string("input_9_groups_0"), val = int32(1)]; tensor stage1_1_reparam_conv_bias_to_fp16 = const()[name = string("stage1_1_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1069312)))]; fp16 quantize_2_scale_1 = const()[name = string("quantize_2_scale_1"), val = fp16(0x1.23cp-8)]; string quantize_2_output_dtype_1 = const()[name = string("quantize_2_output_dtype_1"), val = string("int8")]; tensor quantize_2 = quantize(input = input_7_cast_fp16, output_dtype = quantize_2_output_dtype_1, scale = quantize_2_scale_1)[name = string("quantize_2")]; fp16 dequantize_2_scale_1 = const()[name = string("dequantize_2_scale_1"), val = fp16(0x1.23cp-8)]; tensor dequantize_2 = dequantize(input = quantize_2, scale = dequantize_2_scale_1)[name = string("dequantize_2")]; tensor input_9_cast_fp16 = conv(bias = stage1_1_reparam_conv_bias_to_fp16, dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = stage1_1_reparam_conv_weight_cast_fp16, x = dequantize_2)[name = string("input_9_cast_fp16")]; tensor input_11_cast_fp16 = relu(x = input_9_cast_fp16)[name = string("input_11_cast_fp16")]; string input_13_pad_type_0 = const()[name = string("input_13_pad_type_0"), val = string("custom")]; tensor input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_13_groups_0 = const()[name = string("input_13_groups_0"), val = int32(48)]; tensor input_13_strides_0 = const()[name = string("input_13_strides_0"), val = tensor([1, 1])]; tensor input_13_dilations_0 = const()[name = string("input_13_dilations_0"), val = tensor([1, 1])]; tensor stage1_2_reparam_conv_bias_to_fp16 = const()[name = string("stage1_2_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1069504)))]; fp16 quantize_3_scale_1 = const()[name = string("quantize_3_scale_1"), val = fp16(0x1.758p-8)]; string quantize_3_output_dtype_1 = const()[name = string("quantize_3_output_dtype_1"), val = string("int8")]; tensor quantize_3 = quantize(input = input_11_cast_fp16, output_dtype = quantize_3_output_dtype_1, scale = quantize_3_scale_1)[name = string("quantize_3")]; fp16 dequantize_3_scale_1 = const()[name = string("dequantize_3_scale_1"), val = fp16(0x1.758p-8)]; tensor dequantize_3 = dequantize(input = quantize_3, scale = dequantize_3_scale_1)[name = string("dequantize_3")]; tensor input_13_cast_fp16 = conv(bias = stage1_2_reparam_conv_bias_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = stage1_2_reparam_conv_weight_cast_fp16, x = dequantize_3)[name = string("input_13_cast_fp16")]; tensor input_15_cast_fp16 = relu(x = input_13_cast_fp16)[name = string("input_15_cast_fp16")]; string input_17_pad_type_0 = const()[name = string("input_17_pad_type_0"), val = string("valid")]; tensor input_17_strides_0 = const()[name = string("input_17_strides_0"), val = tensor([1, 1])]; tensor input_17_pad_0 = const()[name = string("input_17_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_17_dilations_0 = const()[name = string("input_17_dilations_0"), val = tensor([1, 1])]; int32 input_17_groups_0 = const()[name = string("input_17_groups_0"), val = int32(1)]; tensor stage1_3_reparam_conv_bias_to_fp16 = const()[name = string("stage1_3_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1069696)))]; fp16 quantize_4_scale_1 = const()[name = string("quantize_4_scale_1"), val = fp16(0x1.45cp-8)]; string quantize_4_output_dtype_1 = const()[name = string("quantize_4_output_dtype_1"), val = string("int8")]; tensor quantize_4 = quantize(input = input_15_cast_fp16, output_dtype = quantize_4_output_dtype_1, scale = quantize_4_scale_1)[name = string("quantize_4")]; fp16 dequantize_4_scale_1 = const()[name = string("dequantize_4_scale_1"), val = fp16(0x1.45cp-8)]; tensor dequantize_4 = dequantize(input = quantize_4, scale = dequantize_4_scale_1)[name = string("dequantize_4")]; tensor input_17_cast_fp16 = conv(bias = stage1_3_reparam_conv_bias_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = stage1_3_reparam_conv_weight_cast_fp16, x = dequantize_4)[name = string("input_17_cast_fp16")]; tensor input_19_cast_fp16 = relu(x = input_17_cast_fp16)[name = string("input_19_cast_fp16")]; string input_21_pad_type_0 = const()[name = string("input_21_pad_type_0"), val = string("custom")]; tensor input_21_pad_0 = const()[name = string("input_21_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_21_strides_0 = const()[name = string("input_21_strides_0"), val = tensor([2, 2])]; int32 input_21_groups_0 = const()[name = string("input_21_groups_0"), val = int32(48)]; tensor input_21_dilations_0 = const()[name = string("input_21_dilations_0"), val = tensor([1, 1])]; tensor stage2_0_reparam_conv_bias_to_fp16 = const()[name = string("stage2_0_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1069888)))]; fp16 quantize_5_scale_1 = const()[name = string("quantize_5_scale_1"), val = fp16(0x1.104p-8)]; string quantize_5_output_dtype_1 = const()[name = string("quantize_5_output_dtype_1"), val = string("int8")]; tensor quantize_5 = quantize(input = input_19_cast_fp16, output_dtype = quantize_5_output_dtype_1, scale = quantize_5_scale_1)[name = string("quantize_5")]; fp16 dequantize_5_scale_1 = const()[name = string("dequantize_5_scale_1"), val = fp16(0x1.104p-8)]; tensor dequantize_5 = dequantize(input = quantize_5, scale = dequantize_5_scale_1)[name = string("dequantize_5")]; tensor input_21_cast_fp16 = conv(bias = stage2_0_reparam_conv_bias_to_fp16, dilations = input_21_dilations_0, groups = input_21_groups_0, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = input_21_strides_0, weight = stage2_0_reparam_conv_weight_cast_fp16, x = dequantize_5)[name = string("input_21_cast_fp16")]; tensor input_23_cast_fp16 = relu(x = input_21_cast_fp16)[name = string("input_23_cast_fp16")]; string input_25_pad_type_0 = const()[name = string("input_25_pad_type_0"), val = string("valid")]; tensor input_25_strides_0 = const()[name = string("input_25_strides_0"), val = tensor([1, 1])]; tensor input_25_pad_0 = const()[name = string("input_25_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_25_dilations_0 = const()[name = string("input_25_dilations_0"), val = tensor([1, 1])]; int32 input_25_groups_0 = const()[name = string("input_25_groups_0"), val = int32(1)]; tensor stage2_1_reparam_conv_bias_to_fp16 = const()[name = string("stage2_1_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1070080)))]; fp16 quantize_6_scale_1 = const()[name = string("quantize_6_scale_1"), val = fp16(0x1.094p-8)]; string quantize_6_output_dtype_1 = const()[name = string("quantize_6_output_dtype_1"), val = string("int8")]; tensor quantize_6 = quantize(input = input_23_cast_fp16, output_dtype = quantize_6_output_dtype_1, scale = quantize_6_scale_1)[name = string("quantize_6")]; fp16 dequantize_6_scale_1 = const()[name = string("dequantize_6_scale_1"), val = fp16(0x1.094p-8)]; tensor dequantize_6 = dequantize(input = quantize_6, scale = dequantize_6_scale_1)[name = string("dequantize_6")]; tensor input_25_cast_fp16 = conv(bias = stage2_1_reparam_conv_bias_to_fp16, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = stage2_1_reparam_conv_weight_cast_fp16, x = dequantize_6)[name = string("input_25_cast_fp16")]; tensor input_27_cast_fp16 = relu(x = input_25_cast_fp16)[name = string("input_27_cast_fp16")]; string input_29_pad_type_0 = const()[name = string("input_29_pad_type_0"), val = string("custom")]; tensor input_29_pad_0 = const()[name = string("input_29_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_29_groups_0 = const()[name = string("input_29_groups_0"), val = int32(128)]; tensor input_29_strides_0 = const()[name = string("input_29_strides_0"), val = tensor([1, 1])]; tensor input_29_dilations_0 = const()[name = string("input_29_dilations_0"), val = tensor([1, 1])]; tensor stage2_2_reparam_conv_bias_to_fp16 = const()[name = string("stage2_2_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1070400)))]; fp16 quantize_7_scale_1 = const()[name = string("quantize_7_scale_1"), val = fp16(0x1.57cp-9)]; string quantize_7_output_dtype_1 = const()[name = string("quantize_7_output_dtype_1"), val = string("int8")]; tensor quantize_7 = quantize(input = input_27_cast_fp16, output_dtype = quantize_7_output_dtype_1, scale = quantize_7_scale_1)[name = string("quantize_7")]; fp16 dequantize_7_scale_1 = const()[name = string("dequantize_7_scale_1"), val = fp16(0x1.57cp-9)]; tensor dequantize_7 = dequantize(input = quantize_7, scale = dequantize_7_scale_1)[name = string("dequantize_7")]; tensor input_29_cast_fp16 = conv(bias = stage2_2_reparam_conv_bias_to_fp16, dilations = input_29_dilations_0, groups = input_29_groups_0, pad = input_29_pad_0, pad_type = input_29_pad_type_0, strides = input_29_strides_0, weight = stage2_2_reparam_conv_weight_cast_fp16, x = dequantize_7)[name = string("input_29_cast_fp16")]; tensor input_31_cast_fp16 = relu(x = input_29_cast_fp16)[name = string("input_31_cast_fp16")]; string input_33_pad_type_0 = const()[name = string("input_33_pad_type_0"), val = string("valid")]; tensor input_33_strides_0 = const()[name = string("input_33_strides_0"), val = tensor([1, 1])]; tensor input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_33_dilations_0 = const()[name = string("input_33_dilations_0"), val = tensor([1, 1])]; int32 input_33_groups_0 = const()[name = string("input_33_groups_0"), val = int32(1)]; tensor stage2_3_reparam_conv_bias_to_fp16 = const()[name = string("stage2_3_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1070720)))]; fp16 quantize_8_scale_1 = const()[name = string("quantize_8_scale_1"), val = fp16(0x1.37cp-9)]; string quantize_8_output_dtype_1 = const()[name = string("quantize_8_output_dtype_1"), val = string("int8")]; tensor quantize_8 = quantize(input = input_31_cast_fp16, output_dtype = quantize_8_output_dtype_1, scale = quantize_8_scale_1)[name = string("quantize_8")]; fp16 dequantize_8_scale_1 = const()[name = string("dequantize_8_scale_1"), val = fp16(0x1.37cp-9)]; tensor dequantize_8 = dequantize(input = quantize_8, scale = dequantize_8_scale_1)[name = string("dequantize_8")]; tensor input_33_cast_fp16 = conv(bias = stage2_3_reparam_conv_bias_to_fp16, dilations = input_33_dilations_0, groups = input_33_groups_0, pad = input_33_pad_0, pad_type = input_33_pad_type_0, strides = input_33_strides_0, weight = stage2_3_reparam_conv_weight_cast_fp16, x = dequantize_8)[name = string("input_33_cast_fp16")]; tensor input_35_cast_fp16 = relu(x = input_33_cast_fp16)[name = string("input_35_cast_fp16")]; string input_37_pad_type_0 = const()[name = string("input_37_pad_type_0"), val = string("custom")]; tensor input_37_pad_0 = const()[name = string("input_37_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_37_groups_0 = const()[name = string("input_37_groups_0"), val = int32(128)]; tensor input_37_strides_0 = const()[name = string("input_37_strides_0"), val = tensor([1, 1])]; tensor input_37_dilations_0 = const()[name = string("input_37_dilations_0"), val = tensor([1, 1])]; tensor stage2_4_reparam_conv_bias_to_fp16 = const()[name = string("stage2_4_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1071040)))]; fp16 quantize_9_scale_1 = const()[name = string("quantize_9_scale_1"), val = fp16(0x1.494p-9)]; string quantize_9_output_dtype_1 = const()[name = string("quantize_9_output_dtype_1"), val = string("int8")]; tensor quantize_9 = quantize(input = input_35_cast_fp16, output_dtype = quantize_9_output_dtype_1, scale = quantize_9_scale_1)[name = string("quantize_9")]; fp16 dequantize_9_scale_1 = const()[name = string("dequantize_9_scale_1"), val = fp16(0x1.494p-9)]; tensor dequantize_9 = dequantize(input = quantize_9, scale = dequantize_9_scale_1)[name = string("dequantize_9")]; tensor input_37_cast_fp16 = conv(bias = stage2_4_reparam_conv_bias_to_fp16, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = stage2_4_reparam_conv_weight_cast_fp16, x = dequantize_9)[name = string("input_37_cast_fp16")]; tensor input_39_cast_fp16 = relu(x = input_37_cast_fp16)[name = string("input_39_cast_fp16")]; string input_41_pad_type_0 = const()[name = string("input_41_pad_type_0"), val = string("valid")]; tensor input_41_strides_0 = const()[name = string("input_41_strides_0"), val = tensor([1, 1])]; tensor input_41_pad_0 = const()[name = string("input_41_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_41_dilations_0 = const()[name = string("input_41_dilations_0"), val = tensor([1, 1])]; int32 input_41_groups_0 = const()[name = string("input_41_groups_0"), val = int32(1)]; tensor stage2_5_reparam_conv_bias_to_fp16 = const()[name = string("stage2_5_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1071360)))]; fp16 quantize_10_scale_1 = const()[name = string("quantize_10_scale_1"), val = fp16(0x1.51cp-9)]; string quantize_10_output_dtype_1 = const()[name = string("quantize_10_output_dtype_1"), val = string("int8")]; tensor quantize_10 = quantize(input = input_39_cast_fp16, output_dtype = quantize_10_output_dtype_1, scale = quantize_10_scale_1)[name = string("quantize_10")]; fp16 dequantize_10_scale_1 = const()[name = string("dequantize_10_scale_1"), val = fp16(0x1.51cp-9)]; tensor dequantize_10 = dequantize(input = quantize_10, scale = dequantize_10_scale_1)[name = string("dequantize_10")]; tensor input_41_cast_fp16 = conv(bias = stage2_5_reparam_conv_bias_to_fp16, dilations = input_41_dilations_0, groups = input_41_groups_0, pad = input_41_pad_0, pad_type = input_41_pad_type_0, strides = input_41_strides_0, weight = stage2_5_reparam_conv_weight_cast_fp16, x = dequantize_10)[name = string("input_41_cast_fp16")]; tensor input_43_cast_fp16 = relu(x = input_41_cast_fp16)[name = string("input_43_cast_fp16")]; string input_45_pad_type_0 = const()[name = string("input_45_pad_type_0"), val = string("custom")]; tensor input_45_pad_0 = const()[name = string("input_45_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_45_groups_0 = const()[name = string("input_45_groups_0"), val = int32(128)]; tensor input_45_strides_0 = const()[name = string("input_45_strides_0"), val = tensor([1, 1])]; tensor input_45_dilations_0 = const()[name = string("input_45_dilations_0"), val = tensor([1, 1])]; tensor stage2_6_reparam_conv_bias_to_fp16 = const()[name = string("stage2_6_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1071680)))]; fp16 quantize_11_scale_1 = const()[name = string("quantize_11_scale_1"), val = fp16(0x1.884p-9)]; string quantize_11_output_dtype_1 = const()[name = string("quantize_11_output_dtype_1"), val = string("int8")]; tensor quantize_11 = quantize(input = input_43_cast_fp16, output_dtype = quantize_11_output_dtype_1, scale = quantize_11_scale_1)[name = string("quantize_11")]; fp16 dequantize_11_scale_1 = const()[name = string("dequantize_11_scale_1"), val = fp16(0x1.884p-9)]; tensor dequantize_11 = dequantize(input = quantize_11, scale = dequantize_11_scale_1)[name = string("dequantize_11")]; tensor input_45_cast_fp16 = conv(bias = stage2_6_reparam_conv_bias_to_fp16, dilations = input_45_dilations_0, groups = input_45_groups_0, pad = input_45_pad_0, pad_type = input_45_pad_type_0, strides = input_45_strides_0, weight = stage2_6_reparam_conv_weight_cast_fp16, x = dequantize_11)[name = string("input_45_cast_fp16")]; tensor input_47_cast_fp16 = relu(x = input_45_cast_fp16)[name = string("input_47_cast_fp16")]; string input_49_pad_type_0 = const()[name = string("input_49_pad_type_0"), val = string("valid")]; tensor input_49_strides_0 = const()[name = string("input_49_strides_0"), val = tensor([1, 1])]; tensor input_49_pad_0 = const()[name = string("input_49_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_49_dilations_0 = const()[name = string("input_49_dilations_0"), val = tensor([1, 1])]; int32 input_49_groups_0 = const()[name = string("input_49_groups_0"), val = int32(1)]; tensor stage2_7_reparam_conv_bias_to_fp16 = const()[name = string("stage2_7_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1072000)))]; fp16 quantize_12_scale_1 = const()[name = string("quantize_12_scale_1"), val = fp16(0x1.96cp-9)]; string quantize_12_output_dtype_1 = const()[name = string("quantize_12_output_dtype_1"), val = string("int8")]; tensor quantize_12 = quantize(input = input_47_cast_fp16, output_dtype = quantize_12_output_dtype_1, scale = quantize_12_scale_1)[name = string("quantize_12")]; fp16 dequantize_12_scale_1 = const()[name = string("dequantize_12_scale_1"), val = fp16(0x1.96cp-9)]; tensor dequantize_12 = dequantize(input = quantize_12, scale = dequantize_12_scale_1)[name = string("dequantize_12")]; tensor input_49_cast_fp16 = conv(bias = stage2_7_reparam_conv_bias_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = stage2_7_reparam_conv_weight_cast_fp16, x = dequantize_12)[name = string("input_49_cast_fp16")]; tensor input_51_cast_fp16 = relu(x = input_49_cast_fp16)[name = string("input_51_cast_fp16")]; string input_53_pad_type_0 = const()[name = string("input_53_pad_type_0"), val = string("custom")]; tensor input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_53_groups_0 = const()[name = string("input_53_groups_0"), val = int32(128)]; tensor input_53_strides_0 = const()[name = string("input_53_strides_0"), val = tensor([1, 1])]; tensor input_53_dilations_0 = const()[name = string("input_53_dilations_0"), val = tensor([1, 1])]; tensor stage2_8_reparam_conv_bias_to_fp16 = const()[name = string("stage2_8_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1072320)))]; fp16 quantize_13_scale_1 = const()[name = string("quantize_13_scale_1"), val = fp16(0x1.87cp-9)]; string quantize_13_output_dtype_1 = const()[name = string("quantize_13_output_dtype_1"), val = string("int8")]; tensor quantize_13 = quantize(input = input_51_cast_fp16, output_dtype = quantize_13_output_dtype_1, scale = quantize_13_scale_1)[name = string("quantize_13")]; fp16 dequantize_13_scale_1 = const()[name = string("dequantize_13_scale_1"), val = fp16(0x1.87cp-9)]; tensor dequantize_13 = dequantize(input = quantize_13, scale = dequantize_13_scale_1)[name = string("dequantize_13")]; tensor input_53_cast_fp16 = conv(bias = stage2_8_reparam_conv_bias_to_fp16, dilations = input_53_dilations_0, groups = input_53_groups_0, pad = input_53_pad_0, pad_type = input_53_pad_type_0, strides = input_53_strides_0, weight = stage2_8_reparam_conv_weight_cast_fp16, x = dequantize_13)[name = string("input_53_cast_fp16")]; tensor input_55_cast_fp16 = relu(x = input_53_cast_fp16)[name = string("input_55_cast_fp16")]; string input_57_pad_type_0 = const()[name = string("input_57_pad_type_0"), val = string("valid")]; tensor input_57_strides_0 = const()[name = string("input_57_strides_0"), val = tensor([1, 1])]; tensor input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_57_dilations_0 = const()[name = string("input_57_dilations_0"), val = tensor([1, 1])]; int32 input_57_groups_0 = const()[name = string("input_57_groups_0"), val = int32(1)]; tensor stage2_9_reparam_conv_bias_to_fp16 = const()[name = string("stage2_9_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1072640)))]; fp16 quantize_14_scale_1 = const()[name = string("quantize_14_scale_1"), val = fp16(0x1.318p-9)]; string quantize_14_output_dtype_1 = const()[name = string("quantize_14_output_dtype_1"), val = string("int8")]; tensor quantize_14 = quantize(input = input_55_cast_fp16, output_dtype = quantize_14_output_dtype_1, scale = quantize_14_scale_1)[name = string("quantize_14")]; fp16 dequantize_14_scale_1 = const()[name = string("dequantize_14_scale_1"), val = fp16(0x1.318p-9)]; tensor dequantize_14 = dequantize(input = quantize_14, scale = dequantize_14_scale_1)[name = string("dequantize_14")]; tensor input_57_cast_fp16 = conv(bias = stage2_9_reparam_conv_bias_to_fp16, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = stage2_9_reparam_conv_weight_cast_fp16, x = dequantize_14)[name = string("input_57_cast_fp16")]; tensor input_59_cast_fp16 = relu(x = input_57_cast_fp16)[name = string("input_59_cast_fp16")]; string input_61_pad_type_0 = const()[name = string("input_61_pad_type_0"), val = string("custom")]; tensor input_61_pad_0 = const()[name = string("input_61_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_61_groups_0 = const()[name = string("input_61_groups_0"), val = int32(128)]; tensor input_61_strides_0 = const()[name = string("input_61_strides_0"), val = tensor([1, 1])]; tensor input_61_dilations_0 = const()[name = string("input_61_dilations_0"), val = tensor([1, 1])]; tensor stage2_10_reparam_conv_bias_to_fp16 = const()[name = string("stage2_10_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1072960)))]; fp16 quantize_15_scale_1 = const()[name = string("quantize_15_scale_1"), val = fp16(0x1.278p-9)]; string quantize_15_output_dtype_1 = const()[name = string("quantize_15_output_dtype_1"), val = string("int8")]; tensor quantize_15 = quantize(input = input_59_cast_fp16, output_dtype = quantize_15_output_dtype_1, scale = quantize_15_scale_1)[name = string("quantize_15")]; fp16 dequantize_15_scale_1 = const()[name = string("dequantize_15_scale_1"), val = fp16(0x1.278p-9)]; tensor dequantize_15 = dequantize(input = quantize_15, scale = dequantize_15_scale_1)[name = string("dequantize_15")]; tensor input_61_cast_fp16 = conv(bias = stage2_10_reparam_conv_bias_to_fp16, dilations = input_61_dilations_0, groups = input_61_groups_0, pad = input_61_pad_0, pad_type = input_61_pad_type_0, strides = input_61_strides_0, weight = stage2_10_reparam_conv_weight_cast_fp16, x = dequantize_15)[name = string("input_61_cast_fp16")]; tensor input_63_cast_fp16 = relu(x = input_61_cast_fp16)[name = string("input_63_cast_fp16")]; string input_65_pad_type_0 = const()[name = string("input_65_pad_type_0"), val = string("valid")]; tensor input_65_strides_0 = const()[name = string("input_65_strides_0"), val = tensor([1, 1])]; tensor input_65_pad_0 = const()[name = string("input_65_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_65_dilations_0 = const()[name = string("input_65_dilations_0"), val = tensor([1, 1])]; int32 input_65_groups_0 = const()[name = string("input_65_groups_0"), val = int32(1)]; tensor stage2_11_reparam_conv_bias_to_fp16 = const()[name = string("stage2_11_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1073280)))]; fp16 quantize_16_scale_1 = const()[name = string("quantize_16_scale_1"), val = fp16(0x1.7e8p-9)]; string quantize_16_output_dtype_1 = const()[name = string("quantize_16_output_dtype_1"), val = string("int8")]; tensor quantize_16 = quantize(input = input_63_cast_fp16, output_dtype = quantize_16_output_dtype_1, scale = quantize_16_scale_1)[name = string("quantize_16")]; fp16 dequantize_16_scale_1 = const()[name = string("dequantize_16_scale_1"), val = fp16(0x1.7e8p-9)]; tensor dequantize_16 = dequantize(input = quantize_16, scale = dequantize_16_scale_1)[name = string("dequantize_16")]; tensor input_65_cast_fp16 = conv(bias = stage2_11_reparam_conv_bias_to_fp16, dilations = input_65_dilations_0, groups = input_65_groups_0, pad = input_65_pad_0, pad_type = input_65_pad_type_0, strides = input_65_strides_0, weight = stage2_11_reparam_conv_weight_cast_fp16, x = dequantize_16)[name = string("input_65_cast_fp16")]; tensor input_67_cast_fp16 = relu(x = input_65_cast_fp16)[name = string("input_67_cast_fp16")]; string input_69_pad_type_0 = const()[name = string("input_69_pad_type_0"), val = string("custom")]; tensor input_69_pad_0 = const()[name = string("input_69_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_69_groups_0 = const()[name = string("input_69_groups_0"), val = int32(128)]; tensor input_69_strides_0 = const()[name = string("input_69_strides_0"), val = tensor([1, 1])]; tensor input_69_dilations_0 = const()[name = string("input_69_dilations_0"), val = tensor([1, 1])]; tensor stage2_12_reparam_conv_bias_to_fp16 = const()[name = string("stage2_12_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1073600)))]; fp16 quantize_17_scale_1 = const()[name = string("quantize_17_scale_1"), val = fp16(0x1.0f8p-8)]; string quantize_17_output_dtype_1 = const()[name = string("quantize_17_output_dtype_1"), val = string("int8")]; tensor quantize_17 = quantize(input = input_67_cast_fp16, output_dtype = quantize_17_output_dtype_1, scale = quantize_17_scale_1)[name = string("quantize_17")]; fp16 dequantize_17_scale_1 = const()[name = string("dequantize_17_scale_1"), val = fp16(0x1.0f8p-8)]; tensor dequantize_17 = dequantize(input = quantize_17, scale = dequantize_17_scale_1)[name = string("dequantize_17")]; tensor input_69_cast_fp16 = conv(bias = stage2_12_reparam_conv_bias_to_fp16, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = stage2_12_reparam_conv_weight_cast_fp16, x = dequantize_17)[name = string("input_69_cast_fp16")]; tensor input_71_cast_fp16 = relu(x = input_69_cast_fp16)[name = string("input_71_cast_fp16")]; string input_73_pad_type_0 = const()[name = string("input_73_pad_type_0"), val = string("valid")]; tensor input_73_strides_0 = const()[name = string("input_73_strides_0"), val = tensor([1, 1])]; tensor input_73_pad_0 = const()[name = string("input_73_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_73_dilations_0 = const()[name = string("input_73_dilations_0"), val = tensor([1, 1])]; int32 input_73_groups_0 = const()[name = string("input_73_groups_0"), val = int32(1)]; tensor stage2_13_reparam_conv_bias_to_fp16 = const()[name = string("stage2_13_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1073920)))]; fp16 quantize_18_scale_1 = const()[name = string("quantize_18_scale_1"), val = fp16(0x1.4bcp-8)]; string quantize_18_output_dtype_1 = const()[name = string("quantize_18_output_dtype_1"), val = string("int8")]; tensor quantize_18 = quantize(input = input_71_cast_fp16, output_dtype = quantize_18_output_dtype_1, scale = quantize_18_scale_1)[name = string("quantize_18")]; fp16 dequantize_18_scale_1 = const()[name = string("dequantize_18_scale_1"), val = fp16(0x1.4bcp-8)]; tensor dequantize_18 = dequantize(input = quantize_18, scale = dequantize_18_scale_1)[name = string("dequantize_18")]; tensor input_73_cast_fp16 = conv(bias = stage2_13_reparam_conv_bias_to_fp16, dilations = input_73_dilations_0, groups = input_73_groups_0, pad = input_73_pad_0, pad_type = input_73_pad_type_0, strides = input_73_strides_0, weight = stage2_13_reparam_conv_weight_cast_fp16, x = dequantize_18)[name = string("input_73_cast_fp16")]; tensor input_75_cast_fp16 = relu(x = input_73_cast_fp16)[name = string("input_75_cast_fp16")]; string input_77_pad_type_0 = const()[name = string("input_77_pad_type_0"), val = string("custom")]; tensor input_77_pad_0 = const()[name = string("input_77_pad_0"), val = tensor([1, 1, 1, 1])]; int32 input_77_groups_0 = const()[name = string("input_77_groups_0"), val = int32(128)]; tensor input_77_strides_0 = const()[name = string("input_77_strides_0"), val = tensor([1, 1])]; tensor input_77_dilations_0 = const()[name = string("input_77_dilations_0"), val = tensor([1, 1])]; tensor stage2_14_reparam_conv_bias_to_fp16 = const()[name = string("stage2_14_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1074240)))]; fp16 quantize_19_scale_1 = const()[name = string("quantize_19_scale_1"), val = fp16(0x1.1cp-8)]; string quantize_19_output_dtype_1 = const()[name = string("quantize_19_output_dtype_1"), val = string("int8")]; tensor quantize_19 = quantize(input = input_75_cast_fp16, output_dtype = quantize_19_output_dtype_1, scale = quantize_19_scale_1)[name = string("quantize_19")]; fp16 dequantize_19_scale_1 = const()[name = string("dequantize_19_scale_1"), val = fp16(0x1.1cp-8)]; tensor dequantize_19 = dequantize(input = quantize_19, scale = dequantize_19_scale_1)[name = string("dequantize_19")]; tensor input_77_cast_fp16 = conv(bias = stage2_14_reparam_conv_bias_to_fp16, dilations = input_77_dilations_0, groups = input_77_groups_0, pad = input_77_pad_0, pad_type = input_77_pad_type_0, strides = input_77_strides_0, weight = stage2_14_reparam_conv_weight_cast_fp16, x = dequantize_19)[name = string("input_77_cast_fp16")]; tensor input_79_cast_fp16 = relu(x = input_77_cast_fp16)[name = string("input_79_cast_fp16")]; string input_81_pad_type_0 = const()[name = string("input_81_pad_type_0"), val = string("valid")]; tensor input_81_strides_0 = const()[name = string("input_81_strides_0"), val = tensor([1, 1])]; tensor input_81_pad_0 = const()[name = string("input_81_pad_0"), val = tensor([0, 0, 0, 0])]; tensor input_81_dilations_0 = const()[name = string("input_81_dilations_0"), val = tensor([1, 1])]; int32 input_81_groups_0 = const()[name = string("input_81_groups_0"), val = int32(1)]; tensor stage2_15_reparam_conv_bias_to_fp16 = const()[name = string("stage2_15_reparam_conv_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.weights_nonane"), offset = uint64(1074560)))]; fp16 quantize_20_scale_1 = const()[name = string("quantize_20_scale_1"), val = fp16(0x1.0bcp-7)]; string quantize_20_output_dtype_1 = const()[name = string("quantize_20_output_dtype_1"), val = string("int8")]; tensor quantize_20 = quantize(input = input_79_cast_fp16, output_dtype = quantize_20_output_dtype_1, scale = quantize_20_scale_1)[name = string("quantize_20")]; fp16 dequantize_20_scale_1 = const()[name = string("dequantize_20_scale_1"), val = fp16(0x1.0bcp-7)]; tensor dequantize_20 = dequantize(input = quantize_20, scale = dequantize_20_scale_1)[name = string("dequantize_20")]; tensor input_81_cast_fp16 = conv(bias = stage2_15_reparam_conv_bias_to_fp16, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = stage2_15_reparam_conv_weight_cast_fp16, x = dequantize_20)[name = string("input_81_cast_fp16")]; tensor input_83_cast_fp16 = relu(x = input_81_cast_fp16)[name = string("input_83_cast_fp16")]; string input_85_pad_type_0 = const()[name = string("input_85_pad_type_0"), val = string("custom")]; tensor input_85_pad_0 = const()[name = string("input_85_pad_0"), val = tensor([1, 1, 1, 1])]; tensor input_85_strides_0 = const()[name = string("input_85_strides_0"), val = tensor([2, 2])]; int32 input_85_groups_0 = const()[name = string("input_85_groups_0"), val = int32(128)]; tensor