program(1.3) [buildInfo = dict, tensor>({{"coremlc-component-MIL", "5.33.5"}, {"coremlc-version", "1877.40.1.0.5"}, {"coremltools-component-milinternal", ""}, {"coremltools-version", "7.2"}}), mldb_token = string("mldb-4blgxjqype")] { func main(pixel_buffer face0, pixel_buffer face1, pixel_buffer face2, pixel_buffer face3, pixel_buffer face4, pixel_buffer face5, pixel_buffer face6, pixel_buffer face7, pixel_buffer face8, pixel_buffer face9) { tensor face0_bgra_uint8 = pixel_buffer_to_tensor(input = face0); tensor face1_bgra_uint8 = pixel_buffer_to_tensor(input = face1); tensor face2_bgra_uint8 = pixel_buffer_to_tensor(input = face2); tensor face3_bgra_uint8 = pixel_buffer_to_tensor(input = face3); tensor face4_bgra_uint8 = pixel_buffer_to_tensor(input = face4); tensor face5_bgra_uint8 = pixel_buffer_to_tensor(input = face5); tensor face6_bgra_uint8 = pixel_buffer_to_tensor(input = face6); tensor face7_bgra_uint8 = pixel_buffer_to_tensor(input = face7); tensor face8_bgra_uint8 = pixel_buffer_to_tensor(input = face8); tensor face9_bgra_uint8 = pixel_buffer_to_tensor(input = face9); tensor face0_bgra_fp16 = cast(dtype = string("fp16"), x = face0_bgra_uint8); tensor face1_bgra_fp16 = cast(dtype = string("fp16"), x = face1_bgra_uint8); tensor face2_bgra_fp16 = cast(dtype = string("fp16"), x = face2_bgra_uint8); tensor face3_bgra_fp16 = cast(dtype = string("fp16"), x = face3_bgra_uint8); tensor face4_bgra_fp16 = cast(dtype = string("fp16"), x = face4_bgra_uint8); tensor face5_bgra_fp16 = cast(dtype = string("fp16"), x = face5_bgra_uint8); tensor face6_bgra_fp16 = cast(dtype = string("fp16"), x = face6_bgra_uint8); tensor face7_bgra_fp16 = cast(dtype = string("fp16"), x = face7_bgra_uint8); tensor face8_bgra_fp16 = cast(dtype = string("fp16"), x = face8_bgra_uint8); tensor face9_bgra_fp16 = cast(dtype = string("fp16"), x = face9_bgra_uint8); tensor batch_faces_bgra = stack(axis = int32(0), values = (face0_bgra_fp16, face1_bgra_fp16, face2_bgra_fp16, face3_bgra_fp16, face4_bgra_fp16, face5_bgra_fp16, face6_bgra_fp16, face7_bgra_fp16, face8_bgra_fp16, face9_bgra_fp16)); tensor batch_faces_b = slice_by_index(begin = tensor([0, 0, 0, 0]), end = tensor([0, 1, 0, 0]), end_mask = tensor([true, false, true, true]), x = batch_faces_bgra); tensor batch_faces_g = slice_by_index(begin = tensor([0, 1, 0, 0]), end = tensor([0, 2, 0, 0]), end_mask = tensor([true, false, true, true]), x = batch_faces_bgra); tensor batch_faces_r = slice_by_index(begin = tensor([0, 2, 0, 0]), end = tensor([0, 3, 0, 0]), end_mask = tensor([true, false, true, true]), x = batch_faces_bgra); tensor batch_face_rgb = concat(axis = int32(1), interleave = bool(false), values = (batch_faces_r, batch_faces_g, batch_faces_b)); tensor rgb2gray_convolutionx_pad_type_0 = const()[name = tensor("rgb2gray_convolutionx_pad_type_0"), val = tensor("same")]; tensor rgb2gray_convolutionx_strides_0 = const()[name = tensor("rgb2gray_convolutionx_strides_0"), val = tensor([1, 1])]; tensor rgb2gray_convolutionx_dilations_0 = const()[name = tensor("rgb2gray_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor rgb2gray_convolutionx_groups_0 = const()[name = tensor("rgb2gray_convolutionx_groups_0"), val = tensor(1)]; tensor rgb2gray_convolutionx_pad_0 = const()[name = tensor("rgb2gray_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor transpose_0_to_fp16 = const()[name = tensor("transpose_0_to_fp16"), val = tensor([[[[0x1.afcp-4]], [[-0x1.974p-1]], [[-0x1.c84p+0]]]])]; tensor rgb2gray_convolutionx_cast_fp16 = conv(dilations = rgb2gray_convolutionx_dilations_0, groups = rgb2gray_convolutionx_groups_0, pad = rgb2gray_convolutionx_pad_0, pad_type = rgb2gray_convolutionx_pad_type_0, strides = rgb2gray_convolutionx_strides_0, weight = transpose_0_to_fp16, x = batch_face_rgb)[name = tensor("rgb2gray_convolutionx_cast_fp16")]; tensor im_prep_convolutionx_pad_type_0 = const()[name = tensor("im_prep_convolutionx_pad_type_0"), val = tensor("same")]; tensor im_prep_convolutionx_strides_0 = const()[name = tensor("im_prep_convolutionx_strides_0"), val = tensor([1, 1])]; tensor im_prep_convolutionx_dilations_0 = const()[name = tensor("im_prep_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor im_prep_convolutionx_groups_0 = const()[name = tensor("im_prep_convolutionx_groups_0"), val = tensor(1)]; tensor im_prep_convolutionx_pad_0 = const()[name = tensor("im_prep_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor transpose_2_to_fp16 = const()[name = tensor("transpose_2_to_fp16"), val = tensor([[[[0x1.01p-7]]]])]; tensor const_71_to_fp16 = const()[name = tensor("const_71_to_fp16"), val = tensor([-0x1p+0])]; tensor im_prep_BiasAdd_cast_fp16 = conv(bias = const_71_to_fp16, dilations = im_prep_convolutionx_dilations_0, groups = im_prep_convolutionx_groups_0, pad = im_prep_convolutionx_pad_0, pad_type = im_prep_convolutionx_pad_type_0, strides = im_prep_convolutionx_strides_0, weight = transpose_2_to_fp16, x = rgb2gray_convolutionx_cast_fp16)[name = tensor("im_prep_BiasAdd_cast_fp16")]; tensor xcep_conv1_0_convolutionx_pad_type_0 = const()[name = tensor("xcep_conv1_0_convolutionx_pad_type_0"), val = tensor("same")]; tensor xcep_conv1_0_convolutionx_strides_0 = const()[name = tensor("xcep_conv1_0_convolutionx_strides_0"), val = tensor([2, 2])]; tensor xcep_conv1_0_convolutionx_dilations_0 = const()[name = tensor("xcep_conv1_0_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor xcep_conv1_0_convolutionx_groups_0 = const()[name = tensor("xcep_conv1_0_convolutionx_groups_0"), val = tensor(1)]; tensor xcep_conv1_0_convolutionx_pad_0 = const()[name = tensor("xcep_conv1_0_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor xcep_conv1_bn_0_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("xcep_conv1_bn_0_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(64)))]; tensor const_72_to_fp16 = const()[name = tensor("const_72_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(704)))]; tensor xcep_conv1_bn_0_batchnorm_1_add_1_cast_fp16 = conv(bias = const_72_to_fp16, dilations = xcep_conv1_0_convolutionx_dilations_0, groups = xcep_conv1_0_convolutionx_groups_0, pad = xcep_conv1_0_convolutionx_pad_0, pad_type = xcep_conv1_0_convolutionx_pad_type_0, strides = xcep_conv1_0_convolutionx_strides_0, weight = xcep_conv1_bn_0_batchnorm_1_mul_1_weight_0_to_fp16, x = im_prep_BiasAdd_cast_fp16)[name = tensor("xcep_conv1_bn_0_batchnorm_1_add_1_cast_fp16")]; tensor xcep_conv1_act_0_Relu_cast_fp16 = relu(x = xcep_conv1_bn_0_batchnorm_1_add_1_cast_fp16)[name = tensor("xcep_conv1_act_0_Relu_cast_fp16")]; tensor xcep_conv1_act_0_Const_to_fp16 = const()[name = tensor("xcep_conv1_act_0_Const_to_fp16"), val = tensor(0x1.8p+2)]; tensor xcep_conv1_act_0_clip_by_value_Minimum_cast_fp16 = minimum(x = xcep_conv1_act_0_Relu_cast_fp16, y = xcep_conv1_act_0_Const_to_fp16)[name = tensor("xcep_conv1_act_0_clip_by_value_Minimum_cast_fp16")]; tensor xcep_conv1_act_0_Const_1_to_fp16 = const()[name = tensor("xcep_conv1_act_0_Const_1_to_fp16"), val = tensor(0x0p+0)]; tensor xcep_conv1_act_0_clip_by_value_cast_fp16 = maximum(x = xcep_conv1_act_0_clip_by_value_Minimum_cast_fp16, y = xcep_conv1_act_0_Const_1_to_fp16)[name = tensor("xcep_conv1_act_0_clip_by_value_cast_fp16")]; tensor xcep_conv2_0_convolutionx_pad_type_0 = const()[name = tensor("xcep_conv2_0_convolutionx_pad_type_0"), val = tensor("same")]; tensor xcep_conv2_0_convolutionx_strides_0 = const()[name = tensor("xcep_conv2_0_convolutionx_strides_0"), val = tensor([2, 2])]; tensor xcep_conv2_0_convolutionx_dilations_0 = const()[name = tensor("xcep_conv2_0_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor xcep_conv2_0_convolutionx_groups_0 = const()[name = tensor("xcep_conv2_0_convolutionx_groups_0"), val = tensor(1)]; tensor xcep_conv2_0_convolutionx_pad_0 = const()[name = tensor("xcep_conv2_0_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor xcep_conv2_bn_0_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("xcep_conv2_bn_0_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(832)))]; tensor const_73_to_fp16 = const()[name = tensor("const_73_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(37760)))]; tensor xcep_conv2_bn_0_batchnorm_1_add_1_cast_fp16 = conv(bias = const_73_to_fp16, dilations = xcep_conv2_0_convolutionx_dilations_0, groups = xcep_conv2_0_convolutionx_groups_0, pad = xcep_conv2_0_convolutionx_pad_0, pad_type = xcep_conv2_0_convolutionx_pad_type_0, strides = xcep_conv2_0_convolutionx_strides_0, weight = xcep_conv2_bn_0_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv1_act_0_clip_by_value_cast_fp16)[name = tensor("xcep_conv2_bn_0_batchnorm_1_add_1_cast_fp16")]; tensor xcep_conv2_act_0_Relu_cast_fp16 = relu(x = xcep_conv2_bn_0_batchnorm_1_add_1_cast_fp16)[name = tensor("xcep_conv2_act_0_Relu_cast_fp16")]; tensor xcep_conv2_act_0_Const_to_fp16 = const()[name = tensor("xcep_conv2_act_0_Const_to_fp16"), val = tensor(0x1.8p+2)]; tensor xcep_conv2_act_0_clip_by_value_Minimum_cast_fp16 = minimum(x = xcep_conv2_act_0_Relu_cast_fp16, y = xcep_conv2_act_0_Const_to_fp16)[name = tensor("xcep_conv2_act_0_clip_by_value_Minimum_cast_fp16")]; tensor xcep_conv2_act_0_Const_1_to_fp16 = const()[name = tensor("xcep_conv2_act_0_Const_1_to_fp16"), val = tensor(0x0p+0)]; tensor xcep_conv2_act_0_clip_by_value_cast_fp16 = maximum(x = xcep_conv2_act_0_clip_by_value_Minimum_cast_fp16, y = xcep_conv2_act_0_Const_1_to_fp16)[name = tensor("xcep_conv2_act_0_clip_by_value_cast_fp16")]; tensor xcep_conv3_0_convolutionx_pad_type_0 = const()[name = tensor("xcep_conv3_0_convolutionx_pad_type_0"), val = tensor("same")]; tensor xcep_conv3_0_convolutionx_strides_0 = const()[name = tensor("xcep_conv3_0_convolutionx_strides_0"), val = tensor([1, 1])]; tensor xcep_conv3_0_convolutionx_dilations_0 = const()[name = tensor("xcep_conv3_0_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor xcep_conv3_0_convolutionx_groups_0 = const()[name = tensor("xcep_conv3_0_convolutionx_groups_0"), val = tensor(1)]; tensor xcep_conv3_0_convolutionx_pad_0 = const()[name = tensor("xcep_conv3_0_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor xcep_conv3_bn_0_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("xcep_conv3_bn_0_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(37952)))]; tensor const_74_to_fp16 = const()[name = tensor("const_74_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(185472)))]; tensor xcep_conv3_bn_0_batchnorm_1_add_1_cast_fp16 = conv(bias = const_74_to_fp16, dilations = xcep_conv3_0_convolutionx_dilations_0, groups = xcep_conv3_0_convolutionx_groups_0, pad = xcep_conv3_0_convolutionx_pad_0, pad_type = xcep_conv3_0_convolutionx_pad_type_0, strides = xcep_conv3_0_convolutionx_strides_0, weight = xcep_conv3_bn_0_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv2_act_0_clip_by_value_cast_fp16)[name = tensor("xcep_conv3_bn_0_batchnorm_1_add_1_cast_fp16")]; tensor xcep_conv3_act_0_Relu_cast_fp16 = relu(x = xcep_conv3_bn_0_batchnorm_1_add_1_cast_fp16)[name = tensor("xcep_conv3_act_0_Relu_cast_fp16")]; tensor xcep_conv3_act_0_Const_to_fp16 = const()[name = tensor("xcep_conv3_act_0_Const_to_fp16"), val = tensor(0x1.8p+2)]; tensor xcep_conv3_act_0_clip_by_value_Minimum_cast_fp16 = minimum(x = xcep_conv3_act_0_Relu_cast_fp16, y = xcep_conv3_act_0_Const_to_fp16)[name = tensor("xcep_conv3_act_0_clip_by_value_Minimum_cast_fp16")]; tensor xcep_conv3_act_0_Const_1_to_fp16 = const()[name = tensor("xcep_conv3_act_0_Const_1_to_fp16"), val = tensor(0x0p+0)]; tensor xcep_conv3_act_0_clip_by_value_cast_fp16 = maximum(x = xcep_conv3_act_0_clip_by_value_Minimum_cast_fp16, y = xcep_conv3_act_0_Const_1_to_fp16)[name = tensor("xcep_conv3_act_0_clip_by_value_cast_fp16")]; tensor xcep_conv4_0_convolutionx_pad_type_0 = const()[name = tensor("xcep_conv4_0_convolutionx_pad_type_0"), val = tensor("same")]; tensor xcep_conv4_0_convolutionx_strides_0 = const()[name = tensor("xcep_conv4_0_convolutionx_strides_0"), val = tensor([2, 2])]; tensor xcep_conv4_0_convolutionx_dilations_0 = const()[name = tensor("xcep_conv4_0_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor xcep_conv4_0_convolutionx_groups_0 = const()[name = tensor("xcep_conv4_0_convolutionx_groups_0"), val = tensor(1)]; tensor xcep_conv4_0_convolutionx_pad_0 = const()[name = tensor("xcep_conv4_0_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor xcep_conv4_bn_0_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("xcep_conv4_bn_0_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(185792)))]; tensor const_75_to_fp16 = const()[name = tensor("const_75_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(480768)))]; tensor xcep_conv4_bn_0_batchnorm_1_add_1_cast_fp16 = conv(bias = const_75_to_fp16, dilations = xcep_conv4_0_convolutionx_dilations_0, groups = xcep_conv4_0_convolutionx_groups_0, pad = xcep_conv4_0_convolutionx_pad_0, pad_type = xcep_conv4_0_convolutionx_pad_type_0, strides = xcep_conv4_0_convolutionx_strides_0, weight = xcep_conv4_bn_0_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv3_act_0_clip_by_value_cast_fp16)[name = tensor("xcep_conv4_bn_0_batchnorm_1_add_1_cast_fp16")]; tensor xcep_conv4_act_0_Relu_cast_fp16 = relu(x = xcep_conv4_bn_0_batchnorm_1_add_1_cast_fp16)[name = tensor("xcep_conv4_act_0_Relu_cast_fp16")]; tensor xcep_conv4_act_0_Const_to_fp16 = const()[name = tensor("xcep_conv4_act_0_Const_to_fp16"), val = tensor(0x1.8p+2)]; tensor xcep_conv4_act_0_clip_by_value_Minimum_cast_fp16 = minimum(x = xcep_conv4_act_0_Relu_cast_fp16, y = xcep_conv4_act_0_Const_to_fp16)[name = tensor("xcep_conv4_act_0_clip_by_value_Minimum_cast_fp16")]; tensor xcep_conv4_act_0_Const_1_to_fp16 = const()[name = tensor("xcep_conv4_act_0_Const_1_to_fp16"), val = tensor(0x0p+0)]; tensor xcep_conv4_act_0_clip_by_value_cast_fp16 = maximum(x = xcep_conv4_act_0_clip_by_value_Minimum_cast_fp16, y = xcep_conv4_act_0_Const_1_to_fp16)[name = tensor("xcep_conv4_act_0_clip_by_value_cast_fp16")]; tensor xcep_conv5_0_convolutionx_pad_type_0 = const()[name = tensor("xcep_conv5_0_convolutionx_pad_type_0"), val = tensor("same")]; tensor xcep_conv5_0_convolutionx_strides_0 = const()[name = tensor("xcep_conv5_0_convolutionx_strides_0"), val = tensor([1, 1])]; tensor xcep_conv5_0_convolutionx_dilations_0 = const()[name = tensor("xcep_conv5_0_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor xcep_conv5_0_convolutionx_groups_0 = const()[name = tensor("xcep_conv5_0_convolutionx_groups_0"), val = tensor(1)]; tensor xcep_conv5_0_convolutionx_pad_0 = const()[name = tensor("xcep_conv5_0_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor xcep_conv5_bn_0_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("xcep_conv5_bn_0_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(481088)))]; tensor const_76_to_fp16 = const()[name = tensor("const_76_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(776064)))]; tensor xcep_conv5_bn_0_batchnorm_1_add_1_cast_fp16 = conv(bias = const_76_to_fp16, dilations = xcep_conv5_0_convolutionx_dilations_0, groups = xcep_conv5_0_convolutionx_groups_0, pad = xcep_conv5_0_convolutionx_pad_0, pad_type = xcep_conv5_0_convolutionx_pad_type_0, strides = xcep_conv5_0_convolutionx_strides_0, weight = xcep_conv5_bn_0_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv4_act_0_clip_by_value_cast_fp16)[name = tensor("xcep_conv5_bn_0_batchnorm_1_add_1_cast_fp16")]; tensor xcep_conv5_act_0_Relu_cast_fp16 = relu(x = xcep_conv5_bn_0_batchnorm_1_add_1_cast_fp16)[name = tensor("xcep_conv5_act_0_Relu_cast_fp16")]; tensor xcep_conv5_act_0_Const_to_fp16 = const()[name = tensor("xcep_conv5_act_0_Const_to_fp16"), val = tensor(0x1.8p+2)]; tensor xcep_conv5_act_0_clip_by_value_Minimum_cast_fp16 = minimum(x = xcep_conv5_act_0_Relu_cast_fp16, y = xcep_conv5_act_0_Const_to_fp16)[name = tensor("xcep_conv5_act_0_clip_by_value_Minimum_cast_fp16")]; tensor xcep_conv5_act_0_Const_1_to_fp16 = const()[name = tensor("xcep_conv5_act_0_Const_1_to_fp16"), val = tensor(0x0p+0)]; tensor xcep_conv5_act_0_clip_by_value_cast_fp16 = maximum(x = xcep_conv5_act_0_clip_by_value_Minimum_cast_fp16, y = xcep_conv5_act_0_Const_1_to_fp16)[name = tensor("xcep_conv5_act_0_clip_by_value_cast_fp16")]; tensor conv_7_sm_convolutionx_pad_type_0 = const()[name = tensor("conv_7_sm_convolutionx_pad_type_0"), val = tensor("same")]; tensor conv_7_sm_convolutionx_strides_0 = const()[name = tensor("conv_7_sm_convolutionx_strides_0"), val = tensor([1, 1])]; tensor conv_7_sm_convolutionx_dilations_0 = const()[name = tensor("conv_7_sm_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor conv_7_sm_convolutionx_groups_0 = const()[name = tensor("conv_7_sm_convolutionx_groups_0"), val = tensor(1)]; tensor conv_7_sm_convolutionx_pad_0 = const()[name = tensor("conv_7_sm_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor conv_pw_7_bn_sm_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("conv_pw_7_bn_sm_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(776384)))]; tensor const_77_to_fp16 = const()[name = tensor("const_77_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(850176)))]; tensor conv_pw_7_bn_sm_batchnorm_1_add_1_cast_fp16 = conv(bias = const_77_to_fp16, dilations = conv_7_sm_convolutionx_dilations_0, groups = conv_7_sm_convolutionx_groups_0, pad = conv_7_sm_convolutionx_pad_0, pad_type = conv_7_sm_convolutionx_pad_type_0, strides = conv_7_sm_convolutionx_strides_0, weight = conv_pw_7_bn_sm_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv5_act_0_clip_by_value_cast_fp16)[name = tensor("conv_pw_7_bn_sm_batchnorm_1_add_1_cast_fp16")]; tensor conv_7_lb_convolutionx_pad_type_0 = const()[name = tensor("conv_7_lb_convolutionx_pad_type_0"), val = tensor("same")]; tensor conv_7_lb_convolutionx_strides_0 = const()[name = tensor("conv_7_lb_convolutionx_strides_0"), val = tensor([1, 1])]; tensor conv_7_lb_convolutionx_dilations_0 = const()[name = tensor("conv_7_lb_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor conv_7_lb_convolutionx_groups_0 = const()[name = tensor("conv_7_lb_convolutionx_groups_0"), val = tensor(1)]; tensor conv_7_lb_convolutionx_pad_0 = const()[name = tensor("conv_7_lb_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor conv_pw_7_bn_lb_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("conv_pw_7_bn_lb_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(850304)))]; tensor const_78_to_fp16 = const()[name = tensor("const_78_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(924096)))]; tensor conv_pw_7_bn_lb_batchnorm_1_add_1_cast_fp16 = conv(bias = const_78_to_fp16, dilations = conv_7_lb_convolutionx_dilations_0, groups = conv_7_lb_convolutionx_groups_0, pad = conv_7_lb_convolutionx_pad_0, pad_type = conv_7_lb_convolutionx_pad_type_0, strides = conv_7_lb_convolutionx_strides_0, weight = conv_pw_7_bn_lb_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv5_act_0_clip_by_value_cast_fp16)[name = tensor("conv_pw_7_bn_lb_batchnorm_1_add_1_cast_fp16")]; tensor conv_7_rb_convolutionx_pad_type_0 = const()[name = tensor("conv_7_rb_convolutionx_pad_type_0"), val = tensor("same")]; tensor conv_7_rb_convolutionx_strides_0 = const()[name = tensor("conv_7_rb_convolutionx_strides_0"), val = tensor([1, 1])]; tensor conv_7_rb_convolutionx_dilations_0 = const()[name = tensor("conv_7_rb_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor conv_7_rb_convolutionx_groups_0 = const()[name = tensor("conv_7_rb_convolutionx_groups_0"), val = tensor(1)]; tensor conv_7_rb_convolutionx_pad_0 = const()[name = tensor("conv_7_rb_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor conv_pw_7_bn_rb_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("conv_pw_7_bn_rb_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(924224)))]; tensor const_79_to_fp16 = const()[name = tensor("const_79_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(998016)))]; tensor conv_pw_7_bn_rb_batchnorm_1_add_1_cast_fp16 = conv(bias = const_79_to_fp16, dilations = conv_7_rb_convolutionx_dilations_0, groups = conv_7_rb_convolutionx_groups_0, pad = conv_7_rb_convolutionx_pad_0, pad_type = conv_7_rb_convolutionx_pad_type_0, strides = conv_7_rb_convolutionx_strides_0, weight = conv_pw_7_bn_rb_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv5_act_0_clip_by_value_cast_fp16)[name = tensor("conv_pw_7_bn_rb_batchnorm_1_add_1_cast_fp16")]; tensor conv_7_pose_convolutionx_pad_type_0 = const()[name = tensor("conv_7_pose_convolutionx_pad_type_0"), val = tensor("same")]; tensor conv_7_pose_convolutionx_strides_0 = const()[name = tensor("conv_7_pose_convolutionx_strides_0"), val = tensor([1, 1])]; tensor conv_7_pose_convolutionx_dilations_0 = const()[name = tensor("conv_7_pose_convolutionx_dilations_0"), val = tensor([1, 1])]; tensor conv_7_pose_convolutionx_groups_0 = const()[name = tensor("conv_7_pose_convolutionx_groups_0"), val = tensor(1)]; tensor conv_7_pose_convolutionx_pad_0 = const()[name = tensor("conv_7_pose_convolutionx_pad_0"), val = tensor([0, 0, 0, 0])]; tensor conv_pw_7_bn_pose_batchnorm_1_mul_1_weight_0_to_fp16 = const()[name = tensor("conv_pw_7_bn_pose_batchnorm_1_mul_1_weight_0_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(998144)))]; tensor const_80_to_fp16 = const()[name = tensor("const_80_to_fp16"), val = tensor(BLOBFILE(path = tensor("@model_path/weights/model.bin"), offset = tensor(1071936)))]; tensor conv_pw_7_bn_pose_batchnorm_1_add_1_cast_fp16 = conv(bias = const_80_to_fp16, dilations = conv_7_pose_convolutionx_dilations_0, groups = conv_7_pose_convolutionx_groups_0, pad = conv_7_pose_convolutionx_pad_0, pad_type = conv_7_pose_convolutionx_pad_type_0, strides = conv_7_pose_convolutionx_strides_0, weight = conv_pw_7_bn_pose_batchnorm_1_mul_1_weight_0_to_fp16, x = xcep_conv5_act_0_clip_by_value_cast_fp16)[name = tensor("conv_pw_7_bn_pose_batchnorm_1_add_1_cast_fp16")]; tensor conv_7_eye_convolutionx_pad_type_0 = const()[name = tensor("conv_7_eye_convolutionx_pad_type_0"), val = tensor("same")]; tensor conv_7_eye_convolutionx_strides_0 = const()[name = tensor("conv_7_eye_convolutionx_strides_0"), val = tensor([1, 1])]; tensor conv_7_eye_convolutionx_dilations_0 = const()[name = tensor