| program(1.3) | |
| [buildInfo = dict<string, string>({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3405.2.1"}})] | |
| { | |
| func main<ios18>(tensor<fp16, [1, 1024, 1, ?]> x) [FlexibleShapeInformation = tuple<tuple<string, dict<string, tensor<int32, [?]>>>, tuple<string, dict<string, dict<string, tensor<int32, [?]>>>>>((("DefaultShapes", {{"x", [1, 1024, 1, 32]}}), ("EnumeratedShapes", {{"2a8dd4d2", {{"x", [1, 1024, 1, 64]}}}, {"3bf9b6d7", {{"x", [1, 1024, 1, 128]}}}, {"44109b23", {{"x", [1, 1024, 1, 1]}}}, {"759fca31", {{"x", [1, 1024, 1, 8]}}}, {"d30434c5", {{"x", [1, 1024, 1, 16]}}}, {"e483fcaa", {{"x", [1, 1024, 1, 4]}}}, {"fabb4dad", {{"x", [1, 1024, 1, 32]}}}})))] { | |
| string hidden_3_pad_type_0 = const()[name = string("hidden_3_pad_type_0"), val = string("valid")]; | |
| tensor<int32, [2]> hidden_3_strides_0 = const()[name = string("hidden_3_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [4]> hidden_3_pad_0 = const()[name = string("hidden_3_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [2]> hidden_3_dilations_0 = const()[name = string("hidden_3_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| int32 hidden_3_groups_0 = const()[name = string("hidden_3_groups_0"), val = int32(1)]; | |
| tensor<fp16, [256, 1024, 1, 1]> var_8_to_fp16 = const()[name = string("op_8_to_fp16"), val = tensor<fp16, [256, 1024, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))]; | |
| tensor<fp16, [256]> in_proj_bias_to_fp16 = const()[name = string("in_proj_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(524416)))]; | |
| tensor<fp16, [1, 256, 1, ?]> hidden_3_cast_fp16 = conv(bias = in_proj_bias_to_fp16, dilations = hidden_3_dilations_0, groups = hidden_3_groups_0, pad = hidden_3_pad_0, pad_type = hidden_3_pad_type_0, strides = hidden_3_strides_0, weight = var_8_to_fp16, x = x)[name = string("hidden_3_cast_fp16")]; | |
| tensor<fp16, [1, 256, 1, ?]> hidden_cast_fp16 = tanh(x = hidden_3_cast_fp16)[name = string("hidden_cast_fp16")]; | |
| fp16 var_16_promoted_to_fp16 = const()[name = string("op_16_promoted_to_fp16"), val = fp16(0x1.2p+3)]; | |
| tensor<fp16, [1, 256, 1, ?]> var_17_cast_fp16 = mul(x = hidden_cast_fp16, y = var_16_promoted_to_fp16)[name = string("op_17_cast_fp16")]; | |
| tensor<fp16, [1, 256, 1, ?]> var_18_cast_fp16 = round(x = var_17_cast_fp16)[name = string("op_18_cast_fp16")]; | |
| fp16 _inversed_x_y_0_to_fp16 = const()[name = string("_inversed_x_y_0_to_fp16"), val = fp16(0x1.c7p-4)]; | |
| tensor<fp16, [1, 256, 1, ?]> _inversed_x_cast_fp16 = mul(x = var_18_cast_fp16, y = _inversed_x_y_0_to_fp16)[name = string("_inversed_x_cast_fp16")]; | |
| string var_31_pad_type_0 = const()[name = string("op_31_pad_type_0"), val = string("valid")]; | |
| tensor<int32, [2]> var_31_strides_0 = const()[name = string("op_31_strides_0"), val = tensor<int32, [2]>([1, 1])]; | |
| tensor<int32, [4]> var_31_pad_0 = const()[name = string("op_31_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])]; | |
| tensor<int32, [2]> var_31_dilations_0 = const()[name = string("op_31_dilations_0"), val = tensor<int32, [2]>([1, 1])]; | |
| int32 var_31_groups_0 = const()[name = string("op_31_groups_0"), val = int32(1)]; | |
| tensor<fp16, [1024, 256, 1, 1]> var_25_to_fp16 = const()[name = string("op_25_to_fp16"), val = tensor<fp16, [1024, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(524992)))]; | |
| tensor<fp16, [1024]> out_proj_bias_to_fp16 = const()[name = string("out_proj_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1049344)))]; | |
| tensor<fp16, [1, 1024, 1, ?]> output = conv(bias = out_proj_bias_to_fp16, dilations = var_31_dilations_0, groups = var_31_groups_0, pad = var_31_pad_0, pad_type = var_31_pad_type_0, strides = var_31_strides_0, weight = var_25_to_fp16, x = _inversed_x_cast_fp16)[name = string("op_31_cast_fp16")]; | |
| } -> (output); | |
| } |