program(1.3) [buildInfo = dict({{"coremlc-component-MIL", "3405.2.1"}, {"coremlc-version", "3405.2.1"}})] { func main(tensor x) [FlexibleShapeInformation = tuple>>, tuple>>>>((("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 hidden_3_strides_0 = const()[name = string("hidden_3_strides_0"), val = tensor([1, 1])]; tensor hidden_3_pad_0 = const()[name = string("hidden_3_pad_0"), val = tensor([0, 0, 0, 0])]; tensor hidden_3_dilations_0 = const()[name = string("hidden_3_dilations_0"), val = tensor([1, 1])]; int32 hidden_3_groups_0 = const()[name = string("hidden_3_groups_0"), val = int32(1)]; tensor var_8_to_fp16 = const()[name = string("op_8_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))]; tensor in_proj_bias_to_fp16 = const()[name = string("in_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(524416)))]; tensor 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 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 var_17_cast_fp16 = mul(x = hidden_cast_fp16, y = var_16_promoted_to_fp16)[name = string("op_17_cast_fp16")]; tensor 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 _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 var_31_strides_0 = const()[name = string("op_31_strides_0"), val = tensor([1, 1])]; tensor var_31_pad_0 = const()[name = string("op_31_pad_0"), val = tensor([0, 0, 0, 0])]; tensor var_31_dilations_0 = const()[name = string("op_31_dilations_0"), val = tensor([1, 1])]; int32 var_31_groups_0 = const()[name = string("op_31_groups_0"), val = int32(1)]; tensor var_25_to_fp16 = const()[name = string("op_25_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(524992)))]; tensor out_proj_bias_to_fp16 = const()[name = string("out_proj_bias_to_fp16"), val = tensor(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1049344)))]; tensor 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); }