program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.7.1"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.3.2"}, {"mldb_token", "mldb-rva93zja72"}})]
{
    func main<ios15>(tensor<fp32, [?, 512]> input) [FlexibleShapeInformation = tuple<tuple<tensor<string, []>, dict<tensor<string, []>, tensor<int32, [?]>>>, tuple<tensor<string, []>, dict<tensor<string, []>, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"input", [1, 512]}}), ("RangeDims", {{"input", [[1, 64], [512, 512]]}})))] {
            tensor<string, []> input_to_fp16_dtype_0 = const()[name = tensor<string, []>("input_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [128, 512]> model_encoder_0_weight_to_fp16 = const()[name = tensor<string, []>("model_encoder_0_weight_to_fp16"), val = tensor<fp16, [128, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [128]> model_encoder_0_bias_to_fp16 = const()[name = tensor<string, []>("model_encoder_0_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131200)))];
            tensor<fp16, [?, 512]> input_to_fp16 = cast(dtype = input_to_fp16_dtype_0, x = input)[name = tensor<string, []>("cast_1")];
            tensor<fp16, [?, 128]> linear_0_cast_fp16 = linear(bias = model_encoder_0_bias_to_fp16, weight = model_encoder_0_weight_to_fp16, x = input_to_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<fp16, [?, 128]> input_9_cast_fp16 = relu(x = linear_0_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<fp16, [128, 128]> model_encoder_3_weight_to_fp16 = const()[name = tensor<string, []>("model_encoder_3_weight_to_fp16"), val = tensor<fp16, [128, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(131520)))];
            tensor<fp16, [128]> model_encoder_3_bias_to_fp16 = const()[name = tensor<string, []>("model_encoder_3_bias_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164352)))];
            tensor<fp16, [?, 128]> linear_1_cast_fp16 = linear(bias = model_encoder_3_bias_to_fp16, weight = model_encoder_3_weight_to_fp16, x = input_9_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
            tensor<fp16, [?, 128]> input_21_cast_fp16 = relu(x = linear_1_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<fp16, [64, 128]> model_encoder_6_weight_to_fp16 = const()[name = tensor<string, []>("model_encoder_6_weight_to_fp16"), val = tensor<fp16, [64, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164672)))];
            tensor<fp16, [64]> model_encoder_6_bias_to_fp16 = const()[name = tensor<string, []>("model_encoder_6_bias_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181120)))];
            tensor<fp16, [?, 64]> linear_2_cast_fp16 = linear(bias = model_encoder_6_bias_to_fp16, weight = model_encoder_6_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
            tensor<fp16, [5, 64]> classification_head_weight_to_fp16 = const()[name = tensor<string, []>("classification_head_weight_to_fp16"), val = tensor<fp16, [5, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181312)))];
            tensor<fp16, [5]> classification_head_bias_to_fp16 = const()[name = tensor<string, []>("classification_head_bias_to_fp16"), val = tensor<fp16, [5]>([0x1.e08p-4, -0x1.d1cp-4, 0x1.c1p-4, -0x1.474p-4, -0x1.26cp-5])];
            tensor<fp16, [?, 5]> linear_3_cast_fp16 = linear(bias = classification_head_bias_to_fp16, weight = classification_head_weight_to_fp16, x = linear_2_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
            tensor<string, []> linear_3_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("linear_3_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [?, 5]> logits_1 = cast(dtype = linear_3_cast_fp16_to_fp32_dtype_0, x = linear_3_cast_fp16)[name = tensor<string, []>("cast_0")];
        } -> (logits_1);
}