program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3401.3.1"}, {"coremlc-version", "3401.4.1"}, {"coremltools-component-torch", "2.6.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "8.2"}})]
{
    func main<ios17>(tensor<fp16, [1, 640]> decoder_output_projected, tensor<fp16, [1, 640]> encoder_output_projected) {
            tensor<fp16, [1, 640]> input_1_cast_fp16 = add(x = decoder_output_projected, y = encoder_output_projected)[name = tensor<string, []>("input_1_cast_fp16")];
            tensor<fp16, [1, 640]> input_3_cast_fp16 = relu(x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<fp16, [1030, 640]> joint_net_1_weight_to_fp16 = const()[name = tensor<string, []>("joint_net_1_weight_to_fp16"), val = tensor<fp16, [1030, 640]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [1030]> joint_net_1_bias_to_fp16 = const()[name = tensor<string, []>("joint_net_1_bias_to_fp16"), val = tensor<fp16, [1030]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1318528)))];
            tensor<fp16, [1, 1030]> linear_0_cast_fp16 = linear(bias = joint_net_1_bias_to_fp16, weight = joint_net_1_weight_to_fp16, x = input_3_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<int32, []> var_11 = const()[name = tensor<string, []>("op_11"), val = tensor<int32, []>(-1)];
            tensor<fp16, [1, 1030]> var_13_softmax_cast_fp16 = softmax(axis = var_11, x = linear_0_cast_fp16)[name = tensor<string, []>("op_13_softmax_cast_fp16")];
            tensor<fp32, []> var_13_epsilon_0 = const()[name = tensor<string, []>("op_13_epsilon_0"), val = tensor<fp32, []>(0x1p-149)];
            tensor<fp16, [1, 1030]> logits = log(epsilon = var_13_epsilon_0, x = var_13_softmax_cast_fp16)[name = tensor<string, []>("op_13_cast_fp16")];
        } -> (logits);
}