code: def gen_forward():
      kernels = [3, 5, 7, 15, 31, 63, 127, 255]
      blocks = [32, 64, 128, 256]
  
      head = """
  /**
   * Copyright (c) Facebook, Inc. and its affiliates.
   *
   * This source code is licensed under the MIT license found in the
   * LICENSE file in the root directory of this source tree.
   */
  
  #include "dynamicconv_cuda.cuh"
  
  std::vector<at::Tensor> dynamicconv_cuda_forward(at::Tensor input, at::Tensor weight, int padding_l) {
  
      at::DeviceGuard g(input.device());
      const auto minibatch = input.size(0);
      const auto numFeatures = input.size(1);
      const auto sequenceLength = input.size(2);
  
      const auto numHeads = weight.size(1);
      const auto filterSize = weight.size(2);
  
      const auto numFiltersInBlock = numFeatures / numHeads;
      const dim3 blocks(minibatch, numFeatures);
  
      auto output = at::zeros_like(input);
      auto stream = at::cuda::getCurrentCUDAStream();
  """
  
      switch = """
      switch(filterSize) {
  """
  
      case_k = """
          case {k}:
  """
  
      main_block = """
              if (padding_l == {pad}) {{
                  AT_DISPATCH_FLOATING_TYPES_AND_HALF(input.scalar_type(), "dynamicconv_forward", ([&] {{
                      dynamicconv_forward_kernel<{k}, {b_size}, {pad}, scalar_t>
                      <<<blocks, {b_size}, 0, stream>>>(
                              input.data<scalar_t>(),
                              weight.data<scalar_t>(),
                              minibatch,
                              sequenceLength,
                              numFeatures,
                              numFiltersInBlock,
                              numHeads,
                              output.data<scalar_t>());
                  }}));
              }} else
  """
  
      bad_padding = """
              {
                  std::cout << "WARNING: Unsupported padding size - skipping forward pass" << std::endl;
              }
              break;\n
  """
  
      end = """
          default:
              std::cout << "WARNING: Unsupported filter length passed - skipping forward pass" << std::endl;
      }
  
      return {output};
  }
  """
  
      with open("dynamicconv_cuda_forward.cu", "w") as forward:
          forward.write(head)
          forward.write(switch)
          for k in kernels:
              b_size = 32
              for b in blocks:
                  if b > k:
                      b_size = b
                      break
              forward.write(case_k.format(k=k))
              for pad in [k // 2, k - 1]:
                  forward.write(
                      main_block.format(k=k, b_size=b_size, pad=pad)
                  )
              forward.write(bad_padding)
          forward.write(end)
  
label_desc: Use image node_id 1 for calling a global function with example usage: gen_forward() without return types