docstr: Generates the CUDA template caller object for the given GEMM template and operation. This CUDATemplateCaller
  may be used to call and benchmark the generated CUDA kernel in a standalone manner to enable Autotuning.
  
  Args:
      kwargs: Additional keyword arguments.
  
  Returns:
      A CUDATemplateCaller object representing the generated CUDA template caller.
docstr_tok: ["Generates","the","CUDA","template","caller","object","for","the","given","GEMM","template","and","operation",".","This","CUDATemplateCaller","may","be","used","to","call","and","benchmark","the","generated","CUDA","kernel","in","a","standalone","manner","to","enable","Autotuning",".","Args",":","kwargs",":","Additional","keyword","arguments",".","Returns",":","A","CUDATemplateCaller","object","representing","the","generated","CUDA","template","caller","."]
code: def generate(  # type: ignore[override]
      self,
      **kwargs,
  ) -> CUDATemplateCaller:
      """
      Generates the CUDA template caller object for the given GEMM template and operation. This CUDATemplateCaller
      may be used to call and benchmark the generated CUDA kernel in a standalone manner to enable Autotuning.
  
      Args:
          kwargs: Additional keyword arguments.
  
      Returns:
          A CUDATemplateCaller object representing the generated CUDA template caller.
      """
      kernel_name = f"cuda_{self.name}"
      with patch.object(
          V.graph, "get_dtype", self._fake_get_dtype(self.output_node)
      ), CUDATemplateKernel(
          kernel_name=kernel_name,
      ) as kernel:
          code = self.render(kernel=kernel, **kwargs)
          _, call_args, _ = kernel.args.python_argdefs()
          log.debug("Generated Code:\n%s", code)
          log.debug(
              "Args: cpp_argdefs: %s, python_argdefs: %s",
              kernel.args.cpp_argdefs(),
              kernel.args.python_argdefs(),
          )
  
      input_reorder = (
          self.input_reorder
          if self.input_reorder is not None
          else list(range(len(self.input_nodes)))
      )
      expected_args = list(
          unique(
              self.input_nodes[idx].get_name() for idx in input_reorder
          )
      )
      expected_args.extend([self.output_node.get_name()])
      assert list(call_args)[: len(expected_args)] == expected_args, (
          call_args,
          expected_args,
      )
      extra_args = V.graph.sizevars.size_hints(
          map(sympy.expand, call_args[len(expected_args) :])
      )
  
      kernel_hash_name = f"cuda_{self.name}_{next(self.index_counter)}"
  
      # create the BenchmarkRequest
      bmreq = CUDABenchmarkRequest(
          kernel_name=kernel_name,
          input_tensor_meta=TensorMeta.from_irnodes(self.input_nodes),
          output_tensor_meta=TensorMeta.from_irnodes(self.output_node),
          extra_args=extra_args,
          source_code=code,
      )
  
      def make_kernel_render(
          template_node: CUDATemplateBuffer,
          epilogue_nodes: Optional[List[IRNode]] = None,
      ):
          kernel = CUDATemplateKernel(
              kernel_name="KERNEL_NAME",
          )
          render = functools.partial(
              self.render,
              kernel=kernel,
              template_buffer_node=template_node,
              epilogue_nodes=epilogue_nodes,
              **kwargs,  # includes "op" argument in case of CUTLASSGemmTemplate
          )
          return kernel, render
  
      return CUDATemplateCaller(
          kernel_hash_name,
          self.name,
          self.input_nodes,
          self.output_node.get_layout(),
          make_kernel_render,
          bmreq,
          self,
      )
  
imports: import functools
  import itertools
  import logging
  from typing import List, Optional
  from unittest.mock import patch
  import sympy
  import torch
  from ...autotune_process import CUDABenchmarkRequest, TensorMeta
  from ...ir import Buffer, CUDATemplateBuffer, IRNode, Layout
  from ...utils import IndentedBuffer, unique
  from ...virtualized import V
  from ..common import KernelTemplate
  from .cuda_kernel import CUDATemplateCaller, CUDATemplateKernel
label_desc: Use image node_id 2 for calling the CUDATemplate obj's underlying member method code with example usage: obj.generate() and returns: CUDATemplateCaller, kernel,  render