parameters: (
          self,
          metadata: NetworkMetadata,
          network_input: List[str],
          working_directory: str,
          keep_onnx_model: bool,
          keep_pytorch_model: bool,
          timing_profile: TimingProfile,
          use_cpu: bool = False,
          batch_size: int = 1
      )
return_statement: return results
docstring: Main entry point of our function which compiles and generates our model data.
docstring_summary: Main entry point of our function which compiles and generates our model data.
docstring_tokens: Main entry point of our function which compiles and generates our model data .
function: def run_framework(
          self,
          metadata: NetworkMetadata,
          network_input: List[str],
          working_directory: str,
          keep_onnx_model: bool,
          keep_pytorch_model: bool,
          timing_profile: TimingProfile,
          use_cpu: bool = False,
          batch_size: int = 1
      ) -> List[NetworkResult]:
          """
          Main entry point of our function which compiles and generates our model data.
          """
          results = []
          workspace = NNFolderWorkspace(
              self.config.network_name, metadata, working_directory
          )
          try:
              network_fpaths = self.generate_and_download_framework(metadata, workspace)
              for ninput in network_input:
                  results.append(
                      self.execute_inference(
                          metadata, network_fpaths, ninput, timing_profile, use_cpu
                      )
                  )
          finally:
              self.cleanup(workspace, keep_onnx_model, keep_pytorch_model)
  
          return results
function_tokens: def run_framework ( self , metadata : NetworkMetadata , network_input : List [ str ] , working_directory : str , keep_onnx_model : bool , keep_pytorch_model : bool , timing_profile : TimingProfile , use_cpu : bool = False , batch_size : int = 1 ) -> List [ NetworkResult ] : results = [ ] workspace = NNFolderWorkspace ( self . config . network_name , metadata , working_directory ) try : network_fpaths = self . generate_and_download_framework ( metadata , workspace ) for ninput in network_input : results . append ( self . execute_inference ( metadata , network_fpaths , ninput , timing_profile , use_cpu ) ) finally : self . cleanup ( workspace , keep_onnx_model , keep_pytorch_model ) return results