parameters: (self, path, epoch=0, remove_amp_cast=True)
docstring: Export HybridBlock to json format that can be loaded by
          `SymbolBlock.imports`, `mxnet.mod.Module` or the C++ interface.
  
          .. note:: When there are only one input, it will have name `data`. When there
                    Are more than one inputs, they will be named as `data0`, `data1`, etc.
  
          Parameters
          ----------
          path : str
              Path to save model. Two files `path-symbol.json` and `path-xxxx.params`
              will be created, where xxxx is the 4 digits epoch number.
          epoch : int
              Epoch number of saved model.
docstring_summary: Export HybridBlock to json format that can be loaded by
          `SymbolBlock.imports`, `mxnet.mod.Module` or the C++ interface.
docstring_tokens: Export HybridBlock to json format that can be loaded by SymbolBlock . imports mxnet . mod . Module or the C ++ interface .
function: def export(self, path, epoch=0, remove_amp_cast=True):
          """Export HybridBlock to json format that can be loaded by
          `SymbolBlock.imports`, `mxnet.mod.Module` or the C++ interface.
  
          .. note:: When there are only one input, it will have name `data`. When there
                    Are more than one inputs, they will be named as `data0`, `data1`, etc.
  
          Parameters
          ----------
          path : str
              Path to save model. Two files `path-symbol.json` and `path-xxxx.params`
              will be created, where xxxx is the 4 digits epoch number.
          epoch : int
              Epoch number of saved model.
          """
          if not self._cached_graph:
              raise RuntimeError(
                  "Please first call block.hybridize() and then run forward with "
                  "this block at least once before calling export.")
          sym = self._cached_graph[1]
          sym.save('%s-symbol.json'%path, remove_amp_cast=remove_amp_cast)
  
          arg_names = set(sym.list_arguments())
          aux_names = set(sym.list_auxiliary_states())
          arg_dict = {}
          for name, param in self.collect_params().items():
              if name in arg_names:
                  arg_dict['arg:%s'%name] = param._reduce()
              else:
                  assert name in aux_names
                  arg_dict['aux:%s'%name] = param._reduce()
          ndarray.save('%s-%04d.params'%(path, epoch), arg_dict)
function_tokens: def export ( self , path , epoch = 0 , remove_amp_cast = True ) : if not self . _cached_graph : raise RuntimeError ( "Please first call block.hybridize() and then run forward with " "this block at least once before calling export." ) sym = self . _cached_graph [ 1 ] sym . save ( '%s-symbol.json' % path , remove_amp_cast = remove_amp_cast ) arg_names = set ( sym . list_arguments ( ) ) aux_names = set ( sym . list_auxiliary_states ( ) ) arg_dict = { } for name , param in self . collect_params ( ) . items ( ) : if name in arg_names : arg_dict [ 'arg:%s' % name ] = param . _reduce ( ) else : assert name in aux_names arg_dict [ 'aux:%s' % name ] = param . _reduce ( ) ndarray . save ( '%s-%04d.params' % ( path , epoch ) , arg_dict )