parameters: (self, transformation_cache, state_manager)
return_statement: return self._get_sparse_tensors_for_input_tensor(input_tensor)
docstring: Converts dense inputs to SparseTensor so downstream code can use it.
docstring_summary: Converts dense inputs to SparseTensor so downstream code can use it.
docstring_tokens: Converts dense inputs to SparseTensor so downstream code can use it .
function: def get_sparse_tensors(self, transformation_cache, state_manager):
      """Converts dense inputs to SparseTensor so downstream code can use it."""
      input_tensor = transformation_cache.get(self, state_manager)
      return self._get_sparse_tensors_for_input_tensor(input_tensor)
function_tokens: def get_sparse_tensors ( self , transformation_cache , state_manager ) : input_tensor = transformation_cache . get ( self , state_manager ) return self . _get_sparse_tensors_for_input_tensor ( input_tensor )