def _as_variant_tensor(self): # pylint: disable=protected-access input_resource = self._input_dataset._as_variant_tensor() return gen_dataset_ops.map_and_batch_dataset( input_resource, self._map_func.captured_inputs, f=self._map_func, batch_size=self._batch_size, num_parallel_batches=self._num_parallel_batches, output_types=nest.flatten(self.output_types), output_shapes=nest.flatten(self.output_shapes))
def _as_variant_tensor(self): # pylint: disable=protected-access input_resource = self._input_dataset._as_variant_tensor() return gen_dataset_ops.map_and_batch_dataset( input_resource, self._map_func.captured_inputs, f=self._map_func, batch_size=self._batch_size, num_parallel_batches=self._num_parallel_batches, output_types=nest.flatten(self.output_types), output_shapes=nest.flatten(self.output_shapes))
def _as_variant_tensor(self): # pylint: disable=protected-access input_resource = self._input_dataset._as_variant_tensor() return gen_dataset_ops.map_and_batch_dataset( input_resource, self._map_func.captured_inputs, f=self._map_func, batch_size=self._batch_size_t, num_parallel_batches=self._num_parallel_batches_t, drop_remainder=self._drop_remainder_t, output_types=nest.flatten( sparse.as_dense_types(self.output_types, self.output_classes)), output_shapes=nest.flatten( sparse.as_dense_shapes(self.output_shapes, self.output_classes)))
def _as_variant_tensor(self): # pylint: disable=protected-access input_resource = self._input_dataset._as_variant_tensor() return gen_dataset_ops.map_and_batch_dataset( input_resource, self._map_func.captured_inputs, f=self._map_func, batch_size=self._batch_size_t, num_parallel_batches=self._num_parallel_batches_t, drop_remainder=self._drop_remainder_t, output_types=nest.flatten( sparse.as_dense_types(self.output_types, self.output_classes)), output_shapes=nest.flatten( sparse.as_dense_shapes(self.output_shapes, self.output_classes)))