# Copyright 2017 The TensorFlow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================== """Python wrapper for prefetching_ops.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from tensorflow.python.data.experimental.ops import prefetching_ops from tensorflow.python.util import deprecation @deprecation.deprecated(None, "Use `tf.data.experimental.prefetch_to_device(...)`.") def prefetch_to_device(device, buffer_size=None): """A transformation that prefetches dataset values to the given `device`. NOTE: Although the transformation creates a `tf.data.Dataset`, the transformation must be the final `Dataset` in the input pipeline. Args: device: A string. The name of a device to which elements will be prefetched. buffer_size: (Optional.) The number of elements to buffer on `device`. Defaults to an automatically chosen value. Returns: A `Dataset` transformation function, which can be passed to `tf.data.Dataset.apply`. """ return prefetching_ops.prefetch_to_device(device, buffer_size) @deprecation.deprecated(None, "Use `tf.data.experimental.copy_to_device(...)`.") def copy_to_device(target_device, source_device="/cpu:0"): """A transformation that copies dataset elements to the given `target_device`. Args: target_device: The name of a device to which elements will be copied. source_device: The original device on which `input_dataset` will be placed. Returns: A `Dataset` transformation function, which can be passed to `tf.data.Dataset.apply`. """ return prefetching_ops.copy_to_device(target_device, source_device)