1# Copyright 2019 The TensorFlow Authors. All Rights Reserved. 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================== 15 16"""API for enabling v2 control flow.""" 17 18from __future__ import absolute_import 19from __future__ import division 20from __future__ import print_function 21 22from tensorflow.python.framework import ops 23from tensorflow.python.ops import control_flow_util 24from tensorflow.python.ops import control_flow_util_v2 25from tensorflow.python.platform import tf_logging as logging 26from tensorflow.python.util.tf_export import tf_export 27 28 29@tf_export(v1=["enable_control_flow_v2"]) 30def enable_control_flow_v2(): # pylint: disable=invalid-name 31 """Use control flow v2. 32 33 control flow v2 (cfv2) is an improved version of control flow in TensorFlow 34 with support for higher order derivatives. Enabling cfv2 will change the 35 graph/function representation of control flow, e.g., `tf.while_loop` and 36 `tf.cond` will generate functional `While` and `If` ops instead of low-level 37 `Switch`, `Merge` etc. ops. Note: Importing and running graphs exported 38 with old control flow will still be supported. 39 40 Calling tf.enable_control_flow_v2() lets you opt-in to this TensorFlow 2.0 41 feature. 42 43 Note: v2 control flow is always enabled inside of tf.function. Calling this 44 function is not required. 45 """ 46 # pylint: disable=protected-access 47 logging.vlog(1, "Enabling control flow v2") 48 ops._control_flow_api_gauge.get_cell().set(True) 49 control_flow_util.ENABLE_CONTROL_FLOW_V2 = True 50 51 52@tf_export(v1=["disable_control_flow_v2"]) 53def disable_control_flow_v2(): # pylint: disable=invalid-name 54 """Opts out of control flow v2. 55 56 Note: v2 control flow is always enabled inside of tf.function. Calling this 57 function has no effect in that case. 58 59 If your code needs tf.disable_control_flow_v2() to be called to work 60 properly please file a bug. 61 """ 62 # pylint: disable=protected-access 63 logging.vlog(1, "Disabling control flow v2") 64 ops._control_flow_api_gauge.get_cell().set(False) 65 control_flow_util.ENABLE_CONTROL_FLOW_V2 = False 66 67 68@tf_export(v1=["control_flow_v2_enabled"]) 69def control_flow_v2_enabled(): # pylint: disable=invalid-name 70 """Returns `True` if v2 control flow is enabled. 71 72 Note: v2 control flow is always enabled inside of tf.function. 73 """ 74 return control_flow_util.EnableControlFlowV2(ops.get_default_graph()) 75 76 77@tf_export(v1=["experimental.output_all_intermediates"]) 78def output_all_intermediates(state): # pylint: disable=invalid-name 79 """Whether to output all intermediates from functional control flow ops. 80 81 The "default" behavior to is to output all intermediates when using v2 control 82 flow inside Keras models in graph mode (possibly inside Estimators). This is 83 needed to support taking gradients of v2 control flow. In graph mode, Keras 84 can sometimes freeze the forward graph before the gradient computation which 85 does not work for v2 control flow since it requires updating the forward ops 86 to output the needed intermediates. We work around this by proactively 87 outputting the needed intermediates when building the forward pass itself. 88 Ideally any such extra tensors should be pruned out at runtime. However, if 89 for any reason this doesn't work for you or if you have an inference-only 90 model you can turn this behavior off using 91 `tf.compat.v1.experimental.output_all_intermediates(False)`. 92 93 If with the default behavior you are still seeing errors of the form 94 "Connecting to invalid output X of source node Y which has Z outputs" try 95 setting `tf.compat.v1.experimental.output_all_intermediates(True)` and 96 please file an issue at https://github.com/tensorflow/tensorflow/issues. 97 98 Args: 99 state: True, False or None. None restores the default behavior. 100 """ 101 control_flow_util_v2._EXPERIMENTAL_OUTPUT_ALL_INTERMEDIATES_OVERRIDE = state # pylint: disable=protected-access 102