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Diffstat (limited to 'tensorflow/python/debug/examples/debug_keras.py')
-rw-r--r-- | tensorflow/python/debug/examples/debug_keras.py | 89 |
1 files changed, 89 insertions, 0 deletions
diff --git a/tensorflow/python/debug/examples/debug_keras.py b/tensorflow/python/debug/examples/debug_keras.py new file mode 100644 index 0000000000..3272d85ade --- /dev/null +++ b/tensorflow/python/debug/examples/debug_keras.py @@ -0,0 +1,89 @@ +# Copyright 2016 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. +# ============================================================================== +"""tfdbg example: debugging tf.keras models training on tf.data.Dataset.""" + +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import argparse +import sys + +import numpy as np +import tensorflow as tf + +from tensorflow.python import debug as tf_debug + + +def main(_): + # Create a dummy dataset. + num_examples = 8 + steps_per_epoch = 2 + input_dims = 3 + output_dims = 1 + xs = np.zeros([num_examples, input_dims]) + ys = np.zeros([num_examples, output_dims]) + dataset = tf.data.Dataset.from_tensor_slices( + (xs, ys)).repeat(num_examples).batch(int(num_examples / steps_per_epoch)) + + sess = tf.Session() + if FLAGS.debug: + # Use the command-line interface (CLI) of tfdbg. + sess = tf_debug.LocalCLIDebugWrapperSession(sess, ui_type=FLAGS.ui_type) + elif FLAGS.tensorboard_debug_address: + # Use the TensorBoard Debugger Plugin (GUI of tfdbg). + sess = tf_debug.TensorBoardDebugWrapperSession( + sess, FLAGS.tensorboard_debug_address) + tf.keras.backend.set_session(sess) + + # Create a dummy model. + model = tf.keras.Sequential([ + tf.keras.layers.Dense(1, input_shape=[input_dims])]) + model.compile(loss="mse", optimizer="sgd") + + # Train the model using the dummy dataset created above. + model.fit(dataset, epochs=FLAGS.epochs, steps_per_epoch=steps_per_epoch) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.register("type", "bool", lambda v: v.lower() == "true") + parser.add_argument( + "--debug", + type="bool", + nargs="?", + const=True, + default=False, + help="Use debugger to track down bad values during training. " + "Mutually exclusive with the --tensorboard_debug_address flag.") + parser.add_argument( + "--ui_type", + type=str, + default="curses", + help="Command-line user interface type (curses | readline).") + parser.add_argument( + "--tensorboard_debug_address", + type=str, + default=None, + help="Connect to the TensorBoard Debugger Plugin backend specified by " + "the gRPC address (e.g., localhost:1234). Mutually exclusive with the " + "--debug flag.") + parser.add_argument( + "--epochs", + type=int, + default=2, + help="Number of epochs to train the model for.") + FLAGS, unparsed = parser.parse_known_args() + tf.app.run(main=main, argv=[sys.argv[0]] + unparsed) |