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# 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)
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