106 lines
3.5 KiB
Python
106 lines
3.5 KiB
Python
# 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 tempfile
|
|
|
|
import numpy as np
|
|
import tensorflow
|
|
|
|
from tensorflow.python import debug as tf_debug
|
|
|
|
tf = tensorflow.compat.v1
|
|
|
|
|
|
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.
|
|
config_file_path = (
|
|
tempfile.mktemp(".tfdbg_config")
|
|
if FLAGS.use_random_config_path else None)
|
|
sess = tf_debug.LocalCLIDebugWrapperSession(
|
|
sess, ui_type=FLAGS.ui_type, config_file_path=config_file_path)
|
|
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(
|
|
"--use_random_config_path",
|
|
type="bool",
|
|
nargs="?",
|
|
const=True,
|
|
default=False,
|
|
help="""If set, set config file path to a random file in the temporary
|
|
directory.""")
|
|
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()
|
|
with tf.Graph().as_default():
|
|
tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)
|