chore: import upstream snapshot with attribution

tensorflow/python/debug/examples/README.md

@@ -0,0 +1,9 @@
+Hi, there!
+
+The documentation of **TensorFlow Debugger (tfdbg)** has moved.
+
+See the source version at
+[this new location](../../../docs_src/guide/debugger.md).
+
+See the public website version at
+[https://www.tensorflow.org/guide/debugger](https://www.tensorflow.org/guide/debugger).

tensorflow/python/debug/examples/v1/BUILD

@@ -0,0 +1,115 @@
+load("@rules_shell//shell:sh_test.bzl", "sh_test")
+load("@xla//third_party/rules_python/python:py_binary.bzl", "py_binary")
+
+package(
+    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
+    licenses = ["notice"],
+)
+
+py_binary(
+    name = "debug_fibonacci",
+    srcs = ["debug_fibonacci.py"],
+    strict_deps = True,
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+        "//third_party/py/numpy",
+    ],
+)
+
+py_binary(
+    name = "debug_errors",
+    srcs = ["debug_errors.py"],
+    strict_deps = True,
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+        "//third_party/py/numpy",
+    ],
+)
+
+py_binary(
+    name = "debug_keras",
+    srcs = ["debug_keras.py"],
+    strict_deps = True,
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+        "//third_party/py/numpy",
+    ],
+)
+
+py_binary(
+    name = "debug_mnist",
+    srcs = ["debug_mnist_v1.py"],
+    main = "debug_mnist_v1.py",
+    strict_deps = True,
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+    ],
+)
+
+sh_test(
+    name = "examples_v1_debug_errors_test",
+    srcs = ["examples_v1_debug_errors_test.sh"],
+    data = [
+        ":debug_errors",
+    ],
+    tags = [
+        "no_windows",
+        "noasan",  # TODO(b/190625515)
+        "v1only",
+    ],
+)
+
+sh_test(
+    name = "examples_v1_debug_fibonacci_test",
+    srcs = ["examples_v1_debug_fibonacci_test.sh"],
+    data = [
+        ":debug_fibonacci",
+    ],
+    tags = [
+        "no_windows",
+        "v1only",
+    ],
+)
+
+sh_test(
+    name = "examples_v1_debug_keras_test",
+    size = "medium",
+    srcs = ["examples_v1_debug_keras_test.sh"],
+    data = [
+        ":debug_keras",
+    ],
+    tags = [
+        "no_windows",
+        "noasan",  # TODO(b/190625515)
+        "v1only",
+    ],
+)
+
+sh_test(
+    name = "examples_v1_debug_mnist_test",
+    srcs = ["examples_v1_debug_mnist_test.sh"],
+    data = [
+        ":debug_mnist",
+    ],
+    tags = [
+        "no_windows",
+        "noasan",  # TODO(b/193153560)
+        "v1only",
+    ],
+)
+
+sh_test(
+    name = "examples_v1_offline_analyzer_test",
+    srcs = ["examples_v1_offline_analyzer_test.sh"],
+    data = [
+        "//tensorflow/python/debug/cli:offline_analyzer",
+    ],
+    tags = [
+        "no_windows",
+        "v1only",
+    ],
+)

tensorflow/python/debug/examples/v1/debug_errors.py

@@ -0,0 +1,93 @@
+# 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.
+# ==============================================================================
+"""Example of debugging TensorFlow runtime errors using tfdbg."""
+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(_):
+  sess = tf.Session()
+
+  # Construct the TensorFlow network.
+  ph_float = tf.placeholder(tf.float32, name="ph_float")
+  x = tf.transpose(ph_float, name="x")
+  v = tf.Variable(np.array([[-2.0], [-3.0], [6.0]], dtype=np.float32), name="v")
+  m = tf.constant(
+      np.array([[0.0, 1.0, 2.0], [-4.0, -1.0, 0.0]]),
+      dtype=tf.float32,
+      name="m")
+  y = tf.matmul(m, x, name="y")
+  z = tf.matmul(m, v, name="z")
+
+  if FLAGS.debug:
+    if FLAGS.use_random_config_path:
+      _, config_file_path = tempfile.mkstemp(".tfdbg_config")
+    else:
+      config_file_path = None
+    sess = tf_debug.LocalCLIDebugWrapperSession(
+        sess, ui_type=FLAGS.ui_type, config_file_path=config_file_path)
+
+  if FLAGS.error == "shape_mismatch":
+    print(sess.run(y, feed_dict={ph_float: np.array([[0.0], [1.0], [2.0]])}))
+  elif FLAGS.error == "uninitialized_variable":
+    print(sess.run(z))
+  elif FLAGS.error == "no_error":
+    print(sess.run(y, feed_dict={ph_float: np.array([[0.0, 1.0, 2.0]])}))
+  else:
+    raise ValueError("Unrecognized error type: " + FLAGS.error)
+
+
+if __name__ == "__main__":
+  parser = argparse.ArgumentParser()
+  parser.register("type", "bool", lambda v: v.lower() == "true")
+  parser.add_argument(
+      "--error",
+      type=str,
+      default="shape_mismatch",
+      help="""\
+      Type of the error to generate (shape_mismatch | uninitialized_variable |
+      no_error).\
+      """)
+  parser.add_argument(
+      "--ui_type",
+      type=str,
+      default="readline",
+      help="Command-line user interface type (only readline is supported)")
+  parser.add_argument(
+      "--debug",
+      type="bool",
+      nargs="?",
+      const=True,
+      default=False,
+      help="Use debugger to track down bad values during training")
+  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.""")
+  FLAGS, unparsed = parser.parse_known_args()
+  with tf.Graph().as_default():
+    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)

tensorflow/python/debug/examples/v1/debug_fibonacci.py

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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.
+# ==============================================================================
+"""Demo of the tfdbg readline UI: A TF network computing Fibonacci sequence."""
+import argparse
+import sys
+
+import numpy as np
+import tensorflow
+
+from tensorflow.python import debug as tf_debug
+
+tf = tensorflow.compat.v1
+
+FLAGS = None
+
+
+def main(_):
+  sess = tf.Session()
+
+  # Construct the TensorFlow network.
+  n0 = tf.Variable(
+      np.ones([FLAGS.tensor_size] * 2), dtype=tf.int32, name="node_00")
+  n1 = tf.Variable(
+      np.ones([FLAGS.tensor_size] * 2), dtype=tf.int32, name="node_01")
+
+  for i in range(2, FLAGS.length):
+    n0, n1 = n1, tf.add(n0, n1, name="node_%.2d" % i)
+
+  sess.run(tf.global_variables_initializer())
+
+  # Wrap the TensorFlow Session object for debugging.
+  if FLAGS.debug and FLAGS.tensorboard_debug_address:
+    raise ValueError(
+        "The --debug and --tensorboard_debug_address flags are mutually "
+        "exclusive.")
+  if FLAGS.debug:
+    sess = tf_debug.LocalCLIDebugWrapperSession(sess)
+
+    def has_negative(_, tensor):
+      return np.any(tensor < 0)
+
+    sess.add_tensor_filter("has_inf_or_nan", tf_debug.has_inf_or_nan)
+    sess.add_tensor_filter("has_negative", has_negative)
+  elif FLAGS.tensorboard_debug_address:
+    sess = tf_debug.TensorBoardDebugWrapperSession(
+        sess, FLAGS.tensorboard_debug_address)
+
+  print("Fibonacci number at position %d:\n%s" % (FLAGS.length, sess.run(n1)))
+
+
+if __name__ == "__main__":
+  parser = argparse.ArgumentParser()
+  parser.register("type", "bool", lambda v: v.lower() == "true")
+  parser.add_argument(
+      "--tensor_size",
+      type=int,
+      default=1,
+      help="""\
+      Size of tensor. E.g., if the value is 30, the tensors will have shape
+      [30, 30].\
+      """)
+  parser.add_argument(
+      "--length",
+      type=int,
+      default=20,
+      help="Length of the fibonacci sequence to compute.")
+  parser.add_argument(
+      "--ui_type",
+      type=str,
+      default="readline",
+      help="Command-line user interface type (only readline is supported)")
+  parser.add_argument(
+      "--debug",
+      dest="debug",
+      action="store_true",
+      help="Use TensorFlow Debugger (tfdbg). Mutually exclusive with the "
+      "--tensorboard_debug_address flag.")
+  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.")
+
+  FLAGS, unparsed = parser.parse_known_args()
+  with tf.Graph().as_default():
+    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)

tensorflow/python/debug/examples/v1/debug_keras.py

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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."""
+
+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.
+    if FLAGS.use_random_config_path:
+      _, config_file_path = tempfile.mkstemp(".tfdbg_config")
+    else:
+      config_file_path = 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="readline",
+      help="Command-line user interface type (only readline is supported).")
+  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)

tensorflow/python/debug/examples/v1/debug_mnist_v1.py

@@ -0,0 +1,235 @@
+# 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.
+# ==============================================================================
+"""Demo of the tfdbg readline CLI: Locating the source of bad numerical values.
+
+The neural network in this demo is larged based on the tutorial at:
+  tensorflow/examples/tutorials/mnist/mnist_with_summaries.py
+
+But modifications are made so that problematic numerical values (infs and nans)
+appear in nodes of the graph during training.
+"""
+import argparse
+import sys
+import tempfile
+
+import tensorflow
+
+from tensorflow.python import debug as tf_debug
+
+tf = tensorflow.compat.v1
+
+IMAGE_SIZE = 28
+HIDDEN_SIZE = 500
+NUM_LABELS = 10
+RAND_SEED = 42
+
+FLAGS = None
+
+
+def parse_args():
+  """Parses commandline arguments.
+
+  Returns:
+    A tuple (parsed, unparsed) of the parsed object and a group of unparsed
+      arguments that did not match the parser.
+  """
+  parser = argparse.ArgumentParser()
+  parser.register("type", "bool", lambda v: v.lower() == "true")
+  parser.add_argument(
+      "--max_steps",
+      type=int,
+      default=10,
+      help="Number of steps to run trainer.")
+  parser.add_argument(
+      "--train_batch_size",
+      type=int,
+      default=100,
+      help="Batch size used during training.")
+  parser.add_argument(
+      "--learning_rate",
+      type=float,
+      default=0.025,
+      help="Initial learning rate.")
+  parser.add_argument(
+      "--data_dir",
+      type=str,
+      default="/tmp/mnist_data",
+      help="Directory for storing data")
+  parser.add_argument(
+      "--ui_type",
+      type=str,
+      default="readline",
+      help="Command-line user interface type (only readline is supported)")
+  parser.add_argument(
+      "--fake_data",
+      type="bool",
+      nargs="?",
+      const=True,
+      default=False,
+      help="Use fake MNIST data for unit testing")
+  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(
+      "--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(
+      "--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.""")
+  return parser.parse_known_args()
+
+
+def main(_):
+  # Import data
+  if FLAGS.fake_data:
+    imgs = tf.random.uniform(maxval=256, shape=(10, 28, 28), dtype=tf.int32)
+    labels = tf.random.uniform(maxval=10, shape=(10,), dtype=tf.int32)
+    mnist_train = imgs, labels
+    mnist_test = imgs, labels
+  else:
+    mnist_train, mnist_test = tf.keras.datasets.mnist.load_data()
+
+  def format_example(imgs, labels):
+    imgs = tf.reshape(imgs, [-1, 28 * 28])
+    imgs = tf.cast(imgs, tf.float32) / 255.0
+    labels = tf.one_hot(labels, depth=10, dtype=tf.float32)
+    return imgs, labels
+
+  ds_train = tf.data.Dataset.from_tensor_slices(mnist_train)
+  ds_train = ds_train.shuffle(
+      1000, seed=RAND_SEED).repeat().batch(FLAGS.train_batch_size)
+  ds_train = ds_train.map(format_example)
+  it_train = ds_train.make_initializable_iterator()
+
+  ds_test = tf.data.Dataset.from_tensors(mnist_test).repeat()
+  ds_test = ds_test.map(format_example)
+  it_test = ds_test.make_initializable_iterator()
+
+  sess = tf.InteractiveSession()
+
+  # Create the MNIST neural network graph.
+
+  # Input placeholders.
+  with tf.name_scope("input"):
+    handle = tf.placeholder(tf.string, shape=())
+
+    iterator = tf.data.Iterator.from_string_handle(
+        handle, (tf.float32, tf.float32),
+        ((None, IMAGE_SIZE * IMAGE_SIZE), (None, 10)))
+
+    x, y_ = iterator.get_next()
+
+  def weight_variable(shape):
+    """Create a weight variable with appropriate initialization."""
+    initial = tf.truncated_normal(shape, stddev=0.1, seed=RAND_SEED)
+    return tf.Variable(initial)
+
+  def bias_variable(shape):
+    """Create a bias variable with appropriate initialization."""
+    initial = tf.constant(0.1, shape=shape)
+    return tf.Variable(initial)
+
+  def nn_layer(input_tensor, input_dim, output_dim, layer_name, act=tf.nn.relu):
+    """Reusable code for making a simple neural net layer."""
+    # Adding a name scope ensures logical grouping of the layers in the graph.
+    with tf.name_scope(layer_name):
+      # This Variable will hold the state of the weights for the layer
+      with tf.name_scope("weights"):
+        weights = weight_variable([input_dim, output_dim])
+      with tf.name_scope("biases"):
+        biases = bias_variable([output_dim])
+      with tf.name_scope("Wx_plus_b"):
+        preactivate = tf.matmul(input_tensor, weights) + biases
+
+      activations = act(preactivate)
+      return activations
+
+  hidden = nn_layer(x, IMAGE_SIZE**2, HIDDEN_SIZE, "hidden")
+  logits = nn_layer(hidden, HIDDEN_SIZE, NUM_LABELS, "output", tf.identity)
+  y = tf.nn.softmax(logits)
+
+  with tf.name_scope("cross_entropy"):
+    # The following line is the culprit of the bad numerical values that appear
+    # during training of this graph. Log of zero gives inf, which is first seen
+    # in the intermediate tensor "cross_entropy/Log:0" during the 4th run()
+    # call. A multiplication of the inf values with zeros leads to nans,
+    # which is first in "cross_entropy/mul:0".
+    #
+    # You can use the built-in, numerically-stable implementation to fix this
+    # issue:
+    #   diff = tf.nn.softmax_cross_entropy_with_logits(labels=y_, logits=logits)
+
+    diff = -(y_ * tf.log(y))
+    with tf.name_scope("total"):
+      cross_entropy = tf.reduce_mean(diff)
+
+  with tf.name_scope("train"):
+    train_step = tf.train.AdamOptimizer(
+        FLAGS.learning_rate).minimize(cross_entropy)
+
+  with tf.name_scope("accuracy"):
+    with tf.name_scope("correct_prediction"):
+      correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1))
+    with tf.name_scope("accuracy"):
+      accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+
+  sess.run(tf.global_variables_initializer())
+  sess.run(it_train.initializer)
+  sess.run(it_test.initializer)
+  train_handle = sess.run(it_train.string_handle())
+  test_handle = sess.run(it_test.string_handle())
+
+  if FLAGS.debug and FLAGS.tensorboard_debug_address:
+    raise ValueError(
+        "The --debug and --tensorboard_debug_address flags are mutually "
+        "exclusive.")
+  if FLAGS.debug:
+    if FLAGS.use_random_config_path:
+      _, config_file_path = tempfile.mkstemp(".tfdbg_config")
+    else:
+      config_file_path = None
+    sess = tf_debug.LocalCLIDebugWrapperSession(
+        sess, ui_type=FLAGS.ui_type, config_file_path=config_file_path)
+  elif FLAGS.tensorboard_debug_address:
+    sess = tf_debug.TensorBoardDebugWrapperSession(
+        sess, FLAGS.tensorboard_debug_address)
+
+  # Add this point, sess is a debug wrapper around the actual Session if
+  # FLAGS.debug is true. In that case, calling run() will launch the CLI.
+  for i in range(FLAGS.max_steps):
+    acc = sess.run(accuracy, feed_dict={handle: test_handle})
+    print("Accuracy at step %d: %s" % (i, acc))
+
+    sess.run(train_step, feed_dict={handle: train_handle})
+
+
+if __name__ == "__main__":
+  FLAGS, unparsed = parse_args()
+  with tf.Graph().as_default():
+    tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)

tensorflow/python/debug/examples/v1/examples_v1_debug_errors_test.sh

@@ -0,0 +1,66 @@
+#!/bin/bash
+# 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.
+# ==============================================================================
+#
+# Bash unit tests for TensorFlow Debugger (tfdbg) Python examples that do not
+# involve downloading data.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg debug_errors against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  DEBUG_ERRORS_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_errors"
+else
+  DEBUG_ERRORS_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_errors"
+fi
+
+# Override the default ui_type=curses to allow the test to pass in a tty-less
+# test environment.
+cat << EOF | ${DEBUG_ERRORS_BIN} --error=no_error --ui_type=readline
+run
+exit
+EOF
+
+cat << EOF | ${DEBUG_ERRORS_BIN} --error=uninitialized_variable --debug --ui_type=readline --use_random_config_path
+run
+ni -a -d -t v/read
+exit
+EOF
+
+echo
+echo "SUCCESS: tfdbg debug_errors test PASSED"

tensorflow/python/debug/examples/v1/examples_v1_debug_fibonacci_test.sh

@@ -0,0 +1,60 @@
+#!/bin/bash
+# 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.
+# ==============================================================================
+#
+# Bash unit tests for TensorFlow Debugger (tfdbg) Python examples that do not
+# involve downloading data.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg debug_fibonacci against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  DEBUG_FIBONACCI_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_fibonacci"
+else
+  DEBUG_FIBONACCI_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_fibonacci"
+fi
+
+# Override the default ui_type=curses to allow the test to pass in a tty-less
+# test environment.
+cat << EOF | ${DEBUG_FIBONACCI_BIN} --tensor_size=2 --ui_type=readline
+run
+exit
+EOF
+
+echo
+echo "SUCCESS: tfdbg debug_fibonacci test PASSED"

tensorflow/python/debug/examples/v1/examples_v1_debug_keras_test.sh

@@ -0,0 +1,66 @@
+#!/bin/bash
+# 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.
+# ==============================================================================
+#
+# Bash unit tests for TensorFlow Debugger (tfdbg) Python examples that do not
+# involve downloading data.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg debug_keras against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  DEBUG_KERAS_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_keras"
+else
+  DEBUG_KERAS_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_keras"
+fi
+
+# Override the default ui_type=curses to allow the test to pass in a tty-less
+# test environment.
+
+# Test debugging of tf.keras.
+cat << EOF | ${DEBUG_KERAS_BIN} --debug --ui_type=readline --use_random_config_path
+run -f has_inf_or_nan
+EOF
+
+# Test debugging of tf.keras, with non-debug runs included.
+cat << EOF | ${DEBUG_KERAS_BIN} --debug --ui_type=readline --use_random_config_path
+run -t 11
+EOF
+
+echo
+echo "SUCCESS: tfdbg debug_keras test PASSED"

tensorflow/python/debug/examples/v1/examples_v1_debug_mnist_test.sh

@@ -0,0 +1,61 @@
+#!/bin/bash
+# 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.
+# ==============================================================================
+#
+# Bash unit tests for TensorFlow Debugger (tfdbg) Python examples that do not
+# involve downloading data.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg examples and binaries against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  DEBUG_MNIST_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_mnist"
+else
+  DEBUG_MNIST_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_mnist"
+fi
+
+# Override the default ui_type=curses to allow the test to pass in a tty-less
+# test environment.
+cat << EOF | ${DEBUG_MNIST_BIN} --debug --max_steps=1 --fake_data --ui_type=readline --use_random_config_path
+run -t 1
+run --node_name_filter hidden --op_type_filter MatMul
+run -f has_inf_or_nan
+EOF
+
+echo
+echo "SUCCESS: tfdbg debug_mnist test PASSED"

tensorflow/python/debug/examples/v1/examples_v1_offline_analyzer_test.sh

@@ -0,0 +1,70 @@
+#!/bin/bash
+# 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.
+# ==============================================================================
+#
+# Bash unit tests for the binary offline_analyzer.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg offline analyzer against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  OFFLINE_ANALYZER_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/cli/offline_analyzer"
+else
+  OFFLINE_ANALYZER_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.cli.offline_analyzer"
+fi
+
+# Test offline_analyzer.
+echo
+echo "Testing offline_analyzer"
+echo
+
+# TODO(cais): Generate an actual debug dump and load it with offline_analyzer,
+# so that we can test the binary runs with a non-error exit code.
+set +e
+OUTPUT=$(${OFFLINE_ANALYZER_BIN} 2>&1)
+set -e
+
+EXPECTED_OUTPUT="ERROR: dump_dir flag is empty."
+if ! echo "${OUTPUT}" | grep -q "${EXPECTED_OUTPUT}"; then
+  echo "ERROR: offline_analyzer output didn't match expectation: ${OUTPUT}" 1>&2
+  echo "Expected output: ${EXPECTED_OUTPUT}"
+  exit 1
+fi
+
+echo
+echo "SUCCESS: tfdbg offline analyzer test PASSED"

tensorflow/python/debug/examples/v1/examples_v1_test.sh

@@ -0,0 +1,130 @@
+#!/bin/bash
+# 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.
+# ==============================================================================
+#
+# Bash unit tests for TensorFlow Debugger (tfdbg) Python examples that do not
+# involve downloading data. Also tests the binary offline_analyzer.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg examples and binaries against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  DEBUG_FIBONACCI_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_fibonacci"
+  DEBUG_ERRORS_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_errors"
+  DEBUG_MNIST_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_mnist"
+  DEBUG_TFLEARN_IRIS_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_tflearn_iris"
+  DEBUG_KERAS_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v1/debug_keras"
+  OFFLINE_ANALYZER_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/cli/offline_analyzer"
+else
+  DEBUG_FIBONACCI_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_fibonacci"
+  DEBUG_ERRORS_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_errors"
+  DEBUG_MNIST_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_mnist"
+  DEBUG_TFLEARN_IRIS_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_tflearn_iris"
+  DEBUG_KERAS_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v1.debug_keras"
+  OFFLINE_ANALYZER_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.cli.offline_analyzer"
+fi
+
+# Override the default ui_type=curses to allow the test to pass in a tty-less
+# test environment.
+cat << EOF | ${DEBUG_FIBONACCI_BIN} --tensor_size=2 --ui_type=readline
+run
+exit
+EOF
+
+cat << EOF | ${DEBUG_ERRORS_BIN} --error=no_error --ui_type=readline
+run
+exit
+EOF
+
+cat << EOF | ${DEBUG_ERRORS_BIN} --error=uninitialized_variable --debug --ui_type=readline --use_random_config_path
+run
+ni -a -d -t v/read
+exit
+EOF
+
+cat << EOF | ${DEBUG_MNIST_BIN} --debug --max_steps=1 --fake_data --ui_type=readline --use_random_config_path
+run -t 1
+run --node_name_filter hidden --op_type_filter MatMul
+run -f has_inf_or_nan
+EOF
+
+# Test the custom dump_root option.
+CUSTOM_DUMP_ROOT=$(mktemp -d)
+mkdir -p ${CUSTOM_DUMP_ROOT}
+
+cat << EOF | ${DEBUG_TFLEARN_IRIS_BIN} --debug --train_steps=2 --dump_root="${CUSTOM_DUMP_ROOT}" --ui_type=readline --use_random_config_path
+run -p
+run -f has_inf_or_nan
+EOF
+
+# Verify that the dump root has been cleaned up on exit.
+if [[ -d "${CUSTOM_DUMP_ROOT}" ]]; then
+  echo "ERROR: dump root at ${CUSTOM_DUMP_ROOT} failed to be cleaned up." 1>&2
+  exit 1
+fi
+
+# Test debugging of tf.keras.
+cat << EOF | ${DEBUG_KERAS_BIN} --debug --ui_type=readline --use_random_config_path
+run -f has_inf_or_nan
+EOF
+
+# Test debugging of tf.keras, with non-debug runs included.
+cat << EOF | ${DEBUG_KERAS_BIN} --debug --ui_type=readline --use_random_config_path
+run -t 11
+EOF
+
+# Test offline_analyzer.
+echo
+echo "Testing offline_analyzer"
+echo
+
+# TODO(cais): Generate an actual debug dump and load it with offline_analyzer,
+# so that we can test the binary runs with a non-error exit code.
+set +e
+OUTPUT=$(${OFFLINE_ANALYZER_BIN} 2>&1)
+set -e
+
+EXPECTED_OUTPUT="ERROR: dump_dir flag is empty."
+if ! echo "${OUTPUT}" | grep -q "${EXPECTED_OUTPUT}"; then
+  echo "ERROR: offline_analyzer output didn't match expectation: ${OUTPUT}" 1>&2
+  echo "Expected output: ${EXPECTED_OUTPUT}"
+  exit 1
+fi
+
+echo
+echo "SUCCESS: tfdbg examples and binaries test PASSED"

tensorflow/python/debug/examples/v2/BUILD

@@ -0,0 +1,49 @@
+load("@rules_shell//shell:sh_test.bzl", "sh_test")
+load("@xla//third_party/rules_python/python:py_binary.bzl", "py_binary")
+
+package(
+    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
+    licenses = ["notice"],
+)
+
+py_binary(
+    name = "debug_fibonacci_v2",
+    srcs = ["debug_fibonacci_v2.py"],
+    strict_deps = True,
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+        "//third_party/py/numpy",
+        "@absl_py//absl:app",
+    ],
+)
+
+py_binary(
+    name = "debug_mnist_v2",
+    srcs = ["debug_mnist_v2.py"],
+    strict_deps = True,
+    deps = [
+        "//tensorflow:tensorflow_py",
+        "//tensorflow/python/debug:debug_py",
+        "//third_party/py/numpy",
+        "@absl_py//absl:app",
+    ],
+)
+
+sh_test(
+    name = "examples_v2_test",
+    size = "medium",
+    srcs = ["examples_v2_test.sh"],
+    data = [
+        ":debug_fibonacci_v2",
+        ":debug_mnist_v2",
+        "//tensorflow/python/debug/cli:offline_analyzer",
+    ],
+    tags = [
+        "no_windows",
+        "noasan",  # TODO(b/143150907)
+        "nomsan",  # TODO(b/143150907)
+        "requires-mem:16g",
+        "v2only",
+    ],
+)

tensorflow/python/debug/examples/v2/debug_fibonacci_v2.py

@@ -0,0 +1,86 @@
+# Copyright 2019 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.
+# ==============================================================================
+"""Demo of the tfdbg curses UI: A TF v2 network computing Fibonacci sequence."""
+import argparse
+import sys
+
+from absl import app
+import numpy as np
+import tensorflow.compat.v2 as tf
+
+FLAGS = None
+
+tf.compat.v1.enable_v2_behavior()
+
+
+def main(_):
+  # Wrap the TensorFlow Session object for debugging.
+  # TODO(anthonyjliu): Enable debugger from flags
+  if FLAGS.debug and FLAGS.tensorboard_debug_address:
+    raise ValueError(
+        "The --debug and --tensorboard_debug_address flags are mutually "
+        "exclusive.")
+  if FLAGS.debug:
+    raise NotImplementedError(
+        "tfdbg v2 support for debug_fibonacci is not implemented yet")
+  elif FLAGS.tensorboard_debug_address:
+    raise NotImplementedError(
+        "Tensorboard Debugger Plugin support for debug_fibonacci_v2 is not "
+        "implemented yet"
+    )
+
+  # Construct the TensorFlow network.
+  n0 = tf.constant(np.ones([FLAGS.tensor_size] * 2), dtype=tf.int32)
+  n1 = tf.constant(np.ones([FLAGS.tensor_size] * 2), dtype=tf.int32)
+
+  for _ in range(2, FLAGS.length):
+    n0, n1 = n1, tf.add(n0, n1)
+
+  print("Fibonacci number at position %d:\n%s" % (FLAGS.length, n1.numpy()))
+
+
+if __name__ == "__main__":
+  parser = argparse.ArgumentParser()
+  parser.register("type", "bool", lambda v: v.lower() == "true")
+  parser.add_argument(
+      "--tensor_size",
+      type=int,
+      default=1,
+      help="""\
+      Size of tensor. E.g., if the value is 30, the tensors will have shape
+      [30, 30].\
+      """)
+  parser.add_argument(
+      "--length",
+      type=int,
+      default=20,
+      help="Length of the fibonacci sequence to compute.")
+  parser.add_argument(
+      "--debug",
+      dest="debug",
+      action="store_true",
+      help="Use TensorFlow Debugger (tfdbg). Mutually exclusive with the "
+      "--tensorboard_debug_address flag.")
+  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.")
+
+  FLAGS, unparsed = parser.parse_known_args()
+
+  app.run(main=main, argv=[sys.argv[0]] + unparsed)

tensorflow/python/debug/examples/v2/debug_mnist_v2.py

@@ -0,0 +1,240 @@
+# Copyright 2019 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.
+# ==============================================================================
+"""Demo of the tfdbg curses CLI: Locating the source of bad numerical values with TF v2.
+
+This demo contains a classical example of a neural network for the mnist
+dataset, but modifications are made so that problematic numerical values (infs
+and nans) appear in nodes of the graph during training.
+"""
+import argparse
+import sys
+
+from absl import app
+import tensorflow.compat.v2 as tf
+
+IMAGE_SIZE = 28
+HIDDEN_SIZE = 500
+NUM_LABELS = 10
+
+# If we set the weights randomly, the model will converge normally about half
+# the time. We need a seed to ensure that the bad numerical values issue
+# appears.
+RAND_SEED = 42
+
+tf.compat.v1.enable_v2_behavior()
+
+FLAGS = None
+
+
+def parse_args():
+  """Parses commandline arguments.
+
+  Returns:
+    A tuple (parsed, unparsed) of the parsed object and a group of unparsed
+      arguments that did not match the parser.
+  """
+  parser = argparse.ArgumentParser()
+  parser.register("type", "bool", lambda v: v.lower() == "true")
+  parser.add_argument(
+      "--max_steps",
+      type=int,
+      default=10,
+      help="Number of steps to run trainer.")
+  parser.add_argument(
+      "--train_batch_size",
+      type=int,
+      default=100,
+      help="Batch size used during training.")
+  parser.add_argument(
+      "--learning_rate",
+      type=float,
+      default=0.025,
+      help="Initial learning rate.")
+  parser.add_argument(
+      "--data_dir",
+      type=str,
+      default="/tmp/mnist_data",
+      help="Directory for storing data")
+  parser.add_argument(
+      "--fake_data",
+      type="bool",
+      nargs="?",
+      const=True,
+      default=False,
+      help="Use fake MNIST data for unit testing")
+  parser.add_argument(
+      "--check_numerics",
+      type="bool",
+      nargs="?",
+      const=True,
+      default=False,
+      help="Use tfdbg to track down bad values during training. "
+      "Mutually exclusive with the --dump_dir flag.")
+  parser.add_argument(
+      "--dump_dir",
+      type=str,
+      default=None,
+      help="Dump TensorFlow program debug data to the specified directory. "
+      "The dumped data contains information regarding tf.function building, "
+      "execution of ops and tf.functions, as well as their stack traces and "
+      "associated source-code snapshots. "
+      "Mutually exclusive with the --check_numerics flag.")
+  parser.add_argument(
+      "--dump_tensor_debug_mode",
+      type=str,
+      default="FULL_HEALTH",
+      help="Mode for dumping tensor values. Options: NO_TENSOR, CURT_HEALTH, "
+      "CONCISE_HEALTH, SHAPE, FULL_HEALTH. This is relevant only when "
+      "--dump_dir is set.")
+  # TODO(cais): Add more tensor debug mode strings once they are supported.
+  parser.add_argument(
+      "--dump_circular_buffer_size",
+      type=int,
+      default=-1,
+      help="Size of the circular buffer used to dump execution events. "
+      "A value <= 0 disables the circular-buffer behavior and causes "
+      "all instrumented tensor values to be dumped. "
+      "This is relevant only when --dump_dir is set.")
+  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.""")
+  return parser.parse_known_args()
+
+
+def main(_):
+  if FLAGS.check_numerics and FLAGS.dump_dir:
+    raise ValueError(
+        "The --check_numerics and --dump_dir flags are mutually "
+        "exclusive.")
+  if FLAGS.check_numerics:
+    tf.debugging.enable_check_numerics()
+  elif FLAGS.dump_dir:
+    tf.debugging.experimental.enable_dump_debug_info(
+        FLAGS.dump_dir,
+        tensor_debug_mode=FLAGS.dump_tensor_debug_mode,
+        circular_buffer_size=FLAGS.dump_circular_buffer_size)
+
+  # Import data
+  if FLAGS.fake_data:
+    imgs = tf.random.uniform(maxval=256, shape=(1000, 28, 28), dtype=tf.int32)
+    labels = tf.random.uniform(maxval=10, shape=(1000,), dtype=tf.int32)
+    mnist_train = imgs, labels
+    mnist_test = imgs, labels
+  else:
+    mnist_train, mnist_test = tf.keras.datasets.mnist.load_data()
+
+  @tf.function
+  def format_example(imgs, labels):
+    """Formats each training and test example to work with our model."""
+    imgs = tf.reshape(imgs, [-1, 28 * 28])
+    imgs = tf.cast(imgs, tf.float32) / 255.0
+    labels = tf.one_hot(labels, depth=10, dtype=tf.float32)
+    return imgs, labels
+
+  train_ds = tf.data.Dataset.from_tensor_slices(mnist_train).shuffle(
+      FLAGS.train_batch_size * FLAGS.max_steps,
+      seed=RAND_SEED).batch(FLAGS.train_batch_size)
+  train_ds = train_ds.map(format_example)
+
+  test_ds = tf.data.Dataset.from_tensor_slices(mnist_test).repeat().batch(
+      len(mnist_test[0]))
+  test_ds = test_ds.map(format_example)
+
+  def get_dense_weights(input_dim, output_dim):
+    """Initializes the parameters for a single dense layer."""
+    initial_kernel = tf.keras.initializers.TruncatedNormal(
+        mean=0.0, stddev=0.1, seed=RAND_SEED)
+    kernel = tf.Variable(initial_kernel([input_dim, output_dim]))
+    bias = tf.Variable(tf.constant(0.1, shape=[output_dim]))
+
+    return kernel, bias
+
+  @tf.function
+  def dense_layer(weights, input_tensor, act=tf.nn.relu):
+    """Runs the forward computation for a single dense layer."""
+    kernel, bias = weights
+    preactivate = tf.matmul(input_tensor, kernel) + bias
+
+    activations = act(preactivate)
+    return activations
+
+  # init model
+  hidden_weights = get_dense_weights(IMAGE_SIZE**2, HIDDEN_SIZE)
+  output_weights = get_dense_weights(HIDDEN_SIZE, NUM_LABELS)
+  variables = hidden_weights + output_weights
+
+  @tf.function
+  def model(x):
+    """Feed forward function of the model.
+
+    Args:
+      x: a (?, 28*28) tensor consisting of the feature inputs for a batch of
+        examples.
+
+    Returns:
+      A (?, 10) tensor containing the class scores for each example.
+    """
+    hidden_act = dense_layer(hidden_weights, x)
+    logits_act = dense_layer(output_weights, hidden_act, tf.identity)
+    y = tf.nn.softmax(logits_act)
+    return y
+
+  @tf.function
+  def loss(probs, labels):
+    """Calculates cross entropy loss.
+
+    Args:
+      probs: Class probabilities predicted by the model. The shape is expected
+        to be (?, 10).
+      labels: Truth labels for the classes, as one-hot encoded vectors. The
+        shape is expected to be the same as `probs`.
+
+    Returns:
+      A scalar loss tensor.
+    """
+    diff = -labels * tf.math.log(probs)
+    loss = tf.reduce_mean(diff)
+    return loss
+
+  train_batches = iter(train_ds)
+  test_batches = iter(test_ds)
+  optimizer = tf.optimizers.Adam(learning_rate=FLAGS.learning_rate)
+  for i in range(FLAGS.max_steps):
+    x_train, y_train = next(train_batches)
+    x_test, y_test = next(test_batches)
+
+    # Train Step
+    with tf.GradientTape() as tape:
+      y = model(x_train)
+      loss_val = loss(y, y_train)
+    grads = tape.gradient(loss_val, variables)
+
+    optimizer.apply_gradients(zip(grads, variables))
+
+    # Evaluation Step
+    y = model(x_test)
+    correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_test, 1))
+    accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+    print("Accuracy at step %d: %s" % (i, accuracy.numpy()))
+
+
+if __name__ == "__main__":
+  FLAGS, unparsed = parse_args()
+  app.run(main=main, argv=[sys.argv[0]] + unparsed)

tensorflow/python/debug/examples/v2/examples_v2_test.sh

@@ -0,0 +1,91 @@
+#!/bin/bash
+# Copyright 2019 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.
+# ==============================================================================
+#
+# Bash unit tests for TensorFlow Debugger (tfdbg) Python examples that do not
+# involve downloading data. Also tests the binary offline_analyzer.
+#
+# Command-line flags:
+#   --virtualenv: (optional) If set, will test the examples and binaries
+#     against pip install of TensorFlow in a virtualenv.
+
+set -e
+
+# Filter out LOG(INFO)
+export TF_CPP_MIN_LOG_LEVEL=1
+
+IS_VIRTUALENV=0
+PYTHON_BIN_PATH=""
+while true; do
+  if [[ -z "$1" ]]; then
+    break
+  elif [[ "$1" == "--virtualenv" ]]; then
+    IS_VIRTUALENV=1
+    PYTHON_BIN_PATH=$(which python)
+    echo
+    echo "IS_VIRTUALENV = ${IS_VIRTUALENV}"
+    echo "PYTHON_BIN_PATH = ${PYTHON_BIN_PATH}"
+    echo "Will test tfdbg examples and binaries against virtualenv pip install."
+    echo
+  fi
+  shift 1
+done
+
+if [[ -z "${PYTHON_BIN_PATH}" ]]; then
+  DEBUG_FIBONACCI_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v2/debug_fibonacci_v2"
+  DEBUG_MNIST_BIN="$TEST_SRCDIR/org_tensorflow/tensorflow/python/debug/examples/v2/debug_mnist_v2"
+else
+  DEBUG_FIBONACCI_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v2.debug_fibonacci"
+  DEBUG_MNIST_BIN="${PYTHON_BIN_PATH} -m tensorflow.python.debug.examples.v2.debug_mnist"
+fi
+
+# Verify fibonacci runs normally without additional flags
+${DEBUG_FIBONACCI_BIN} --tensor_size=2
+
+# Verify mnist runs normally without additional flags
+${DEBUG_MNIST_BIN} --max_steps=4 --fake_data
+
+# Verify mnist does not break with check_numerics enabled on first iteration
+# check_numerics should not cause non-zero exit code on a single train step
+${DEBUG_MNIST_BIN} --max_steps=1 --fake_data --check_numerics
+
+# Verify check_numerics exits with non-zero exit code
+! ${DEBUG_MNIST_BIN} --max_steps=4 --fake_data --check_numerics
+
+# Verify that dumping works properly.
+TMP_DIR="$(mktemp -d)"
+${DEBUG_MNIST_BIN} --max_steps=4 --fake_data --dump_dir="${TMP_DIR}"
+
+# Check that the .execution and .graph_execution_traces are not empty,
+# i.e., the content of the circular buffer have been written to the disk.
+EXECUTION_FILE="$(ls ${TMP_DIR}/*.execution)"
+EXECUTION_FILE_SIZE=$(du -b "${EXECUTION_FILE}" | awk '{print $1}')
+echo "Size of ${EXECUTION_FILE}: ${EXECUTION_FILE_SIZE}"
+if [[ "${EXECUTION_FILE_SIZE}" == "0" ]]; then
+  echo "ERROR: ${EXECUTION_FILE} is unexpectedly empty."
+  exit 1
+fi
+
+GRAPH_TRACES_FILE="$(ls ${TMP_DIR}/*.graph_execution_traces)"
+GRAPH_TRACES_FILE_SIZE=$(du -b "${EXECUTION_FILE}" | awk '{print $1}')
+echo "Size of ${GRAPH_TRACES_FILE}: ${GRAPH_TRACES_FILE_SIZE}"
+if [[ "${GRAPH_TRACES_FILE_SIZE}" == "0" ]]; then
+  echo "ERROR: ${GRAPH_TRACES_FILE} is unexpectedly empty."
+  exit 1
+fi
+
+rm -rf "${TMP_DIR}"
+
+echo "SUCCESS: tfdbg examples and binaries test PASSED"