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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 CLI as SessionRunHook."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.core.protobuf import config_pb2
from tensorflow.python.debug.lib import debug_utils
from tensorflow.python.debug.lib import stepper
from tensorflow.python.debug.wrappers import dumping_wrapper
from tensorflow.python.debug.wrappers import framework
from tensorflow.python.debug.wrappers import local_cli_wrapper
from tensorflow.python.training import session_run_hook
class LocalCLIDebugHook(session_run_hook.SessionRunHook,
local_cli_wrapper.LocalCLIDebugWrapperSession):
"""Command-line-interface debugger hook.
Can be used as a monitor/hook for `tf.train.MonitoredSession`s and
`tf.contrib.learn`'s `Estimator`s and `Experiment`s.
"""
def __init__(self, ui_type="curses"):
"""Create a local debugger command-line interface (CLI) hook.
Args:
ui_type: (str) user-interface type.
"""
self._ui_type = ui_type
self._wrapper_initialized = False
self._pending_tensor_filters = {}
def add_tensor_filter(self, filter_name, tensor_filter):
"""Add a tensor filter.
See doc of `LocalCLIDebugWrapperSession.add_tensor_filter()` for details.
Override default behavior to accomodate the possibility of this method being
called prior to the initialization of the underlying
`LocalCLIDebugWrapperSession` object.
Args:
filter_name: See doc of `LocalCLIDebugWrapperSession.add_tensor_filter()`
for details.
tensor_filter: See doc of
`LocalCLIDebugWrapperSession.add_tensor_filter()` for details.
"""
if self._wrapper_initialized:
local_cli_wrapper.LocalCLIDebugWrapperSession.add_tensor_filter(
self, filter_name, tensor_filter)
else:
self._pending_tensor_filters[filter_name] = tensor_filter
def begin(self):
pass
def before_run(self, run_context):
if not self._wrapper_initialized:
local_cli_wrapper.LocalCLIDebugWrapperSession.__init__(
self, run_context.session, ui_type=self._ui_type)
# Actually register tensor filters registered prior to the construction
# of the underlying LocalCLIDebugWrapperSession object.
for filter_name in self._pending_tensor_filters:
local_cli_wrapper.LocalCLIDebugWrapperSession.add_tensor_filter(
self, filter_name, self._pending_tensor_filters[filter_name])
self._wrapper_initialized = True
# Increment run call counter.
self._run_call_count += 1
# Adapt run_context to an instance of OnRunStartRequest for invoking
# superclass on_run_start().
on_run_start_request = framework.OnRunStartRequest(
run_context.original_args.fetches, run_context.original_args.feed_dict,
None, None, self._run_call_count)
on_run_start_response = self.on_run_start(on_run_start_request)
self._performed_action = on_run_start_response.action
run_args = session_run_hook.SessionRunArgs(
None, feed_dict=None, options=config_pb2.RunOptions())
if self._performed_action == framework.OnRunStartAction.DEBUG_RUN:
self._decorate_options_for_debug(run_args.options,
run_context.session.graph)
elif self._performed_action == framework.OnRunStartAction.INVOKE_STEPPER:
# The _finalized property must be set to False so that the NodeStepper
# can insert ops for retrieving TensorHandles.
# pylint: disable=protected-access
run_context.session.graph._finalized = False
# pylint: enable=protected-access
with stepper.NodeStepper(
run_context.session,
run_context.original_args.
fetches,
run_context.original_args.feed_dict) as node_stepper:
self.invoke_node_stepper(
node_stepper, restore_variable_values_on_exit=True)
return run_args
def after_run(self, run_context, run_values):
# Adapt run_context and run_values to OnRunEndRequest and invoke superclass
# on_run_end()
on_run_end_request = framework.OnRunEndRequest(self._performed_action,
run_values.run_metadata)
self.on_run_end(on_run_end_request)
def _decorate_options_for_debug(self, options, graph):
"""Modify RunOptions.debug_options.debug_tensor_watch_opts for debugging.
Args:
options: (config_pb2.RunOptions) The RunOptions instance to be modified.
graph: A TensorFlow Graph object.
"""
debug_utils.watch_graph(
options, graph, debug_urls=self._get_run_debug_urls())
options.output_partition_graphs = True
class DumpingDebugHook(session_run_hook.SessionRunHook,
dumping_wrapper.DumpingDebugWrapperSession):
"""A debugger hook that dumps debug data to filesystem.
Can be used as a monitor/hook for `tf.train.MonitoredSession`s and
`tf.contrib.learn`'s `Estimator`s and `Experiment`s.
"""
def __init__(self, session_root, watch_fn=None, log_usage=True):
"""Create a local debugger command-line interface (CLI) hook.
Args:
session_root: See doc of
`dumping_wrapper.DumpingDebugWrapperSession.__init__`.
watch_fn: See doc of
`dumping_wrapper.DumpingDebugWrapperSession.__init__`.
log_usage: (bool) Whether usage is to be logged.
"""
self._session_root = session_root
self._watch_fn = watch_fn
self._log_usage = log_usage
self._wrapper_initialized = False
def begin(self):
pass
def before_run(self, run_context):
if not self._wrapper_initialized:
dumping_wrapper.DumpingDebugWrapperSession.__init__(
self,
run_context.session,
self._session_root,
watch_fn=self._watch_fn,
log_usage=self._log_usage)
self._wrapper_initialized = True
self._run_call_count += 1
(debug_urls, debug_ops, node_name_regex_whitelist,
op_type_regex_whitelist) = self._prepare_run_watch_config(
run_context.original_args.fetches, run_context.original_args.feed_dict)
run_options = config_pb2.RunOptions()
debug_utils.watch_graph(
run_options,
run_context.session.graph,
debug_urls=debug_urls,
debug_ops=debug_ops,
node_name_regex_whitelist=node_name_regex_whitelist,
op_type_regex_whitelist=op_type_regex_whitelist)
run_args = session_run_hook.SessionRunArgs(
None, feed_dict=None, options=run_options)
return run_args
def after_run(self, run_context, run_values):
pass
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