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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.
# ==============================================================================
"""TensorFlow Debugger (tfdbg) Utilities."""
import re
def add_debug_tensor_watch(run_options,
node_name,
output_slot=0,
debug_ops="DebugIdentity",
debug_urls=None,
tolerate_debug_op_creation_failures=False,
global_step=-1):
"""Add watch on a `Tensor` to `RunOptions`.
N.B.:
1. Under certain circumstances, the `Tensor` may not get actually watched
(e.g., if the node of the `Tensor` is constant-folded during runtime).
2. For debugging purposes, the `parallel_iteration` attribute of all
`tf.while_loop`s in the graph are set to 1 to prevent any node from
being executed multiple times concurrently. This change does not affect
subsequent non-debugged runs of the same `tf.while_loop`s.
Args:
run_options: An instance of `config_pb2.RunOptions` to be modified.
node_name: (`str`) name of the node to watch.
output_slot: (`int`) output slot index of the tensor from the watched node.
debug_ops: (`str` or `list` of `str`) name(s) of the debug op(s). Can be a
`list` of `str` or a single `str`. The latter case is equivalent to a
`list` of `str` with only one element.
For debug op types with customizable attributes, each debug op string can
optionally contain a list of attribute names, in the syntax of:
debug_op_name(attr_name_1=attr_value_1;attr_name_2=attr_value_2;...)
debug_urls: (`str` or `list` of `str`) URL(s) to send debug values to,
e.g., `file:///tmp/tfdbg_dump_1`, `grpc://localhost:12345`.
tolerate_debug_op_creation_failures: (`bool`) Whether to tolerate debug op
creation failures by not throwing exceptions.
global_step: (`int`) Optional global_step count for this debug tensor
watch.
"""
watch_opts = run_options.debug_options.debug_tensor_watch_opts
run_options.debug_options.global_step = global_step
watch = watch_opts.add()
watch.tolerate_debug_op_creation_failures = (
tolerate_debug_op_creation_failures)
watch.node_name = node_name
watch.output_slot = output_slot
if isinstance(debug_ops, str):
debug_ops = [debug_ops]
watch.debug_ops.extend(debug_ops)
if debug_urls:
if isinstance(debug_urls, str):
debug_urls = [debug_urls]
watch.debug_urls.extend(debug_urls)
def watch_graph(run_options,
graph,
debug_ops="DebugIdentity",
debug_urls=None,
node_name_regex_allowlist=None,
op_type_regex_allowlist=None,
tensor_dtype_regex_allowlist=None,
tolerate_debug_op_creation_failures=False,
global_step=-1,
reset_disk_byte_usage=False):
"""Add debug watches to `RunOptions` for a TensorFlow graph.
To watch all `Tensor`s on the graph, let both `node_name_regex_allowlist`
and `op_type_regex_allowlist` be the default (`None`).
N.B.:
1. Under certain circumstances, the `Tensor` may not get actually watched
(e.g., if the node of the `Tensor` is constant-folded during runtime).
2. For debugging purposes, the `parallel_iteration` attribute of all
`tf.while_loop`s in the graph are set to 1 to prevent any node from
being executed multiple times concurrently. This change does not affect
subsequent non-debugged runs of the same `tf.while_loop`s.
Args:
run_options: An instance of `config_pb2.RunOptions` to be modified.
graph: An instance of `ops.Graph`.
debug_ops: (`str` or `list` of `str`) name(s) of the debug op(s) to use.
debug_urls: URLs to send debug values to. Can be a list of strings,
a single string, or None. The case of a single string is equivalent to
a list consisting of a single string, e.g., `file:///tmp/tfdbg_dump_1`,
`grpc://localhost:12345`.
For debug op types with customizable attributes, each debug op name string
can optionally contain a list of attribute names, in the syntax of:
debug_op_name(attr_name_1=attr_value_1;attr_name_2=attr_value_2;...)
node_name_regex_allowlist: Regular-expression allowlist for node_name,
e.g., `"(weight_[0-9]+|bias_.*)"`
op_type_regex_allowlist: Regular-expression allowlist for the op type of
nodes, e.g., `"(Variable|Add)"`.
If both `node_name_regex_allowlist` and `op_type_regex_allowlist`
are set, the two filtering operations will occur in a logical `AND`
relation. In other words, a node will be included if and only if it
hits both allowlists.
tensor_dtype_regex_allowlist: Regular-expression allowlist for Tensor
data type, e.g., `"^int.*"`.
This allowlist operates in logical `AND` relations to the two allowlists
above.
tolerate_debug_op_creation_failures: (`bool`) whether debug op creation
failures (e.g., due to dtype incompatibility) are to be tolerated by not
throwing exceptions.
global_step: (`int`) Optional global_step count for this debug tensor
watch.
reset_disk_byte_usage: (`bool`) whether to reset the tracked disk byte
usage to zero (default: `False`).
"""
if not debug_ops:
raise ValueError("debug_ops must not be empty or None.")
if not debug_urls:
raise ValueError("debug_urls must not be empty or None.")
if isinstance(debug_ops, str):
debug_ops = [debug_ops]
node_name_pattern = (
re.compile(node_name_regex_allowlist)
if node_name_regex_allowlist else None)
op_type_pattern = (
re.compile(op_type_regex_allowlist) if op_type_regex_allowlist else None)
tensor_dtype_pattern = (
re.compile(tensor_dtype_regex_allowlist)
if tensor_dtype_regex_allowlist else None)
ops = graph.get_operations()
for op in ops:
# Skip nodes without any output tensors.
if not op.outputs:
continue
node_name = op.name
op_type = op.type
if node_name_pattern and not node_name_pattern.match(node_name):
continue
if op_type_pattern and not op_type_pattern.match(op_type):
continue
for slot in range(len(op.outputs)):
if (tensor_dtype_pattern and
not tensor_dtype_pattern.match(op.outputs[slot].dtype.name)):
continue
add_debug_tensor_watch(
run_options,
node_name,
output_slot=slot,
debug_ops=debug_ops,
debug_urls=debug_urls,
tolerate_debug_op_creation_failures=(
tolerate_debug_op_creation_failures),
global_step=global_step)
# If no filter for node or tensor is used, will add a wildcard node name, so
# that all nodes, including the ones created internally by TensorFlow itself
# (e.g., by Grappler), can be watched during debugging.
use_node_name_wildcard = (not node_name_pattern and
not op_type_pattern and
not tensor_dtype_pattern)
if use_node_name_wildcard:
add_debug_tensor_watch(
run_options,
"*",
output_slot=-1,
debug_ops=debug_ops,
debug_urls=debug_urls,
tolerate_debug_op_creation_failures=tolerate_debug_op_creation_failures,
global_step=global_step)
run_options.debug_options.reset_disk_byte_usage = reset_disk_byte_usage
def watch_graph_with_denylists(run_options,
graph,
debug_ops="DebugIdentity",
debug_urls=None,
node_name_regex_denylist=None,
op_type_regex_denylist=None,
tensor_dtype_regex_denylist=None,
tolerate_debug_op_creation_failures=False,
global_step=-1,
reset_disk_byte_usage=False):
"""Add debug tensor watches, denylisting nodes and op types.
This is similar to `watch_graph()`, but the node names and op types are
denylisted, instead of allowlisted.
N.B.:
1. Under certain circumstances, the `Tensor` may not get actually watched
(e.g., if the node of the `Tensor` is constant-folded during runtime).
2. For debugging purposes, the `parallel_iteration` attribute of all
`tf.while_loop`s in the graph are set to 1 to prevent any node from
being executed multiple times concurrently. This change does not affect
subsequent non-debugged runs of the same `tf.while_loop`s.
Args:
run_options: An instance of `config_pb2.RunOptions` to be modified.
graph: An instance of `ops.Graph`.
debug_ops: (`str` or `list` of `str`) name(s) of the debug op(s) to use. See
the documentation of `watch_graph` for more details.
debug_urls: URL(s) to send debug values to, e.g.,
`file:///tmp/tfdbg_dump_1`, `grpc://localhost:12345`.
node_name_regex_denylist: Regular-expression denylist for node_name. This
should be a string, e.g., `"(weight_[0-9]+|bias_.*)"`.
op_type_regex_denylist: Regular-expression denylist for the op type of
nodes, e.g., `"(Variable|Add)"`. If both node_name_regex_denylist and
op_type_regex_denylist are set, the two filtering operations will occur in
a logical `OR` relation. In other words, a node will be excluded if it
hits either of the two denylists; a node will be included if and only if
it hits neither of the denylists.
tensor_dtype_regex_denylist: Regular-expression denylist for Tensor data
type, e.g., `"^int.*"`. This denylist operates in logical `OR` relations
to the two allowlists above.
tolerate_debug_op_creation_failures: (`bool`) whether debug op creation
failures (e.g., due to dtype incompatibility) are to be tolerated by not
throwing exceptions.
global_step: (`int`) Optional global_step count for this debug tensor watch.
reset_disk_byte_usage: (`bool`) whether to reset the tracked disk byte
usage to zero (default: `False`).
"""
if isinstance(debug_ops, str):
debug_ops = [debug_ops]
node_name_pattern = (
re.compile(node_name_regex_denylist)
if node_name_regex_denylist else None)
op_type_pattern = (
re.compile(op_type_regex_denylist) if op_type_regex_denylist else None)
tensor_dtype_pattern = (
re.compile(tensor_dtype_regex_denylist)
if tensor_dtype_regex_denylist else None)
ops = graph.get_operations()
for op in ops:
# Skip nodes without any output tensors.
if not op.outputs:
continue
node_name = op.name
op_type = op.type
if node_name_pattern and node_name_pattern.match(node_name):
continue
if op_type_pattern and op_type_pattern.match(op_type):
continue
for slot in range(len(op.outputs)):
if (tensor_dtype_pattern and
tensor_dtype_pattern.match(op.outputs[slot].dtype.name)):
continue
add_debug_tensor_watch(
run_options,
node_name,
output_slot=slot,
debug_ops=debug_ops,
debug_urls=debug_urls,
tolerate_debug_op_creation_failures=(
tolerate_debug_op_creation_failures),
global_step=global_step)
run_options.debug_options.reset_disk_byte_usage = reset_disk_byte_usage