337 lines
12 KiB
Python
337 lines
12 KiB
Python
# Copyright 2016 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""A Context that captures profile and performs profiling/dumping.
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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import contextlib
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import os
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import random
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import sys
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import threading
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from tensorflow.core.protobuf import config_pb2
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from tensorflow.python import pywrap_tensorflow as print_mdl
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from tensorflow.python.client import session
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from tensorflow.python.framework import errors
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from tensorflow.python.framework import ops
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from tensorflow.python.platform import gfile
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from tensorflow.python.profiler import model_analyzer
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from tensorflow.python.util import compat
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WARMUP_STEPS = 10
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MAX_TRACED_STEPS = 100
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def _profiled_init(self, target='', graph=None, config=None):
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"""Overwrites the session.__init__."""
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self._profiler_init_internal(target, graph, config) # pylint: disable=protected-access
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def _profiled_run(self,
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fetches,
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feed_dict=None,
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options=None,
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run_metadata=None):
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"""Overwrites the session.run()."""
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# pylint: disable=protected-access
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# Count the session steps.
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with self.profile_context._new_step() as state:
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step, locked = state
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# Fast path if no need for profiling.
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if locked and not self.profile_context._is_fast_path(step):
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# Maybe trace this step.
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if self.profile_context._should_trace(step, self.graph, fetches):
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if self.profile_context._debug:
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sys.stderr.write('debug: tracing step: %d\n' % step)
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# Enable tracing, perform auto profiling or auto dump.
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if not run_metadata:
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run_metadata = config_pb2.RunMetadata()
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if not options:
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options = config_pb2.RunOptions(
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trace_level=config_pb2.RunOptions.FULL_TRACE)
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old_trace_level = options.trace_level
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else:
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old_trace_level = options.trace_level
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options.trace_level = config_pb2.RunOptions.FULL_TRACE
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ret = self._profiler_run_internal(
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fetches, feed_dict, options, run_metadata)
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if self.profile_context._debug:
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self.profile_context._dump_file(run_metadata, 'run_meta_%d' % step)
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self.profile_context.profiler._graph = self.graph
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self.profile_context.profiler.add_step(step, run_metadata)
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options.trace_level = old_trace_level
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else:
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ret = self._profiler_run_internal(fetches, feed_dict, options)
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# Maybe dump profile.
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self.profile_context._maybe_dump(step)
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# Maybe profile:
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to_profiles = self.profile_context._profile_candidates()
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for to_prof in to_profiles:
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cmd, opts, _ = to_prof
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if self.profile_context._debug:
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sys.stderr.write('debug: profiling %s step: %d\n' % (cmd, step))
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if cmd == 'graph':
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self.profile_context.profiler.profile_graph(opts)
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elif cmd == 'scope':
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self.profile_context.profiler.profile_name_scope(opts)
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elif cmd == 'op':
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self.profile_context.profiler.profile_operations(opts)
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elif cmd == 'code':
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self.profile_context.profiler.profile_python(opts)
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else:
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raise ValueError('Unknown cmd: %s\n' % cmd)
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return ret
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# Fast no lock path.
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return self._profiler_run_internal(
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fetches, feed_dict, options, run_metadata)
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# pylint: enable=protected-access
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class ProfileContext(object):
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"""A Context that captures RunMetadata and performs profiling.
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```python
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# Trace steps 100~200, profile at [150, 200] and dump profile at 200.
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with tf.contrib.tfprof.ProfileContext('/tmp/train_dir',
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trace_steps=range(100, 200, 3),
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dump_steps=[200]) as pctx:
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opts = tf.profiler.ProfileOptionBuilder.time_and_memory()
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pctx.add_auto_profiling('op', opts, [150, 200])
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train_loop().
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# Tracing only.
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with tf.contrib.tfprof.ProfileContext('/tmp/train_dir') as pctx:
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# Run train/eval loop for at least few hundred steps. Profiles will be
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# dumped to train_dir. Use web UI or command line to do profiling.
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train_loop().
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# When session object is available, do explicit trace, profile and dump.
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with tf.contrib.tfprof.ProfileContext('/tmp/train_dir',
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trace_steps=[],
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dump_steps=[]) as pctx:
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opts = tf.profiler.ProfileOptionBuilder.time_and_memory()
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pctx.trace_next_step()
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_ = session.run(train_op)
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pctx.profiler.profile_operations(options=opts)
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```
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Args:
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profile_dir: Directory to store profiles.
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trace_steps: A list of session run steps to trace. If None, use
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pre-defined steps.
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dump_steps: A list of steps to dump the profile to `profile_dir`. If None,
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use pre-defined steps.
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enabled: If false, everything is disabled with minimal overhead. It allows
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user to only enable profiling when needed.
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debug: If true, also dumps the raw trace RunMetadata text file to
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profile_dir. And print debugging message. Useful for bug report.
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"""
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def __init__(self,
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profile_dir,
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trace_steps=None,
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dump_steps=None,
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enabled=True,
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debug=False):
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self._enabled = enabled
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if not self._enabled:
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return
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self._debug = debug
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if not profile_dir:
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raise ValueError('Must have a directory for profile.\n')
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self._profiler_dir = profile_dir
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if trace_steps is None:
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self._trace_steps = set()
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self._auto_tracing = True
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else:
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if len(trace_steps) > MAX_TRACED_STEPS:
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raise ValueError('Only support tracing up to 100 steps.\n')
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self._trace_steps = set(trace_steps[:])
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self._auto_tracing = False
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if dump_steps is None:
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self._dump_steps = set([MAX_TRACED_STEPS])
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else:
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self._dump_steps = set(dump_steps[:])
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self._rng = random.Random(111)
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self._fetched = set()
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self._slow_path_steps = self._dump_steps | self._trace_steps
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self._trace_next_step = False
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self._dump_next_step = False
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self._step = 0
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self._traced_steps = 0
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self._auto_profiles = []
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self._profiler = None
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self._lock = threading.Lock()
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def add_auto_profiling(self, cmd, options, profile_steps):
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"""Traces and profiles at some session run steps.
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Args:
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cmd: The profiling commands. (i.e. scope, op, python, graph)
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options: The profiling options.
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profile_steps: A list/set of integers. The profiling command and options
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will be run automatically at these integer steps. Each step is
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a session.run.
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"""
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if not self._enabled:
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return
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self._auto_profiles.append((cmd, options, profile_steps[:]))
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self._slow_path_steps |= set(profile_steps)
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self._trace_steps |= set(profile_steps)
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@property
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def profiler(self):
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"""Returns the current profiler object."""
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if not self._enabled:
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return None
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if not self._profiler:
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self._profiler = model_analyzer.Profiler(ops.get_default_graph())
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return self._profiler
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def trace_next_step(self):
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"""Enables tracing and adds traces to profiler at next step."""
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if not self._enabled:
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return
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self._trace_next_step = True
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self._slow_path_steps.add(self._step)
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def dump_next_step(self):
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"""Enable tracing and dump profiles at next step."""
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if not self._enabled:
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return
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self._dump_next_step = True
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self._slow_path_steps.add(self._step)
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def _is_fast_path(self, step):
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if step in self._slow_path_steps:
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return False
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# When user doesn't set the tracing steps explicitly, auto decide it.
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if (self._auto_tracing and step > WARMUP_STEPS and
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self._traced_steps <= MAX_TRACED_STEPS):
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return False
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return True
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def _should_trace(self, step, graph, fetches):
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"""Whether should do tracing at current step."""
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if self._traced_steps > MAX_TRACED_STEPS:
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return False
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# Check user-set tracing steps.
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if step in self._trace_steps or self._trace_next_step:
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self._traced_steps += 1
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return True
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# If no user-set tracing steps set and passes warm up steps, auto trace.
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if self._auto_tracing and step > WARMUP_STEPS:
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# If the fetches have not been seen before, trace it.
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with graph.as_default():
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fetch_names = [f.name for f in
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session._FetchMapper.for_fetch(fetches).unique_fetches()] # pylint: disable=protected-access
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fetch_name = '-'.join(sorted(fetch_names))
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if self._debug:
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sys.stderr.write('debug: trace fetches: %s\n' % fetch_name)
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if fetch_name not in self._fetched:
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self._fetched.add(fetch_name)
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self._traced_steps += 1
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return True
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# If the trace coverage is low, does some random tracing.
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if (self.profiler._coverage < 0.5 and step < MAX_TRACED_STEPS and # pylint: disable=protected-access
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self._rng.randint(0, 10) < 2):
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self._traced_steps += 1
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return True
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return False
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def _maybe_dump(self, step):
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"""Maybe dump the profile file."""
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if not (step in self._dump_steps or self._dump_next_step):
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return
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if self._debug:
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sys.stderr.write('debug: dumping file at step: %d\n' % step)
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if not gfile.Exists(self._profiler_dir):
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gfile.MakeDirs(self._profiler_dir)
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filename = os.path.join(compat.as_bytes(self._profiler_dir),
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compat.as_bytes('profile_%d' % step))
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self.profiler._write_profile(filename) # pylint: disable=protected-access
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def _dump_file(self, pb, basename):
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if not gfile.Exists(self._profiler_dir):
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gfile.MakeDirs(self._profiler_dir)
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with gfile.Open(os.path.join(self._profiler_dir, basename), 'w') as f:
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f.write('%s' % pb)
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@contextlib.contextmanager
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def _new_step(self):
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acquired = self._lock.acquire(False)
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yield (self._step, acquired)
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self._step += 1
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self._trace_next_step = False
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self._dump_next_step = False
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if acquired:
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self._lock.release()
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def _profile_candidates(self):
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to_profile = []
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for auto_prof in self._auto_profiles:
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_, _, prof_steps = auto_prof
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if self._step in prof_steps:
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to_profile.append(auto_prof)
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return to_profile
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def __enter__(self):
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if self._enabled:
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self.old_run = getattr(session.BaseSession, 'run', None)
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self.old_init = getattr(session.BaseSession, '__init__', None)
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if not self.old_run:
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raise errors.InternalError(None, None, 'BaseSession misses run method.')
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elif not self.old_init:
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raise errors.InternalError(None, None,
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'BaseSession misses __init__ method.')
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elif getattr(session.BaseSession, '_profiler_run_internal', None):
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raise errors.InternalError(None, None,
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'Already in context or context not cleaned.')
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elif getattr(session.BaseSession, '_profiler_init_internal', None):
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raise errors.InternalError(None, None,
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'Already in context or context not cleaned.')
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else:
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setattr(session.BaseSession, 'run', _profiled_run)
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setattr(session.BaseSession, '__init__', _profiled_init)
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setattr(session.BaseSession, '_profiler_run_internal', self.old_run)
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setattr(session.BaseSession, '_profiler_init_internal', self.old_init)
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setattr(session.BaseSession, 'profile_context', self)
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return self
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else:
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return self
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def __exit__(self, exec_type, exec_value, exec_tb):
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if not self._enabled:
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return
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print_mdl.DeleteProfiler()
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setattr(session.BaseSession, 'run', self.old_run)
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setattr(session.BaseSession, '__init__', self.old_init)
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setattr(session.BaseSession, '_profiler_run_internal', None)
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setattr(session.BaseSession, '_profiler_init_internal', None)
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setattr(session.BaseSession, 'profile_context', None)
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