| /external/tensorflow/tensorflow/contrib/tfprof/ |
| tfprof_logger.py | 28 def write_op_log(graph, log_dir, op_log=None, run_meta=None, add_trace=True):
29 _write_op_log(graph, log_dir, op_log, run_meta, add_trace)
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| model_analyzer.py | 104 'Use `tf.profiler.advise(graph, run_meta, options)`. See README.md')
105 def advise(graph, run_meta=None, tfprof_options=_DEFAULT_ADVISE_OPTIONS):
106 return _advise(graph, run_meta, tfprof_options)
110 'Use `tf.profiler.profile(graph, run_meta, op_log, cmd, options)`. '
114 run_meta=None,
118 return _profile(graph, run_meta, op_log, tfprof_cmd, tfprof_options)
|
| /external/tensorflow/tensorflow/core/profiler/internal/ |
| print_model_analysis.h | 38 double AddStep(int64 step, const string* graph, const string* run_meta,
55 // 'graph', 'run_meta', 'op_log' are serialized GraphDef, RunMetadata,
59 string PrintModelAnalysis(const string* graph, const string* run_meta,
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| print_model_analysis.cc | 123 double AddStep(int64 step, const string* graph, const string* run_meta,
137 CHECK(run_meta && !run_meta->empty());
140 run_meta_ptr->ParseFromString(*run_meta);
172 string PrintModelAnalysis(const string* graph, const string* run_meta,
183 if (run_meta && !run_meta->empty()) {
185 run_meta_ptr->ParseFromString(*run_meta);
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| tfprof_stats.h | 55 std::unique_ptr<RunMetadata> run_meta,
90 void AddRunMeta(int64 step, std::unique_ptr<RunMetadata> run_meta);
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| tfprof_stats.cc | 50 std::unique_ptr<RunMetadata> run_meta,
60 if (run_meta && run_meta->has_step_stats()) {
61 AddRunMeta(0, std::move(run_meta));
263 void TFStats::AddRunMeta(int64 step, std::unique_ptr<RunMetadata> run_meta) {
264 if (!run_meta || !run_meta->has_step_stats()) {
276 for (const auto& dev_stat : run_meta->step_stats().dev_stats()) {
|
| /external/tensorflow/tensorflow/python/profiler/internal/ |
| run_metadata_test.py | 43 def _extract_node(run_meta, node_name):
45 for dev_stat in run_meta.step_stats.dev_stats:
81 run_meta=run_metadata,
92 run_meta = config_pb2.RunMetadata()
96 run_metadata=run_meta)
103 sess.graph, run_meta, options=opts)
104 return tfprof_node, run_meta
116 tfprof_node, run_meta = _run_model()
120 ret = _extract_node(run_meta, 'MatMul')
122 self.assertEqual(len(ret['gpu:0/stream:all']), 1, '%s' % run_meta)
[all...] |
| /external/tensorflow/tensorflow/cc/profiler/ |
| profiler.h | 43 /// RunMetadata run_meta;
45 /// &run_meta);
52 /// profiler.AddStep(0, run_meta);
61 /// Adds tracing information `run_meta` to profiler. A `run_meta` is
63 /// to the `run_meta`. When calling ProfileXXX methods, caller can specify
64 /// `step` in `options` to seletively profile the corresponding `run_meta`.
65 /// Multiple different `run_meta` can be keyed by the same `step` in order
67 void AddStep(int64 step, const RunMetadata& run_meta);
|
| profiler.cc | 26 void Profiler::AddStep(int64 step, const RunMetadata& run_meta) {
28 *run_meta_ptr = run_meta;
|
| /external/tensorflow/tensorflow/python/profiler/ |
| profiler_test.py | 47 # Test the output without run_meta.
52 # Test the output with run_meta.
53 run_meta = config_pb2.RunMetadata()
57 run_metadata=run_meta)
60 profiler.add_step(1, run_meta)
66 sess.graph, cmd='graph', run_meta=run_meta, options=opts)
76 sess.graph, cmd='scope', run_meta=run_meta, options=opts)
86 sess.graph, cmd='code', run_meta=run_meta, options=opts
[all...] |
| tfprof_logger.py | 39 def _fill_missing_graph_shape(graph, run_meta):
40 """Fill Tensor shapes in 'graph' with run time shape from 'run_meta'."""
41 for dev_stat in run_meta.step_stats.dev_stats:
77 def _get_logged_ops(graph, run_meta=None, add_trace=True,
83 run_meta: RunMetadata proto used to complete shape information.
91 if run_meta:
92 graph = _fill_missing_graph_shape(graph, run_meta)
138 if op_missing_shape > 0 and not run_meta:
144 def merge_default_with_oplog(graph, op_log=None, run_meta=None,
152 run_meta: RunMetadata proto used to complete shape information
[all...] |
| model_analyzer.py | 138 run_meta = tf.RunMetadata()
142 run_metadata=run_meta)
143 profiler.add_step(i, run_meta)
189 def add_step(self, step, run_meta):
193 step: int, An id used to group one or more different `run_meta` together.
195 id in the `options` to profile these `run_meta` together.
196 run_meta: RunMetadata proto that contains statistics of a session run.
200 self._graph, run_meta=run_meta)
204 run_meta.SerializeToString()
[all...] |
| model_analyzer_test.py | 160 run_meta = config_pb2.RunMetadata()
164 run_metadata=run_meta)
167 sess.graph, run_meta, options=opts)
186 run_meta = config_pb2.RunMetadata()
190 run_metadata=run_meta)
193 sess.graph, run_meta, cmd='code', options=opts)
276 run_meta = config_pb2.RunMetadata()
280 run_metadata=run_meta)
283 sess.graph, run_meta, cmd='code', options=opts)
304 run_meta = config_pb2.RunMetadata(
[all...] |
| /external/tensorflow/tensorflow/core/profiler/g3doc/ |
| python_api.md | 79 run_meta=run_metadata,
87 run_meta=run_metadata,
124 run_meta = config_pb2.RunMetadata()
128 run_metadata=run_meta)
130 # Add run_meta of step 1.
131 profiler.add_step(1, run_meta)
139 # Add run_meta of step 2.
148 # Add run_meta of step 3.
|
| advise.md | 10 run_meta = config_pb2.RunMetadata()
14 run_metadata=run_meta)
15 profiler.add_step(1, run_meta)
22 sess.graph, run_meta=run_metadata)
|
| command_line.md | 40 with tf.gfile.Open(os.path.join(output_dir, "run_meta"), "w") as f:
97 --run_meta_path=run_meta
102 --run_meta_path=run_meta \
108 --run_meta_path=run_meta \
116 --run_meta_path=run_meta \
150 # supported select fields. Availability depends on --[run_meta|checkpoint|op_log]_path.
269 --run_meta_path=/tmp/run_meta
301 sess.graph, /tmp/my_op_log_dir, op_log, run_meta)
|
| profile_time.md | 105 sess.graph, run_meta, cmd='code', options=opts)
|
| /external/tensorflow/tensorflow/core/profiler/ |
| profiler.cc | 237 std::unique_ptr<RunMetadata> run_meta(new RunMetadata());
238 s = ReadProtoFile(Env::Default(), run_meta_files[i], run_meta.get(),
245 tf_stat->AddRunMeta(i, std::move(run_meta));
|
