| /external/tensorflow/tensorflow/python/util/ |
| D | tfprof.i | 44 %unignore tensorflow::tfprof;
45 %unignore tensorflow::tfprof::PrintModelAnalysis;
46 %unignore tensorflow::tfprof::NewProfiler;
47 %unignore tensorflow::tfprof::ProfilerFromFile;
48 %unignore tensorflow::tfprof::DeleteProfiler;
49 %unignore tensorflow::tfprof::AddStep;
50 %unignore tensorflow::tfprof::SerializeToString;
51 %unignore tensorflow::tfprof::WriteProfile;
52 %unignore tensorflow::tfprof::Profile;
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| /external/tensorflow/tensorflow/core/profiler/internal/ |
| D | tfprof_utils.cc | 31 namespace tfprof { namespace
116 tensorflow::tfprof::Options* opts) { in ParseCmdLine()
129 if (pieces[i] == string(tensorflow::tfprof::kOptions[0])) { in ParseCmdLine()
135 } else if (pieces[i] == tensorflow::tfprof::kOptions[1]) { in ParseCmdLine()
141 } else if (pieces[i] == tensorflow::tfprof::kOptions[2]) { in ParseCmdLine()
147 } else if (pieces[i] == tensorflow::tfprof::kOptions[3]) { in ParseCmdLine()
153 } else if (pieces[i] == tensorflow::tfprof::kOptions[4]) { in ParseCmdLine()
159 } else if (pieces[i] == tensorflow::tfprof::kOptions[5]) { in ParseCmdLine()
165 } else if (pieces[i] == tensorflow::tfprof::kOptions[6]) { in ParseCmdLine()
172 } else if (pieces[i] == tensorflow::tfprof::kOptions[7]) { in ParseCmdLine()
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| D | tfprof_utils.h | 29 namespace tfprof {
39 tensorflow::tfprof::Options* opts);
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| D | tfprof_constants.h | 20 namespace tfprof {
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| /external/tensorflow/tensorflow/core/profiler/g3doc/ |
| D | command_line.md | 4 * [Start `tfprof`](#start-tfprof)
17 tfprof command line tool uses the following input:
45 tensorflow.tfprof.OpLogProto (optional). A proto used to provide extra operation
60 ### Start `tfprof`
62 #### Build `tfprof` argument
72 #### Start `tfprof` Interactive Mode argument
74 # The following commands will start tfprof interactive mode.
121 #### Start `tfprof` Non-interactive Mode. argument
124 # Runs tfprof in one-shot.
135 tfprof>
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| D | profile_model_architecture.md | 12 For example `_trainable_variables` is created automatically by tfprof Python
18 tfprof> scope -account_type_regexes VariableV2 -max_depth 4 -select params
48 * It must have `RegisterStatistics('flops')` defined in TensorFlow. tfprof
54 shape is only known during runtime. tfprof can fill in the missing shape
59 * If no RunMetadata is provided, tfprof counts float_ops of each graph node
60 once, even if it is defined in a tf.while_loop. This is because tfprof
62 RunMetadata is provided, tfprof calculates float_ops as float_ops *
68 tfprof> scope -min_float_ops 1 -select float_ops -account_displayed_op_only
82 tfprof> op -min_float_ops 1 -select float_ops -account_displayed_op_only -order_by float_ops
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| D | profile_time.md | 3 * [Times in TensorFlow and tfprof](#times-in-tensorflow-and-tfprof)
10 ### Times in TensorFlow and tfprof
23 tfprof reports 3 execution times:
48 tfprof> code -show_name_regexes seq2seq_attention.* -max_depth 10 -select micros -order_by micros
75 tfprof> code -start_name_regexes .*_add_seq2seq.* -show_name_regexes seq2seq_attention.* -max_depth…
84 tfprof> code -max_depth 5 -select micros -order_by micros -start_name_regexes .*_add_seq2seq.* -mi…
118 tfprof> op -select micros,occurrence -order_by micros
134 tfprof> op -select micros,device -order_by micros
153 tfprof options allow users to generate timeline in some advanced ways.
172 tfprof> scope -max_depth 30 -select micros -min_micros 100000 -order_by micros
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| D | profile_memory.md | 8 tfprof> graph -max_depth 10000000 -step 0 -account_type_regexes .* -output timeline:outfile=<filena…
24 tfprof> op -select bytes -order_by bytes
39 tfprof> scope -order_by bytes -select bytes -min_bytes 100000000
59 tfprof> code -max_depth 10 -select bytes -order_by bytes -start_name_regexes .*seq2seq.* -min_byte…
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| D | advise.md | 3 tfprof analyzes profiles and generates advice for common issues.
28 tfprof --graph_path=graph.pbtxt \
32 tfprof> advise
78 There is no magic behind advise mode. tfprof builds the profiles first, then
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| D | python_api.md | 30 # param_stats can be tensorflow.tfprof.GraphNodeProto or
31 # tensorflow.tfprof.MultiGraphNodeProto, depending on the view.
109 tfprof allows you to profile statistics across multiple steps.
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| D | options.md | 5 For all tfprof views, the profiles are processed with the following procedures
20 (e.g. MatMul, Conv2D). `tfprof` also considers device as operation type.
103 …of the type regexes specified. tfprof allow user to define extra operation types for graph nodes t…
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| /external/tensorflow/tensorflow/contrib/tfprof/ |
| D | __init__.py | 27 from tensorflow.contrib.tfprof import model_analyzer
28 from tensorflow.contrib.tfprof import tfprof_logger
30 from tensorflow.contrib.tfprof.model_analyzer import ProfileContext
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| D | BUILD | 8 name = "tfprof",
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| /external/tensorflow/tensorflow/core/profiler/ |
| D | README.md | 30 with tf.contrib.tfprof.ProfileContext('/tmp/train_dir') as pctx:
36 tfprof> op -select micros,bytes,occurrence -order_by micros
53 with tf.contrib.tfprof.ProfileContext('/tmp/train_dir',
77 with tf.contrib.tfprof.ProfileContext('/tmp/train_dir',
106 tfprof> code -max_depth 1000 -show_name_regexes .*model_analyzer.*py.* -select micros -account_type…
125 tfprof> scope -account_type_regexes VariableV2 -max_depth 4 -select params
141 tfprof> op -select micros,bytes,occurrence -order_by micros
159 tfprof> advise
219 tfprof> graph -step -1 -max_depth 100000 -output timeline:outfile=<filename>
241 tfprof> code -select accelerator_micros -max_depth 100000 -output pprof:outfile=<filename> -trim_n…
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| D | tfprof_options.proto | 3 package tensorflow.tfprof;
6 // Only used to pass tfprof options from Python to C++.
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| D | tfprof_log.proto | 3 package tensorflow.tfprof;
30 // float_ops is filled by tfprof Python API when called. It requires the
37 // Used to support tfprof "code" view.
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.profiler.-op-log-proto.pbtxt | 10 type_name: ".tensorflow.tfprof.OpLogEntry"
17 type_name: ".tensorflow.tfprof.OpLogProto.IdToStringEntry"
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| D | tensorflow.profiler.-advice-proto.pbtxt | 10 type_name: ".tensorflow.tfprof.AdviceProto.CheckersEntry"
25 type_name: ".tensorflow.tfprof.AdviceProto.Checker"
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| D | tensorflow.profiler.-graph-node-proto.pbtxt | 16 type_name: ".tensorflow.tfprof.TFProfTensorProto"
162 type_name: ".tensorflow.tfprof.GraphNodeProto.InputShapesEntry"
169 type_name: ".tensorflow.tfprof.GraphNodeProto"
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| D | tensorflow.profiler.-multi-graph-node-proto.pbtxt | 124 type_name: ".tensorflow.tfprof.GraphNodeProto"
131 type_name: ".tensorflow.tfprof.MultiGraphNodeProto"
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| D | tensorflow.profiler.-advice-proto.-checkers-entry.pbtxt | 16 type_name: ".tensorflow.tfprof.AdviceProto.Checker"
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| /external/tensorflow/tensorflow/core/profiler/internal/advisor/ |
| D | internal_checker_runner_dummy.cc | 18 namespace tfprof { namespace
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| D | internal_checker_runner.h | 24 namespace tfprof {
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| D | checker.h | 24 namespace tfprof {
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| /external/tensorflow/tensorflow/cc/profiler/ |
| D | profiler.h | 26 namespace tfprof {
|