diff options
| author |  A. Unique TensorFlower <gardener@tensorflow.org> | 2016-10-25 14:02:41 -0800 |
|---|---|---|
| committer | TensorFlower Gardener <gardener@tensorflow.org> | 2016-10-25 15:19:00 -0700 |
| commit | 289ddb1cb6209d09e14ad44a4363f9a8b68e9006 (patch) | |
| tree | af822c48086ff8f228592215e0345ce529165f5e /tensorflow/contrib/tfprof | |
| parent | d97c2ad2b6e72aaae9da297212e90cb7576fa79e (diff) | |
Add tfprof python API to tf.contrib and move tfprof CLI to tensorflow/tools.
Change: 137207286
Diffstat (limited to 'tensorflow/contrib/tfprof')
40 files changed, 601 insertions, 4595 deletions
diff --git a/tensorflow/contrib/tfprof/BUILD b/tensorflow/contrib/tfprof/BUILD index d55bda1bd0..e817cb86df 100644 --- a/tensorflow/contrib/tfprof/BUILD +++ b/tensorflow/contrib/tfprof/BUILD @@ -12,6 +12,7 @@ py_library( srcs_version = "PY2AND3", visibility = ["//tensorflow:__subpackages__"], deps = [ + "//tensorflow/contrib/tfprof/python/tools/tfprof:model_analyzer", "//tensorflow/contrib/tfprof/python/tools/tfprof:tfprof_logger", ], ) diff --git a/tensorflow/contrib/tfprof/README.md b/tensorflow/contrib/tfprof/README.md index 013be48676..e103cb2121 100644 --- a/tensorflow/contrib/tfprof/README.md +++ b/tensorflow/contrib/tfprof/README.md @@ -20,434 +20,9 @@ and measures system performance. 4. Explore model based on name scope or graph structure. 5. Selectively grouping/filtering/accounting/ordering ops. -### Interfaces +tfprof can be used as CommandLine Interface (CLI) and Python API. +CLI locates in tensorflow/tools/tfprof. +Python API locates in tensorflow/contrib/tfprof. +Tutorial locates in tensorflow/tools/tfprof/README.md -[CLI Tutorials](#cli-tutorials): -It supports interactive mode for exploration and single-shot mode for -scripts. Outputs can be dumped to files or printed in terminal. - -Python API Tutorials: Python API is not released yet. - -## CLI Tutorials - -Tutorials are based on a 32 layers ResNet. -TODO(xpan): Provide graph.pbtxt, model.ckpt, tfprof_log and run_meta download. - -### Examples - -1) Start `tfprof` command line tool - -```shell -# Build the tool. -bazel build -c opt tensorflow/contrib/tfprof/... - -# Help information, including detail 'option' instructions. -bazel-bin/tensorflow/contrib/tfprof/tools/tfprof/tfprof help -# -# The following commands will start tfprof interactive mode. -# -# Profile model shapes and parameters only. -bazel-bin/tensorflow/contrib/tfprof/tools/tfprof/tfprof \ - --graph_path=/graph.pbtxt -# -# Additionally profile checkpoint statistics and values. -# Use '-account_type_regexes _checkpoint_variables' to select -# checkpoint tensors. -bazel-bin/tensorflow/contrib/tfprof/tools/tfprof/tfprof \ - --graph_path=graph.pbtxt \ - --checkpoint_path=model.ckpt -# -# Additionally profile ops requested memory and timing. -# See CLI Input Files section on generating run_meta file. -bazel-bin/tensorflow/contrib/tfprof/tools/tfprof/tfprof \ - --graph_path=graph.pbtxt \ - --run_meta_path=run_meta \ - --checkpoint_path=model.ckpt -# -# tfprof_log is used to define customized op types and float ops. -# Use tfprof_logger.write_op_log() to create tfprof_log. -# See 11) in Examples section on generating tfprof_log file. -bazel-bin/tensorflow/contrib/tfprof/tools/tfprof/tfprof \ - --graph_path=graph.pbtxt \ - --run_meta_path=run_meta \ - --op_log_path=tfprof_log \ - --checkpoint_path=model.ckpt -``` -Note that `graph.pbtxt` is an ASCII text format. - -2) Press enter to show the default options - -```shell -tfprof> -tfprof> --max_depth 4 --min_bytes 0 --min_micros 0 --min_params 0 --min_float_ops 0 --device_regexes .* --order_by name --account_type_regexes Variable --start_name_regexes .* --trim_name_regexes --show_name_regexes .* --hide_name_regexes IsVariableInitialized_[0-9]+,save\/.*,^zeros[0-9_]* --account_displayed_op_only false -# supported select fileds. Availability depends on --[run_meta|checkpoint|op_log]_path. -# [bytes|micros|params|float_ops|num_hidden_ops|tensor_value|device|op_types] --select params --viz false --dump_to_file -``` - -3) I want to see the `BatchNorm`'s gamma value in checkpoint. - -```shell -# Requires --graph_path, --checkpoint_path. -tfprof> scope -show_name_regexes unit_1_0.*gamma -select tensor_value -max_depth 5 -_TFProfRoot () - unit_1_0/shared_activation/init_bn/gamma () -[1.80 2.10 2.06 1.91 2.26 1.86 1.81 1.37 1.78 1.85 1.96 1.54 2.04 2.34 2.22 1.99 ], - unit_1_0/sub2/bn2/gamma () -[1.57 1.83 1.30 1.25 1.59 1.14 1.26 0.82 1.19 1.10 1.48 1.01 0.82 1.23 1.21 1.14 ], -``` - -4) I want to see my checkpoint tensors shape and number of parameters. - -```shell -# Requires --graph_path, --checkpoint_path. -# Increase -max_depth to see all tensors. -tfprof> scope -account_type_regexes _checkpoint_variables -select params -max_depth 4 -_TFProfRoot (--/930.58k params) - global_step (0/0 params) - init/init_conv/DW (3x3x3x16, 432/864 params) - pool_logit/DW (64x10, 640/1.28k params) - pool_logit/DW/Momentum (64x10, 640/640 params) - pool_logit/biases (10, 10/20 params) - pool_logit/biases/Momentum (10, 10/10 params) - unit_last/final_bn/beta (64, 64/128 params) - unit_last/final_bn/gamma (64, 64/128 params) - unit_last/final_bn/moving_mean (64, 64/64 params) - unit_last/final_bn/moving_variance (64, 64/64 params) -``` - -5) I defined an op named ‘cost’ to calculate the loss. I want to know what ops -it depends on take a long time to run. Hint: Use the ‘graph’ command to explore -graph dependencies. - -```shell -# Requires --graph_path, --run_meta_path. -tfprof> graph -start_name_regexes cost.* -max_depth 100 -min_micros 10000 -select micros -account_type_regexes .* -_TFProfRoot (0us/3.61sec) - init/init_conv/Conv2D (11.75ms/3.10sec) - random_shuffle_queue_DequeueMany (3.09sec/3.09sec) - unit_1_0/sub2/conv2/Conv2D (74.14ms/3.19sec) - unit_1_3/sub2/conv2/Conv2D (60.75ms/3.34sec) - unit_2_4/sub2/conv2/Conv2D (73.58ms/3.54sec) - unit_3_3/sub2/conv2/Conv2D (10.26ms/3.60sec) -``` - -6) I want to know the expensive operations during the back propagation. -Hint: tensorflow prepend ‘gradient’ to your defined name scopes. Use the ‘scope’ -command to explore based on name scope hierarchies. - -```shell -# Requires --graph_path, --run_meta_path. -tfprof> scope -start_name_regexes gradient.* -max_depth 100 -min_micros 20000 -select micros -account_type_regexes .* -_TFProfRoot (0us/2.29sec) - gradients/unit_1_0/sub1/conv1/Conv2D_grad/Conv2DBackpropFilter (54.96ms/54.96ms) - gradients/unit_1_0/sub2/conv2/Conv2D_grad/Conv2DBackpropFilter (83.63ms/83.63ms) - gradients/unit_1_1/sub1/conv1/Conv2D_grad/Conv2DBackpropFilter (99.25ms/99.25ms) - gradients/unit_1_2/sub1/conv1/Conv2D_grad/Conv2DBackpropFilter (95.40ms/95.40ms) - gradients/unit_1_2/sub2/conv2/Conv2D_grad/Conv2DBackpropFilter (99.83ms/99.83ms) - gradients/unit_1_3/sub1/conv1/Conv2D_grad/Conv2DBackpropFilter (95.39ms/95.39ms) - ... -``` - -7) Show the number of float operations in the model. -Note: float operations calculation depends on -1) op.RegisterStatistics. If an op doesn’t -have RegisterStatistics defined, its float operations cannot be counted. -2) fully defined shape is also necessary in order to calculate flops. -float operations number is provided by tensorflow::tfprof::OpLog logged from -Python API. - -```shell -# Requires --graph_path, --op_log_path. -tfprof> scope -min_float_ops 1 -max_depth 10 -select float_ops -account_type_regexes .* -_TFProfRoot (0/17.63b flops) - gradients/pool_logit/xw_plus_b/MatMul_grad/MatMul (163.84k/163.84k flops) - gradients/pool_logit/xw_plus_b/MatMul_grad/MatMul_1 (163.84k/163.84k flops) - init/init_conv/Conv2D (113.25m/113.25m flops) - pool_logit/xw_plus_b (1.28k/165.12k flops) - pool_logit/xw_plus_b/MatMul (163.84k/163.84k flops) - unit_1_0/sub1/conv1/Conv2D (603.98m/603.98m flops) - unit_1_0/sub2/conv2/Conv2D (603.98m/603.98m flops) - unit_1_1/sub1/conv1/Conv2D (603.98m/603.98m flops) - unit_1_1/sub2/conv2/Conv2D (603.98m/603.98m flops) - ... -``` - -8) Show the number of parameters of all `tf.trainable_variables()` in the model. - -```shell -# Requires --graph_path --op_log_path. -# store option for future commands. -tfprof> set -account_type_regexes _trainable_variables -tfprof> scope -max_depth 4 -select params -_TFProfRoot (--/464.15k params) - init/init_conv/DW (3x3x3x16, 432/432 params) - pool_logit/DW (64x10, 640/640 params) - pool_logit/biases (10, 10/10 params) - unit_last/final_bn/beta (64, 64/64 params) - unit_last/final_bn/gamma (64, 64/64 params) -``` - -Where does “_trainable_variables” come from? It is from the OpLog file -generated by write_op_log() Python API. write_op_log() help users create some -common op types implicitly. Users can define their own op types and log it -through the write_op_log() API. - -9) What if I’m lazy and don’t want to define op type? I have given my ops -well-defined names in my model’s code. And want to use names to select a group -of ops. Let’s try it! - -```shell -tfprof> set -account_type_regexes .* -tfprof> scope -show_name_regexes unit_2_1.*DW -max_depth 100 -account_displayed_op_only -_TFProfRoot (0/18.43k params) - unit_2_1/sub1/conv1/DW (3x3x32x32, 9.22k/9.22k params) - unit_2_1/sub2/conv2/DW (3x3x32x32, 9.22k/9.22k params) -``` - -The above command allows you to filter ops that match specific names. -`-account_displayed_op_only` asks tfprof to only account ops displayed -in terminal. Otherwise, tfprof accounts all ops matched by -`-account_type_regexes` recursively even if they are hidden due to some -options such as -max_depth. - -10) TensorFlow has built-in op types. For example, built-in op type `Variable` -seems to include `Variable's` created by your model. However, be careful when -depending on it because TensorFlow creates extra `Variable` ops implicitly and -the implicitly created ops can have the same prefix as the `Variable's` you -defined. - -In the following example, extra `Variables` are created and “/Momentum” is -appended to their names. This might cause you “model capacity” calculation -to get wrong. - -```shell -tfprof> scope -account_type_regexes Variable -max_depth 4 -select params -_TFProfRoot (--/930.58k params) - global_step (1/1 params) - init/init_conv/DW (3x3x3x16, 432/864 params) - pool_logit/DW (64x10, 640/1.28k params) - pool_logit/DW/Momentum (64x10, 640/640 params) - pool_logit/biases (10, 10/20 params) - pool_logit/biases/Momentum (10, 10/10 params) - unit_last/final_bn/beta (64, 64/128 params) - unit_last/final_bn/gamma (64, 64/128 params) - unit_last/final_bn/moving_mean (64, 64/64 params) - unit_last/final_bn/moving_variance (64, 64/64 params) -``` - - -11) A example of defining extra op type for ops using `OpLog` - -First, in Python code, create an `OpLog` proto and add op type -information to it: - -```python - -op_log = tfprof_log_pb2.OpLog() -entry = op_log.log_entries.add() -entry.name = 'pool_logit/DW' -entry.types.append('pool_logit') -entry = op_log.log_entries.add() -entry.name = 'pool_logit/biases' -# Alternatively: -# var = tf.get_variable(xxx) -# entry.name = var.op.name -entry.types.append('pool_logit') -``` - -Second, call write_op_log to write the OpLog proto. - -```python -tf.tfprof.tfprof_logger.write_op_log(sess.graph, /tmp/my_op_log_dir, op_log) -``` - -Third, when starting the tfprof tool, specify -"--op_log_path /tmp/my_op_log_dir/op_log" - -```shell -tfprof> scope -account_type_regexes pool_logit -max_depth 4 -select params -_TFProfRoot (--/650 params) - pool_logit/DW (64x10, 640/640 params) - pool_logit/biases (10, 10/10 params) -``` - -Note that when you call -`tf.tfprof.tfprof_logger.write_op_log(...)`, the tool adds all `Variables` -inside `tf.trainable_variables()` to `_trainable_variables`. - -12) Run tfprof in one-shot mode and dump result to file. - -```shell -# Printed to stdout if --dump_to_file is not set. -tfprof scope --graph_path /cns/ij-d/home/xpan/tfprof/graph.pbtxt \ - --max_depth 3 \ - --dump_to_file "/tmp/dump" -Reading Files... -Parsing GraphDef... -Preparing Views... - -cat /tmp/dump -_TFProfRoot (--/930.58k params) - global_step (0/0 params) - pool_logit/DW (64x10, 640/1.28k params) - pool_logit/biases (10, 10/20 params) -``` - -13) Analyze how balanced Variable are on parameter servers. - -In this tutorial, I'm going to use a seq2seq model, which are split -on several gpus at workers and several parameter servers. - -In tfprof, 'device' is an op_type. For example, if op1 and op2 are placed on -gpu0. They share an op_type called 'gpu0'. - -```shell -bazel-bin/tensorflow/contrib/tfprof/tools/tfprof/tfprof \ - --graph_path ~/tfprof/textsum/graph.pbtxt \ - --run_meta_path ~/tfprof/textsum/run_meta - -# Looks like ps task 1 is holding twice more parameters than task 0. -tfprof> scope -select device,params -account_type_regexes .*ps.*task:0.* -max_depth 1 -_TFProfRoot (--/25.81m params) -tfprof> scope -select device,params -account_type_regexes .*ps.*task:1.* -max_depth 1 -_TFProfRoot (--/58.84m params) -``` - -### CLI Input Files - -tfprof command line inference (CLI) loads dumped files from a tensorflow model. -Convert them into in-memory data structures. To use it, users need to specify -the locations of the dumped files. The following are the dumped files loaded -by tfprof: - -<b>--graph_path:</b> GraphDef text file (required). Used to build in-memory -representation of the model. For example, graph.pbtxt written by tf.Supervisor -is a candidate. If you are not using tf.Supervisor, you can easily get GraphDef -using tf.Graph.as_graph_def() or other API. - -<b>--run_meta_path:</b> tensorflow::RunMetadata. -Used to get the memory and time consumption of -each op of the model. Users need to enable it. For example, the following code -snippet writes a RunMetadata file: - -```python -run_options = config_pb2.RunOptions(trace_level=config_pb2.RunOptions.FULL_TRACE) -run_metadata = config_pb2.RunMetadata() -# Once a while, call it the get the RunMeta. -_ = self._sess.run(..., options=run_options, run_metadata=run_metadata) -with gfile.Open(os.path.join(output_dir, "run_meta"), "w") as f: - f.write(run_metadata.SerializeToString()) -``` - -<b>--op_log_path:</b> -tensorflow::tfprof::OpLog. A proto used to provide extra op information -for ops. By giving a group of ops a type name, users can easily aggregate the -statistics for those ops without accidently missing or including extra ops. -tfprof exposes the following Python API to add op information and logging. - -```python -tf.contrib.tfprof.tfprof_logger.write_op_log(graph, log_dir, op_log=None) -``` - -<b>--checkpoint_path:</b> -TensorFlow checkpoint. It defines _checkpoint_variable op type. It also -provides checkpointed tensors' values. - - -## Design - - -### In-memory representation - -<b>Scope:</b> This representation organizes ops based on name scope hierarchy, -similar to filesystem hierarchy. Hence, it is essentially a tree data structure. -For example op1 with name “name1/name2” is a child of op2 with name “name1”. - -<b>Graph:</b> The representation organizes ops based on op inputs. Hence it is -a graph structure. The graph is a “directed acyclic graph” (hopefully), with -direction from “output to input”. The direction is design this way so that users -can trace from “result” to its “sources”. - -### Command line options - -tfprof’s major goals are to measure system performance and quicly analyze -model architectures. Hence, its commands and options should allow users to achieve -these 2 goals easily. - -<b>graph:</b> It is expected that users will mostly use graph representation to -debug system performance. Hence, tfprof supports graph command, which pulls the -graph in-memory representation described above. - -<b>scope:</b> It is expected that some users might want to explore their model -statistics using the name scope information they defined in the Python codes. -Hence, tfprof supports “scope” command, which pulls the tree in-memory -representation. - -<b>set:</b> It is used to store the options so that user doesn’t need to -re-type the same option again and again in the follow up command line. Note that -tfprof has traditional terminal’s history and auto-complete support. - -<b>help:</b> print help information. - -<b>Options:</b> Run “tfprof help” to get detailed explanations. - -```python -"-max_depth", -"-min_bytes", -"-min_micros", -"-min_params", -"-min_float_ops", -"-order_by", -"-account_type_regexes", -"-start_name_regexes", -"-trim_name_regexes", -"-show_name_regexes", -"-hide_name_regexes", -"-account_displayed_op_only", -"-select", -"-viz", # Only supported for graph command. -"-dump_to_file", -``` - -A key design is that stats are aggregated from descendants up to ancestors. -`-account_type_regexes` is used to decide which ops stat is accounted. It makes -decision based on op type. Usually set it to `.*` if no extra type information -is added to the ops using OpLog. Intuitively, only accounted ops are displayed. -`-min/max` and `-show/hide/trim/start` options are only used the optionally -displayed or hide ops based on ops’ name and stats. However, they don’t prevent -tfprof from accounting stats of hidden ops. Hence, the stat of a op can be -aggregated by its parent even if it is hidden. `-account_displayed_op_only` is -an option to break this rule. When it is set, only displayed ops are accounted. - -Regexes are all comma-separated, for example `-show_name_regexes` -`regex1.*,regex2.*`. It is designed this way because it is convenient and comma -is not expected to show up in op names. - -`-order_by` is used to order displayed ops. Displayed ops at the same hierarchy -(notice the indent printed) are sorted according to order_by. - -## Future Work - -* Load SummaryWriter event logs so that it can show the latest summary value. - -* Better sorting and aggregation of outputs. Easier comprehension. - -* Currently, shape information is based on `graph.pbtxt`. When the shape -information is incomplete, tfprof ignores it. See if it can use `RunMetadata` -and `Checkpoint` to complete shape information. +Enjoy!
\ No newline at end of file diff --git a/tensorflow/contrib/tfprof/__init__.py b/tensorflow/contrib/tfprof/__init__.py index ce777979b9..129dad2726 100644 --- a/tensorflow/contrib/tfprof/__init__.py +++ b/tensorflow/contrib/tfprof/__init__.py @@ -17,5 +17,6 @@ from __future__ import absolute_import from __future__ import division from __future__ import print_function +from tensorflow.contrib.tfprof.python.tools.tfprof import model_analyzer from tensorflow.contrib.tfprof.python.tools.tfprof import tfprof_logger from tensorflow.python.util.all_util import make_all diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD b/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD index 87a8311486..07677c6ed7 100644 --- a/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD +++ b/tensorflow/contrib/tfprof/python/tools/tfprof/BUILD @@ -3,14 +3,36 @@ licenses(["notice"]) # Apache 2.0 package(default_visibility = ["//visibility:public"]) load("//tensorflow:tensorflow.bzl", "tf_py_test") +load("//tensorflow:tensorflow.bzl", "tf_py_wrap_cc") + +py_library( + name = "model_analyzer", + srcs = ["model_analyzer.py"], + srcs_version = "PY2AND3", + deps = [ + "//tensorflow/contrib/tfprof/python/tools/tfprof:pywrap_tensorflow_print_model_analysis_lib", + "//tensorflow/contrib/tfprof/python/tools/tfprof:tfprof_logger", + "//tensorflow/tools/tfprof:protos_all_py", + ], +) + +py_test( + name = "model_analyzer_test", + srcs = ["model_analyzer_test.py"], + srcs_version = "PY2AND3", + deps = [ + ":model_analyzer", + "//tensorflow:tensorflow_py", + ], +) py_library( name = "tfprof_logger", srcs = ["tfprof_logger.py"], srcs_version = "PY2AND3", deps = [ - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_py", "//tensorflow/python:framework_for_generated_wrappers", + "//tensorflow/tools/tfprof:protos_all_py", ], ) @@ -20,7 +42,34 @@ tf_py_test( additional_deps = [ ":tfprof_logger", "//tensorflow:tensorflow_py", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_py", + "//tensorflow/tools/tfprof:protos_all_py", + ], +) + +tf_py_wrap_cc( + name = "pywrap_tensorflow_print_model_analysis_lib", + srcs = ["pywrap_tensorflow_print_model_analysis.i"], + swig_includes = [ + "//tensorflow/python:lib/core/strings.i", + "//tensorflow/python:platform/base.i", + ], + deps = [ + "//tensorflow/core:framework_headers_lib", + "//tensorflow/tools/tfprof/internal:print_model_analysis_hdr", + "//util/python:python_headers", + ], +) + +py_test( + name = "print_model_analysis_test", + srcs = ["print_model_analysis_test.py"], + srcs_version = "PY2AND3", + deps = [ + ":pywrap_tensorflow_print_model_analysis_lib", + "//tensorflow:tensorflow_py", + "//tensorflow/python:framework_test_lib", + "//tensorflow/python:platform_test", + "//tensorflow/tools/tfprof:protos_all_py", ], ) diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py new file mode 100644 index 0000000000..92943b1adb --- /dev/null +++ b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer.py @@ -0,0 +1,187 @@ +# 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. +# ============================================================================== +"""Model Analyzer. + +Analyze model, including shape, params, time, memory, structure, etc. +""" +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +from tensorflow.contrib.tfprof.python.tools.tfprof import pywrap_tensorflow_print_model_analysis_lib as print_mdl +from tensorflow.contrib.tfprof.python.tools.tfprof import tfprof_logger +from tensorflow.tools.tfprof import tfprof_options_pb2 +from tensorflow.tools.tfprof import tfprof_output_pb2 + +# pylint: disable=bad-whitespace +# pylint: disable=bad-continuation +# 2 example tfprof_options for print_model_analysis API. +# +# Show the parameter statistics of trainable variables. +TRAINABLE_VARS_PARAMS_STAT_OPTIONS = { + 'max_depth': 10000, + 'min_bytes': 0, + 'min_micros': 0, + 'min_params': 0, + 'min_float_ops': 0, + 'device_regexes': ['.*'], + 'order_by': 'name', + 'account_type_regexes': [tfprof_logger.TRAINABLE_VARIABLES], + 'start_name_regexes': ['.*'], + 'trim_name_regexes': [], + 'show_name_regexes': ['.*'], + 'hide_name_regexes': [], + 'account_displayed_op_only': True, + 'select': ['params'], + 'viz': False, + 'dump_to_file': '' +} + +# Show the number float operations. +FLOAT_OPS_OPTIONS = { + 'max_depth': 10000, + 'min_bytes': 0, + 'min_micros': 0, + 'min_params': 0, + 'min_float_ops': 1, + 'device_regexes': ['.*'], + 'order_by': 'float_ops', + 'account_type_regexes': ['.*'], + 'start_name_regexes': ['.*'], + 'trim_name_regexes': [], + 'show_name_regexes': ['.*'], + 'hide_name_regexes': [], + 'account_displayed_op_only': True, + 'select': ['float_ops'], + 'viz': False, + 'dump_to_file': '' +} + +# Show number of parameters on parameter server 0. +# It is recommended to provide`run_meta` argument +# to have complete device placement info. +PRINT_PARAMS_ON_DEVICE = { + 'max_depth': 1, + 'min_bytes': 0, + 'min_micros': 0, + 'min_params': 0, + 'min_float_ops': 0, + 'device_regexes': ['.*'], + 'order_by': 'name', + 'account_type_regexes': ['.*ps.*task:0.*'], + 'start_name_regexes': ['.*'], + 'trim_name_regexes': [], + 'show_name_regexes': ['.*'], + 'hide_name_regexes': [], + 'account_displayed_op_only': False, + 'select': ['device', 'params'], + 'viz': False, + 'dump_to_file': '' +} + +# Show the timing stats and memory demands. +PRINT_ALL_TIMING_MEMORY = { + 'max_depth': 10000, + 'min_bytes': 1, # Only >=1 + 'min_micros': 1, # Only >=1 + 'min_params': 0, + 'min_float_ops': 0, + 'device_regexes': ['.*'], + 'order_by': 'name', + 'account_type_regexes': ['.*'], + 'start_name_regexes': ['.*'], + 'trim_name_regexes': [], + 'show_name_regexes': ['.*'], + 'hide_name_regexes': [], + 'account_displayed_op_only': True, + 'select': ['micros', 'bytes'], + 'viz': False, + 'dump_to_file': '' +} + +# pylint: enable=bad-whitespace +# pylint: enable=bad-continuation + + +def print_model_analysis(graph, + run_meta=None, + op_log=None, + tfprof_cmd='scope', + tfprof_options=TRAINABLE_VARS_PARAMS_STAT_OPTIONS): + """Print model statistics. + + Prints the model statistics to stdout. Also returns the results + in a TFProfNode proto. See go/tfprof or run tfprof tool: + 'bazel run third_party/tensorflow/tools/tfprof help' + + Examples: + Show the parameter/shape statistics of tf.trainable_variables(). + print_model_analysis(sess.graph). + + Show number of float ops. Only ops with RegisterStatistics defined + are counted. + show_float_op_opts = model_analyzer.FLOAT_OPS_OPTIONS + print_model_analysis(sess.graph, tfprof_options=show_float_op_opts) + + Args: + graph: tf.Graph. + run_meta: tensorflow::RunMetadata proto. When provided, also shows valid + timing and memory information when 'select' option contains + 'micros' and 'bytes'. + op_log: tensorflow::tfprof::OpLog proto. users can use this proto to + group together ops and use a op_type to select the group. + tfprof_cmd: string. Either 'scope' or 'graph'. 'scope' view organize + ops using their name scopes. 'graph' view organize ops using + their graph inputs. + tfprof_options: See 'tfprof help' for details. + Returns: + TFProfNode proto. Side effect: a formatted output to stdout. + """ + # pylint: disable=protected-access + op_log = tfprof_logger._merge_default_with_oplog(graph, op_log, run_meta) + # pylint: enable=protected-access + opts = tfprof_options_pb2.OptionsProto() + opts.max_depth = tfprof_options['max_depth'] + opts.min_bytes = tfprof_options['min_bytes'] + opts.min_micros = tfprof_options['min_micros'] + opts.min_params = tfprof_options['min_params'] + opts.min_float_ops = tfprof_options['min_float_ops'] + for p in tfprof_options['device_regexes']: + opts.device_regexes.append(p) + opts.order_by = tfprof_options['order_by'] + for p in tfprof_options['account_type_regexes']: + opts.account_type_regexes.append(p) + for p in tfprof_options['start_name_regexes']: + opts.start_name_regexes.append(p) + for p in tfprof_options['trim_name_regexes']: + opts.trim_name_regexes.append(p) + for p in tfprof_options['show_name_regexes']: + opts.show_name_regexes.append(p) + for p in tfprof_options['hide_name_regexes']: + opts.hide_name_regexes.append(p) + opts.account_displayed_op_only = tfprof_options['account_displayed_op_only'] + for p in tfprof_options['select']: + opts.select.append(p) + opts.viz = tfprof_options['viz'] + opts.dump_to_file = tfprof_options['dump_to_file'] + + run_meta_str = run_meta.SerializeToString() if run_meta else b'' + op_log_str = op_log.SerializeToString() if op_log else b'' + + tfprof_node = tfprof_output_pb2.TFProfNode() + tfprof_node.ParseFromString( + print_mdl.PrintModelAnalysis( + graph.as_graph_def().SerializeToString(), run_meta_str, op_log_str, + tfprof_cmd.encode('utf-8'), opts.SerializeToString())) diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py new file mode 100644 index 0000000000..2673a64d33 --- /dev/null +++ b/tensorflow/contrib/tfprof/python/tools/tfprof/model_analyzer_test.py @@ -0,0 +1,84 @@ +# 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. +# ============================================================================== +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import os + +import tensorflow as tf + + +class PrintModelAnalysisTest(tf.test.TestCase): + + def _BuildSmallModel(self): + image = tf.zeros([2, 6, 6, 3]) + kernel = tf.get_variable( + 'DW', [3, 3, 3, 6], + tf.float32, + initializer=tf.random_normal_initializer(stddev=0.001)) + x = tf.nn.conv2d(image, kernel, [1, 2, 2, 1], padding='SAME') + kernel = tf.get_variable( + 'DW2', [2, 2, 6, 12], + tf.float32, + initializer=tf.random_normal_initializer(stddev=0.001)) + x = tf.nn.conv2d(x, kernel, [1, 2, 2, 1], padding='SAME') + return x + + def testDumpToFile(self): + opts = tf.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS + opts['dump_to_file'] = os.path.join(tf.test.get_temp_dir(), 'dump') + + with tf.Session() as sess: + _ = self._BuildSmallModel() + tf.contrib.tfprof.model_analyzer.print_model_analysis( + sess.graph, tfprof_options=opts) + + with tf.gfile.Open(opts['dump_to_file'], 'r') as f: + self.assertEqual('_TFProfRoot (--/450 params)\n' + ' DW (3x3x3x6, 162/162 params)\n' + ' DW2 (2x2x6x12, 288/288 params)\n', + f.read().decode('utf-8')) + + def testSelectEverything(self): + opts = tf.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS + opts['dump_to_file'] = os.path.join(tf.test.get_temp_dir(), 'dump') + opts['account_type_regexes'] = ['.*'] + opts['select'] = [ + 'bytes', 'params', 'float_ops', 'num_hidden_ops', 'device', 'op_types' + ] + + with tf.Session() as sess: + x = self._BuildSmallModel() + + sess.run(tf.initialize_all_variables()) + run_meta = tf.RunMetadata() + _ = sess.run(x, + options=tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE), + run_metadata=run_meta) + + tf.contrib.tfprof.model_analyzer.print_model_analysis( + sess.graph, run_meta, tfprof_options=opts) + + with tf.gfile.Open(opts['dump_to_file'], 'r') as f: + # pylint: disable=line-too-long + self.assertEqual( + '_TFProfRoot (0/450 params, 0/10.44k flops, 0B/5.28KB, _kTFScopeParent)\n Conv2D (0/0 params, 5.83k/5.83k flops, 432B/432B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D)\n Conv2D_1 (0/0 params, 4.61k/4.61k flops, 384B/384B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Conv2D)\n DW (3x3x3x6, 162/162 params, 0/0 flops, 648B/1.30KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Variable|_trainable_variables)\n DW/Assign (0/0 params, 0/0 flops, 0B/0B, Assign)\n DW/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n DW/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n DW/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n DW/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n DW/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n DW/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n DW/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n DW/read (0/0 params, 0/0 flops, 648B/648B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity)\n DW2 (2x2x6x12, 288/288 params, 0/0 flops, 1.15KB/2.30KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Variable|_trainable_variables)\n DW2/Assign (0/0 params, 0/0 flops, 0B/0B, Assign)\n DW2/Initializer (0/0 params, 0/0 flops, 0B/0B, _kTFScopeParent)\n DW2/Initializer/random_normal (0/0 params, 0/0 flops, 0B/0B, Add)\n DW2/Initializer/random_normal/RandomStandardNormal (0/0 params, 0/0 flops, 0B/0B, RandomStandardNormal)\n DW2/Initializer/random_normal/mean (0/0 params, 0/0 flops, 0B/0B, Const)\n DW2/Initializer/random_normal/mul (0/0 params, 0/0 flops, 0B/0B, Mul)\n DW2/Initializer/random_normal/shape (0/0 params, 0/0 flops, 0B/0B, Const)\n DW2/Initializer/random_normal/stddev (0/0 params, 0/0 flops, 0B/0B, Const)\n DW2/read (0/0 params, 0/0 flops, 1.15KB/1.15KB, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Identity)\n init (0/0 params, 0/0 flops, 0B/0B, NoOp)\n zeros (0/0 params, 0/0 flops, 864B/864B, /job:localhost/replica:0/task:0/cpu:0, /job:localhost/replica:0/task:0/cpu:0|Const)\n', + f.read().decode('utf-8')) + # pylint: enable=line-too-long + + +if __name__ == '__main__': + tf.test.main() diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py b/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py new file mode 100644 index 0000000000..4000f0024e --- /dev/null +++ b/tensorflow/contrib/tfprof/python/tools/tfprof/print_model_analysis_test.py @@ -0,0 +1,227 @@ +# 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. +# ============================================================================== +"""print_model_analysis test.""" +from __future__ import absolute_import +from __future__ import division +from __future__ import print_function + +import tensorflow as tf +from google.protobuf import text_format +from tensorflow.contrib.tfprof.python.tools.tfprof import pywrap_tensorflow_print_model_analysis_lib as print_mdl +from tensorflow.tools.tfprof import tfprof_options_pb2 +from tensorflow.tools.tfprof import tfprof_output_pb2 + +# pylint: disable=bad-whitespace +# pylint: disable=bad-continuation +TEST_OPTIONS = { + 'max_depth': 10000, + 'min_bytes': 0, + 'min_micros': 0, + 'min_params': 0, + 'min_float_ops': 0, + 'device_regexes': ['.*'], + 'order_by': 'name', + 'account_type_regexes': ['.*'], + 'start_name_regexes': ['.*'], + 'trim_name_regexes': [], + 'show_name_regexes': ['.*'], + 'hide_name_regexes': [], + 'account_displayed_op_only': True, + 'select': ['params'], + 'viz': False +} + +# pylint: enable=bad-whitespace +# pylint: enable=bad-continuation + + +class PrintModelAnalysisTest(tf.test.TestCase): + + def _BuildSmallModel(self): + image = tf.zeros([2, 6, 6, 3]) + kernel = tf.get_variable( + 'DW', [6, 6, 3, 6], + tf.float32, + initializer=tf.random_normal_initializer(stddev=0.001)) + x = tf.nn.conv2d(image, kernel, [1, 2, 2, 1], padding='SAME') + return x + + def testPrintModelAnalysis(self): + opts = tfprof_options_pb2.OptionsProto() + opts.max_depth = TEST_OPTIONS['max_depth'] + opts.min_bytes = TEST_OPTIONS['min_bytes'] + opts.min_micros = TEST_OPTIONS['min_micros'] + opts.min_params = TEST_OPTIONS['min_params'] + opts.min_float_ops = TEST_OPTIONS['min_float_ops'] + for p in TEST_OPTIONS['device_regexes']: + opts.device_regexes.append(p) + opts.order_by = TEST_OPTIONS['order_by'] + for p in TEST_OPTIONS['account_type_regexes']: + opts.account_type_regexes.append(p) + for p in TEST_OPTIONS['start_name_regexes']: + opts.start_name_regexes.append(p) + for p in TEST_OPTIONS['trim_name_regexes']: + opts.trim_name_regexes.append(p) + for p in TEST_OPTIONS['show_name_regexes']: + opts.show_name_regexes.append(p) + for p in TEST_OPTIONS['hide_name_regexes']: + opts.hide_name_regexes.append(p) + opts.account_displayed_op_only = TEST_OPTIONS['account_displayed_op_only'] + for p in TEST_OPTIONS['select']: + opts.select.append(p) + opts.viz = TEST_OPTIONS['viz'] + + with tf.Session() as sess: + _ = self._BuildSmallModel() + tfprof_pb = tfprof_output_pb2.TFProfNode() + tfprof_pb.ParseFromString( + print_mdl.PrintModelAnalysis(sess.graph.as_graph_def( + ).SerializeToString(), b'', b'', b'scope', opts.SerializeToString())) + + expected_pb = tfprof_output_pb2.TFProfNode() + text_format.Merge(r"""name: "_TFProfRoot" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 648 + children { + name: "Conv2D" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW" + exec_micros: 0 + requested_bytes: 0 + parameters: 648 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 648 + children { + name: "DW/Assign" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW/Initializer" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + children { + name: "DW/Initializer/random_normal" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + children { + name: "DW/Initializer/random_normal/RandomStandardNormal" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW/Initializer/random_normal/mean" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW/Initializer/random_normal/mul" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW/Initializer/random_normal/shape" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW/Initializer/random_normal/stddev" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + float_ops: 0 + total_float_ops: 0 + } + float_ops: 0 + total_float_ops: 0 + } + children { + name: "DW/read" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + float_ops: 0 + total_float_ops: 0 + } + children { + name: "zeros" + exec_micros: 0 + requested_bytes: 0 + total_exec_micros: 0 + total_requested_bytes: 0 + total_parameters: 0 + float_ops: 0 + total_float_ops: 0 + } + float_ops: 0 + total_float_ops: 0""", expected_pb) + self.assertEqual(expected_pb, tfprof_pb) + + +if __name__ == '__main__': + tf.test.main() diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/pywrap_tensorflow_print_model_analysis.i b/tensorflow/contrib/tfprof/python/tools/tfprof/pywrap_tensorflow_print_model_analysis.i new file mode 100644 index 0000000000..05b734a699 --- /dev/null +++ b/tensorflow/contrib/tfprof/python/tools/tfprof/pywrap_tensorflow_print_model_analysis.i @@ -0,0 +1,43 @@ +/* Copyright 2015 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. +==============================================================================*/ + +%include "tensorflow/python/lib/core/strings.i" +%include "tensorflow/python/platform/base.i" + +%{ +#include "tensorflow/tools/tfprof/internal/print_model_analysis.h" +#include "tensorflow/core/framework/types.h" +%} + +%typemap(typecheck) const string & = char *; +%typemap(in) const string& (string temp) { + if (!_PyObjAs<string>($input, &temp)) return NULL; + $1 = &temp; +} +%typemap(out) const string& { + $result = PyString_FromStringAndSize($1->data(), $1->size()); +} +%apply const string & {string &}; +%apply const string & {string *}; + +%ignoreall + +%unignore tensorflow; +%unignore tensorflow::tfprof; +%unignore tensorflow::tfprof::PrintModelAnalysis; + +%include "tensorflow/tools/tfprof/internal/print_model_analysis.h" + +%unignoreall
\ No newline at end of file diff --git a/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py b/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py index 53dd2632b6..1f710bc970 100644 --- a/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py +++ b/tensorflow/contrib/tfprof/python/tools/tfprof/tfprof_logger.py @@ -24,8 +24,8 @@ import os import sys import tensorflow as tf -from tensorflow.contrib.tfprof.tools.tfprof import tfprof_log_pb2 from tensorflow.python.framework import ops +from tensorflow.tools.tfprof import tfprof_log_pb2 TRAINABLE_VARIABLES = '_trainable_variables' REGISTERED_FLOP_STATS = 'flops' @@ -85,7 +85,7 @@ def _get_logged_ops(graph, run_meta=None): if node.name not in logged_ops: entry = tfprof_log_pb2.OpLogEntry() entry.name = node.name - entry.float_ops = stats.value + entry.float_ops = int(stats.value) logged_ops[entry.name] = entry for v in graph.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES): diff --git a/tensorflow/contrib/tfprof/tools/tfprof/BUILD b/tensorflow/contrib/tfprof/tools/tfprof/BUILD deleted file mode 100644 index da161b1ffa..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/BUILD +++ /dev/null @@ -1,52 +0,0 @@ -package( - default_visibility = ["//visibility:public"], -) - -licenses(["notice"]) # Apache 2.0 - -# ----------------------------------------------------------------------------- -# Google-internal targets. These must be at the end for syncrepo. - -filegroup( - name = "all_files", - srcs = glob( - ["**/*"], - exclude = [ - "**/METADATA", - "**/OWNERS", - ], - ), - visibility = ["//tensorflow:__subpackages__"], -) - -cc_binary( - name = "tfprof", - srcs = ["tfprof_main.cc"], - deps = [ - ":protos_all_cc", - "//tensorflow/c:c_api", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof/internal:tfprof_options", - "//tensorflow/contrib/tfprof/tools/tfprof/internal:tfprof_stats", - "//tensorflow/contrib/tfprof/tools/tfprof/internal:tfprof_utils", - "//tensorflow/core:framework_headers_lib", - "//tensorflow/core:framework_internal", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "@linenoise//:linenoise", - ], -) - -load("//tensorflow/core:platform/default/build_config.bzl", "tf_proto_library") - -tf_proto_library( - name = "protos_all", - srcs = glob( - ["**/*.proto"], - ), - cc_api_version = 2, - cc_libs = ["//tensorflow/core:protos_all_cc"], - go_api_version = 2, - java_api_version = 2, - visibility = ["//visibility:public"], -) diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/BUILD b/tensorflow/contrib/tfprof/tools/tfprof/internal/BUILD deleted file mode 100644 index 7a4b4c0c98..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/BUILD +++ /dev/null @@ -1,234 +0,0 @@ -package( - default_visibility = ["//tensorflow:__subpackages__"], -) - -licenses(["notice"]) # Apache 2.0 - -load("//tensorflow:tensorflow.bzl", "tf_cc_test") - -cc_library( - name = "tfprof_stats", - srcs = ["tfprof_stats.cc"], - hdrs = ["tfprof_stats.h"], - deps = [ - ":tfprof_graph", - ":tfprof_node", - ":tfprof_options", - ":tfprof_scope", - ":tfprof_show", - ":tfprof_utils", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:regexp_internal", - ], -) - -cc_library( - name = "tfprof_node", - srcs = ["tfprof_node.cc"], - hdrs = ["tfprof_node.h"], - deps = [ - ":tfprof_options", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - ], -) - -cc_library( - name = "tfprof_scope", - srcs = ["tfprof_scope.cc"], - hdrs = ["tfprof_scope.h"], - deps = [ - ":tfprof_constants", - ":tfprof_node", - ":tfprof_options", - ":tfprof_show", - ":tfprof_tensor", - ":tfprof_utils", - "//tensorflow/c:c_api", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:framework", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:regexp_internal", - ], -) - -cc_library( - name = "tfprof_graph", - srcs = ["tfprof_graph.cc"], - hdrs = ["tfprof_graph.h"], - deps = [ - ":tfprof_constants", - ":tfprof_node", - ":tfprof_options", - ":tfprof_show", - ":tfprof_tensor", - ":tfprof_utils", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:regexp_internal", - ], -) - -cc_library( - name = "tfprof_show", - srcs = ["tfprof_show.cc"], - hdrs = ["tfprof_show.h"], - deps = [ - ":tfprof_constants", - ":tfprof_node", - ":tfprof_options", - ":tfprof_tensor", - ":tfprof_utils", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:regexp_internal", - ], -) - -tf_cc_test( - name = "tfprof_show_test", - srcs = ["tfprof_show_test.cc"], - data = [ - "testdata/ckpt", - "testdata/graph.pbtxt", - "testdata/run_meta", - "testdata/tfprof_log", - ], - deps = [ - ":tfprof_constants", - ":tfprof_options", - ":tfprof_stats", - ":tfprof_utils", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:test", - "//tensorflow/core:test_main", - "//tensorflow/core:testlib", - ], -) - -cc_library( - name = "tfprof_utils", - srcs = ["tfprof_utils.cc"], - hdrs = ["tfprof_utils.h"], - copts = ["-Wno-sign-compare"], - deps = [ - ":tfprof_options", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:regexp_internal", - ], -) - -cc_library( - name = "tfprof_options", - srcs = ["tfprof_options.cc"], - hdrs = ["tfprof_options.h"], - deps = [ - "//tensorflow/core:framework_headers_lib", - "//tensorflow/core:lib", - ], -) - -cc_library( - name = "print_model_analysis", - srcs = ["print_model_analysis.cc"], - hdrs = ["print_model_analysis.h"], - deps = [ - ":tfprof_options", - ":tfprof_stats", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - ], -) - -tf_cc_test( - name = "tfprof_stats_test", - srcs = ["tfprof_stats_test.cc"], - data = [ - "testdata/ckpt", - "testdata/graph.pbtxt", - "testdata/run_meta", - "testdata/tfprof_log", - ], - deps = [ - ":tfprof_constants", - ":tfprof_options", - ":tfprof_stats", - ":tfprof_utils", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:test", - "//tensorflow/core:test_main", - "//tensorflow/core:testlib", - ], -) - -cc_library( - name = "tfprof_tensor", - srcs = ["tfprof_tensor.cc"], - hdrs = ["tfprof_tensor.h"], - copts = ["-Wno-sign-compare"], - deps = [ - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:framework", - "//tensorflow/core:lib", - ], -) - -tf_cc_test( - name = "tfprof_tensor_test", - srcs = ["tfprof_tensor_test.cc"], - data = [ - "testdata/ckpt", - "testdata/graph.pbtxt", - ], - deps = [ - ":tfprof_options", - ":tfprof_stats", - ":tfprof_utils", - "//tensorflow/c:checkpoint_reader", - "//tensorflow/contrib/tfprof/tools/tfprof:protos_all_cc", - "//tensorflow/core:lib", - "//tensorflow/core:protos_all_cc", - "//tensorflow/core:test", - "//tensorflow/core:test_main", - "//tensorflow/core:testlib", - ], -) - -cc_library( - name = "tfprof_constants", - hdrs = ["tfprof_constants.h"], - deps = [ - ], -) -# ----------------------------------------------------------------------------- -# Google-internal targets. These must be at the end for syncrepo. - -filegroup( - name = "all_files", - srcs = glob( - ["**/*"], - exclude = [ - "**/METADATA", - "**/OWNERS", - ], - ), - visibility = ["//tensorflow:__subpackages__"], -) diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.cc deleted file mode 100644 index ab1e47b32d..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.cc +++ /dev/null @@ -1,65 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.h" - -#include <stdio.h> -#include <memory> -#include <utility> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h" - -namespace tensorflow { -namespace tfprof { -string PrintModelAnalysis(const string* graph, const string* run_meta, - const string* op_log, const string* command, - const Options* options) { - CHECK(graph) << "graph mustn't be null"; - CHECK(command) << "command mustn't be null"; - CHECK(options) << "options mustn't be null"; - std::unique_ptr<GraphDef> graph_ptr(new GraphDef()); - graph_ptr->ParseFromString(*graph); - - std::unique_ptr<RunMetadata> run_meta_ptr; - if (run_meta) { - run_meta_ptr.reset(new RunMetadata()); - run_meta_ptr->ParseFromString(*run_meta); - } - - std::unique_ptr<OpLog> op_log_ptr; - if (op_log) { - op_log_ptr.reset(new OpLog()); - op_log_ptr->ParseFromString(*op_log); - } - - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader; - - TFStats tf_stats(std::move(graph_ptr), std::move(run_meta_ptr), - std::move(op_log_ptr), std::move(ckpt_reader)); - - if (options->dump_to_file.empty()) { - printf("\n=========================Options=============================\n"); - printf("%s", options->ToString().c_str()); - printf("\n==================Model Analysis Report======================\n"); - TFProfNode root(tf_stats.PrintGraph(*command, *options)); - printf("\n======================End of Report==========================\n"); - fflush(stdout); - return root.SerializeAsString(); - } - return tf_stats.PrintGraph(*command, *options).SerializeAsString(); -} -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.h deleted file mode 100644 index 579147f164..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/print_model_analysis.h +++ /dev/null @@ -1,45 +0,0 @@ -/* 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. -==============================================================================*/ - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_PRINT_MODEL_ANALYSIS_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_PRINT_MODEL_ANALYSIS_H_ - -#include <string> - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.pb.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/core/errors.h" -#include "tensorflow/core/protobuf/config.pb.h" - -namespace tensorflow { -namespace tfprof { - -// ***This API is only for swig.*** -// -// Interface defined for Python API swig. Calls the tfprof core API. -// 'graph', 'run_meta', 'op_log' are serialized GraphDef, RunMetadata, -// OpLog strings, respectively. -// 'graph', 'command' and 'options' are required. Others can be nullptr -// if not available. -string PrintModelAnalysis(const string* graph, const string* run_meta, - const string* op_log, const string* command, - const Options* options); - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_PRINT_MODEL_ANALYSIS_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/ckpt b/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/ckpt Binary files differdeleted file mode 100644 index 2f59f071c5..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/ckpt +++ /dev/null diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/graph.pbtxt b/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/graph.pbtxt deleted file mode 100644 index fd54551776..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/graph.pbtxt +++ /dev/null @@ -1,636 +0,0 @@ -node { - name: "zeros" - op: "Const" - attr { - key: "dtype" - 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value { - list { - s: "loc:@DW2" - } - } - } - attr { - key: "dtype" - value { - type: DT_INT32 - } - } - attr { - key: "value" - value { - tensor { - dtype: DT_INT32 - tensor_shape { - dim { - size: 4 - } - } - tensor_content: "\002\000\000\000\002\000\000\000\006\000\000\000\014\000\000\000" - } - } - } -} -node { - name: "DW2/Initializer/random_normal/mean" - op: "Const" - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } - attr { - key: "dtype" - value { - type: DT_FLOAT - } - } - attr { - key: "value" - value { - tensor { - dtype: DT_FLOAT - tensor_shape { - } - float_val: 0.0 - } - } - } -} -node { - name: "DW2/Initializer/random_normal/stddev" - op: "Const" - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } - attr { - key: "dtype" - value { - type: DT_FLOAT - } - } - attr { - key: "value" - value { - tensor { - dtype: DT_FLOAT - tensor_shape { - } - float_val: 0.0010000000475 - } - } - } -} -node { - name: "DW2/Initializer/random_normal/RandomStandardNormal" - op: "RandomStandardNormal" - input: "DW2/Initializer/random_normal/shape" - attr { - key: "T" - value { - type: DT_INT32 - } - } - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } - attr { - key: "dtype" - value { - type: DT_FLOAT - } - } - attr { - key: "seed" - value { - i: 87654321 - } - } - attr { - key: "seed2" - value { - i: 15 - } - } -} -node { - name: "DW2/Initializer/random_normal/mul" - op: "Mul" - input: "DW2/Initializer/random_normal/RandomStandardNormal" - input: "DW2/Initializer/random_normal/stddev" - attr { - key: "T" - value { - type: DT_FLOAT - } - } - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } -} -node { - name: "DW2/Initializer/random_normal" - op: "Add" - input: "DW2/Initializer/random_normal/mul" - input: "DW2/Initializer/random_normal/mean" - attr { - key: "T" - value { - type: DT_FLOAT - } - } - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } -} -node { - name: "DW2/Assign" - op: "Assign" - input: "DW2" - input: "DW2/Initializer/random_normal" - attr { - key: "T" - value { - type: DT_FLOAT - } - } - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } - attr { - key: "use_locking" - value { - b: true - } - } - attr { - key: "validate_shape" - value { - b: true - } - } -} -node { - name: "DW2/read" - op: "Identity" - input: "DW2" - attr { - key: "T" - value { - type: DT_FLOAT - } - } - attr { - key: "_class" - value { - list { - s: "loc:@DW2" - } - } - } -} -node { - name: "Conv2D_1" - op: "Conv2D" - input: "Conv2D" - input: "DW2/read" - attr { - key: "T" - value { - type: DT_FLOAT - } - } - attr { - key: "data_format" - value { - s: "NHWC" - } - } - attr { - key: "padding" - value { - s: "SAME" - } - } - attr { - key: "strides" - value { - list { - i: 1 - i: 2 - i: 2 - i: 1 - } - } - } - attr { - key: "use_cudnn_on_gpu" - value { - b: true - } - } -} -versions { - producer: 13 -} diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/run_meta b/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/run_meta deleted file mode 100644 index 2d5bb7ddaf..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/run_meta +++ /dev/null @@ -1,22 +0,0 @@ - - - -%/job:localhost/replica:0/task:0/cpu:0: -_SOURCE (2 -cpuB_SOURCE = NoOp()H塈a -zeros (2 -cpu:(&"cpu0 Bzeros = Const()H^ -DW (2 -cpu:(&"cpu0ੀ BDW = Variable()H` -DW2 (2 -cpu:(& " cpu0 BDW2 = Variable()Hj -DW/read (2 -cpu:(&"cpu0ੀ BDW/read = Identity(DW)Hm -DW2/read (2 -cpu:(& " cpu0 BDW2/read = Identity(DW2)Hs -Conv2D P(U2 -cpu:(&"cpu0ી B Conv2D = Conv2D(zeros, DW/read)H{ -Conv2D_1 (2 -cpu:(& "cpu0 B#Conv2D_1 = Conv2D(Conv2D, DW2/read)H6 -_SINK (2 -cpuB_SINK = NoOp()H
\ No newline at end of file diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/tfprof_log b/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/tfprof_log deleted file mode 100644 index c35d4338e9..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/testdata/tfprof_log +++ /dev/null @@ -1,9 +0,0 @@ - -
-Conv2D_1$ - -DW2_trainable_variables - -DW_trainable_variables - -Conv2D-
\ No newline at end of file diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h deleted file mode 100644 index 169ebae4a7..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h +++ /dev/null @@ -1,37 +0,0 @@ -/* 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. -==============================================================================*/ - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_CONSTANTS_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_CONSTANTS_H_ - -namespace tensorflow { -namespace tfprof { - -// Op name of root of everything. Aggregates all stats. -static const char* const kTFProfRoot = "_TFProfRoot"; -// Op type for nodes that doesn't represent a physical node in the -// TensorFlow model. Only exist as a placehold to aggregate children. -// For example, kTFProfRoot belongs to this type. -static const char* const kTFGraphParent = "_TFGraphParent"; -static const char* const kTFScopeParent = "_kTFScopeParent"; -// Op type for tf.trainable_variables(). -static const char* const kTrainableVarType = "_trainable_variables"; -// Op type for tensors in the checkpoint file. -static const char* const kCkptVarType = "_checkpoint_variables"; - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_CONSTANTS_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.cc deleted file mode 100644 index 287fd78d46..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.cc +++ /dev/null @@ -1,222 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.h" - -#include <stdio.h> -#include <utility> - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h" -#include "tensorflow/core/lib/strings/strcat.h" -#include "tensorflow/core/lib/strings/stringprintf.h" -#include "tensorflow/core/platform/regexp.h" - -namespace tensorflow { -namespace tfprof { -GraphNode* TFGraph::CreateParentNode(const string& name) { - node_defs_.push_back(std::unique_ptr<NodeDef>(new NodeDef())); - node_defs_.back()->set_name(name); - node_defs_.back()->set_op(kTFGraphParent); - parent_nodes_[name] = - std::unique_ptr<TFNode>(new TFNode(node_defs_.back().get())); - nodes_map_[name] = - std::unique_ptr<GraphNode>(new GraphNode(parent_nodes_[name].get())); - return nodes_map_[name].get(); -} - -void TFGraph::AddNode(TFNode* node) { - string name = node->node_def()->name(); - nodes_map_[name] = std::unique_ptr<GraphNode>(new GraphNode(node)); -} - -void TFGraph::Build() { - if (!roots_.empty()) return; - - std::set<string> nonroots; - // Filter out the root nodes (node not input of any other node). - for (auto it = nodes_map_.begin(); it != nodes_map_.end(); it++) { - GraphNode* node = it->second.get(); - const std::map<string, TFNode*>& inputs = node->node->inputs(); - for (auto inputs_it = inputs.cbegin(); inputs_it != inputs.cend(); - inputs_it++) { - nonroots.insert(inputs_it->first); - auto child_it = nodes_map_.find(inputs_it->first); - if (child_it != nodes_map_.end()) { - node->children.push_back(child_it->second.get()); - } - } - } - for (auto it = nodes_map_.begin(); it != nodes_map_.end(); it++) { - if (nonroots.find(it->first) == nonroots.end()) { - roots_.push_back(it->second.get()); - } - } -} - -const ShowNode* TFGraph::ShowInternal(const Options& opts) { - // Search the nodes to start from. - std::vector<GraphNode*> roots = roots_; - if (opts.start_name_regexes.size() != 1 || - opts.start_name_regexes[0] != ".*") { - std::set<string> visited; - roots = SearchRoot(roots, opts.start_name_regexes, &visited); - } - - GraphNode* root = CreateParentNode(kTFProfRoot); - root->children.assign(roots.begin(), roots.end()); - - std::map<string, int64> account_visits; - Account({root}, opts, &account_visits); - - if (opts.viz) { - printf("Visualizing feature disabled...\n"); - } - std::set<string> visits; - return PrintGraph({root}, opts, 1, 0, 0, &visits)[0]; -} - -std::vector<GraphNode*> TFGraph::SearchRoot( - const std::vector<GraphNode*>& roots, const std::vector<string>& regexes, - std::set<string>* visited) { - std::vector<GraphNode*> res; - if (roots.empty()) { - return res; - } - for (GraphNode* root : roots) { - if (visited->find(root->name()) != visited->end()) continue; - visited->insert(root->name()); - // If the parent is a start point, don't search its children. - // Note that its children can still be added as start node through - // another route. - bool match_start_node = false; - for (const string& regex : regexes) { - if (RE2::FullMatch(root->name(), regex)) { - res.push_back(root); - match_start_node = true; - break; - } - } - if (match_start_node) { - continue; - } - std::vector<GraphNode*> nroot = - SearchRoot(root->children, regexes, visited); - res.insert(res.end(), nroot.begin(), nroot.end()); - } - return res; -} - -std::vector<GraphNode*> TFGraph::PrintGraph(const std::vector<GraphNode*> roots, - const Options& opts, int depth, - int hidden, int last_ident, - std::set<string>* visits) { - std::vector<GraphNode*> show_nodes; - - for (GraphNode* node : roots) { - if (visits->find(node->name()) != visits->end()) continue; - visits->insert(node->name()); - - int nhidden = hidden; - int nlast_ident = last_ident; - bool show = ShouldShow(node, opts, depth); - if (show) { - node->formatted_str.clear(); - if (opts.account_displayed_op_only) { - node->ResetTotalStats(); - node->AddSelfToTotalStats(); - } - nhidden = 0; - nlast_ident = (hidden && opts.select.find(kShown[4]) != opts.select.end() - ? last_ident + 4 - : last_ident + 2); - } else { - ++nhidden; - } - - std::vector<GraphNode*> show_cnodes; - if (!ShouldTrim(node, opts.trim_name_regexes)) { - show_cnodes = PrintGraph(node->children, opts, depth + 1, nhidden, - nlast_ident, visits); - } - if (show) { - show_cnodes = SortNodes(show_cnodes, opts); - string children_str; - for (GraphNode* sc : show_cnodes) { - children_str += sc->formatted_str; - node->mutable_proto()->add_children()->MergeFrom(sc->proto()); - if (opts.account_displayed_op_only) { - node->AggregateTotalStats(sc); - } - } - if (hidden && opts.select.find(kShown[4]) != opts.select.end()) { - node->formatted_str = strings::Printf( - "%s...hidden %d...\n", string(last_ident, ' ').c_str(), hidden); - node->formatted_str += - strings::Printf(" %s%s\n", string(last_ident, ' ').c_str(), - node->Format(opts).c_str()); - } else { - node->formatted_str = - strings::Printf("%s%s\n", string(last_ident, ' ').c_str(), - node->Format(opts).c_str()); - } - if (opts.select.find(kShown[5]) != opts.select.end()) { - std::unique_ptr<TFProfTensor> tfprof_tensor; - if (LookUpCheckPoint(node->name(), &tfprof_tensor)) { - string value_str; - tfprof_tensor->Display(&value_str, - node->mutable_proto()->mutable_tensor_value()); - node->formatted_str += value_str; - } - } - - node->formatted_str += children_str; - show_nodes.push_back(node); - } else { - show_nodes.insert(show_nodes.end(), show_cnodes.begin(), - show_cnodes.end()); - } - } - return show_nodes; -} - -void TFGraph::Account(const std::vector<GraphNode*>& roots, const Options& opts, - std::map<string, int64>* visits) { - if (roots.empty()) return; - - for (GraphNode* node : roots) { - if (visits->find(node->name()) != visits->end()) continue; - (*visits)[node->name()] = 1; - node->ResetTotalStats(); - // Depth-firsth. - Account(node->children, opts, visits); - - node->account = ShouldAccount(node, opts); - if (node->account) { - node->AddSelfToTotalStats(); - } - // Aggregate its children stats. - for (GraphNode* c : node->children) { - // A node can be visited from multiple parents. Only account once. - // "visits==1" is when the node is visited through depth-first search. - (*visits)[c->name()] += 1; - if ((*visits)[c->name()] > 2) continue; - - node->AggregateTotalStats(c); - } - } -} -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.h deleted file mode 100644 index ee54534f56..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.h +++ /dev/null @@ -1,116 +0,0 @@ -/* 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. -==============================================================================*/ - -// Build a graph structure based on op inputs/outputs. The graph is a directed -// acyclic graph pointing *from outputs to inputs*. - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_GRAPH_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_GRAPH_H_ - -#include <deque> -#include <map> -#include <memory> -#include <set> -#include <string> -#include <vector> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/core/errors.h" - -namespace tensorflow { -namespace tfprof { -class GraphNode : public ShowNode { - public: - explicit GraphNode(TFNode* node) : ShowNode(node) { - mutable_proto()->set_inputs(node->inputs().size()); - mutable_proto()->set_total_inputs(0); - } - - void AggregateTotalStats(GraphNode* node) { - ShowNode::AggregateTotalStats(node); - mutable_proto()->set_total_inputs(proto().total_inputs() + - node->proto().total_inputs() + 1); - } - - void AddSelfToTotalStats() { - ShowNode::AddSelfToTotalStats(); - mutable_proto()->set_total_inputs(proto().total_inputs() + - proto().inputs()); - } - - void ResetTotalStats() { - ShowNode::ResetTotalStats(); - mutable_proto()->set_total_inputs(0); - } - - std::vector<GraphNode*> children; -}; - -// Organize tensorflow ops in a graph structure, pointing from output ops -// to input ops. -class TFGraph : public TFShow { - public: - explicit TFGraph(checkpoint::CheckpointReader* ckpt_reader) - : TFShow(ckpt_reader) {} - ~TFGraph() override {} - - void AddNode(TFNode* node) override; - - void Build() override; - - private: - const ShowNode* ShowInternal(const Options& opts) override; - - bool ShouldShowIfExtra(ShowNode* node, const Options& opts, - int depth) override { - return true; - } - - GraphNode* CreateParentNode(const string& name); - - std::vector<GraphNode*> SearchRoot(const std::vector<GraphNode*>& roots, - const std::vector<string>& regexes, - std::set<string>* visited); - - std::vector<GraphNode*> PrintGraph(const std::vector<GraphNode*> roots, - const Options& opts, int depth, int hidden, - int last_ident, std::set<string>* visits); - - void VisualizeGraph(GraphNode* root, const Options& opts); - - std::vector<GraphNode*> GenerateGraphDot( - GraphNode* root, GraphNode* last_shown, const Options& opts, int depth, - int hidden, std::set<string>* declared_nodes, - std::set<string>* declared_edges, TFProfNode* parent); - - void Account(const std::vector<GraphNode*>& roots, const Options& opts, - std::map<string, int64>* visits); - - std::vector<GraphNode*> roots_; - std::vector<std::unique_ptr<NodeDef>> node_defs_; - std::map<string, std::unique_ptr<TFNode>> parent_nodes_; - std::map<string, std::unique_ptr<GraphNode>> nodes_map_; -}; - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_GRAPH_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.cc deleted file mode 100644 index 0e8ab366cb..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.cc +++ /dev/null @@ -1,47 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h" - -#include "tensorflow/core/framework/allocation_description.pb.h" -#include "tensorflow/core/framework/tensor_description.pb.h" - -namespace tensorflow { -namespace tfprof { -void TFNode::AddStepStat(const string& device, const NodeExecStats* step_stat) { - if (!device.empty()) { - // This might override device from GraphDef. - device_ = device; - } - step_stat_ = step_stat; - - op_start_micros_ = step_stat_->all_start_micros(); - if (step_stat_->op_end_rel_micros() && step_stat_->op_start_rel_micros()) { - op_exec_micros_ = - step_stat_->op_end_rel_micros() - step_stat_->op_start_rel_micros(); - } - all_spent_micros_ = step_stat_->all_end_rel_micros(); - - for (const auto& output : step_stat_->output()) { - if (output.has_tensor_description() && - output.tensor_description().has_allocation_description()) { - requested_bytes_ += output.tensor_description() - .allocation_description() - .requested_bytes(); - } - } -} -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h deleted file mode 100644 index c8a8f5e7ec..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h +++ /dev/null @@ -1,106 +0,0 @@ -/* 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. -==============================================================================*/ - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_NODE_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_NODE_H_ - -#include <map> -#include <set> -#include <string> -#include <vector> - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/core/framework/allocation_description.pb.h" -#include "tensorflow/core/framework/attr_value.pb.h" -#include "tensorflow/core/framework/node_def.pb.h" -#include "tensorflow/core/framework/step_stats.pb.h" -#include "tensorflow/core/framework/tensor_description.pb.h" -#include "tensorflow/core/framework/tensor_shape.pb.h" -#include "tensorflow/core/lib/core/errors.h" - -namespace tensorflow { -namespace tfprof { - -class TFNode { - public: - TFNode(const NodeDef* node) - : node_(node), - step_stat_(nullptr), - op_start_micros_(0), - op_exec_micros_(0), - all_spent_micros_(0), - requested_bytes_(0), - float_ops_(0) { - if (!node) return; - - for (const auto& attr : node->attr()) { - // TODO(xpan): Also consider _output_shapes. - if (attr.first != "shape" || !attr.second.has_shape()) continue; - if (!shape_.empty()) { - fprintf(stderr, "Found duplicated shapes!\n"); - continue; - } - std::vector<int64> shape_vec; - for (const auto& d : attr.second.shape().dim()) { - shape_vec.push_back(d.size()); - } - update_shape(shape_vec); - } - op_types_.insert(node->op()); - device_ = node->device(); - } - - TFNode() : TFNode(nullptr) {} - - void AddInput(TFNode* input) { inputs_[input->node_def()->name()] = input; } - - void AddOpType(const string& op_type) { op_types_.insert(op_type); } - - void AddStepStat(const string& device, const NodeExecStats* step_stat); - - void AddFloatOps(int64 float_ops) { float_ops_ = float_ops; } - - const NodeDef* node_def() { return node_; } - const std::map<string, TFNode*>& inputs() { return inputs_; } - int64 op_start_micros() { return op_start_micros_; } - int64 op_exec_micros() { return op_exec_micros_; } - int64 all_spent_micros() { return all_spent_micros_; } - int64 requested_byptes() { return requested_bytes_; } - int64 float_ops() { return float_ops_; } - string device() { return device_; } - const std::set<string>& op_types() { return op_types_; } - - const std::vector<int64>& shape() { return shape_; } - void update_shape(const std::vector<int64>& shape) { shape_ = shape; } - - private: - std::map<string, TFNode*> inputs_; - const NodeDef* node_; - const NodeExecStats* step_stat_; - - std::vector<int64> shape_; - std::set<string> op_types_; - string device_; - int64 op_start_micros_; - int64 op_exec_micros_; - int64 all_spent_micros_; - int64 requested_bytes_; - int64 float_ops_; -}; - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_NODE_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.cc deleted file mode 100644 index 2574415fdd..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.cc +++ /dev/null @@ -1,57 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" - -#include "tensorflow/core/lib/strings/stringprintf.h" - -namespace tensorflow { -namespace tfprof { - -string Options::ToString() const { - const string s = strings::Printf( - "%-28s%d\n" - "%-28s%lld\n" - "%-28s%lld\n" - "%-28s%lld\n" - "%-28s%lld\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n" - "%-28s%s\n", - kOptions[0], max_depth, kOptions[1], min_bytes, kOptions[2], min_micros, - kOptions[3], min_params, kOptions[4], min_float_ops, kOptions[5], - str_util::Join(device_regexes, ",").c_str(), kOptions[6], - order_by.c_str(), kOptions[7], - str_util::Join(account_type_regexes, ",").c_str(), kOptions[8], - str_util::Join(start_name_regexes, ",").c_str(), kOptions[9], - str_util::Join(trim_name_regexes, ",").c_str(), kOptions[10], - str_util::Join(show_name_regexes, ",").c_str(), kOptions[11], - str_util::Join(hide_name_regexes, ",").c_str(), kOptions[12], - (account_displayed_op_only ? "true" : "false"), kOptions[13], - str_util::Join(select, ",").c_str(), kOptions[14], - (viz ? "true" : "false"), kOptions[15], dump_to_file.c_str()); - return s; -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h deleted file mode 100644 index a0c52e6d1a..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h +++ /dev/null @@ -1,119 +0,0 @@ -/* 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. -==============================================================================*/ - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_OPTIONS_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_OPTIONS_H_ - -#include <set> -#include <string> -#include <utility> -#include <vector> - -#include "tensorflow/core/framework/types.h" -#include "tensorflow/core/lib/core/errors.h" -#include "tensorflow/core/lib/strings/str_util.h" - -namespace tensorflow { -namespace tfprof { -static const char* const kOptions[] = { - "-max_depth", - "-min_bytes", - "-min_micros", - "-min_params", - "-min_float_ops", - "-device_regexes", - "-order_by", - "-account_type_regexes", - "-start_name_regexes", - "-trim_name_regexes", - "-show_name_regexes", - "-hide_name_regexes", - "-account_displayed_op_only", - "-select", - "-viz", - "-dump_to_file", -}; - -static const char* const kOrderBy[] = { - "name", "bytes", "micros", "params", "float_ops", -}; - -// Append Only. -static const char* const kShown[] = { - "bytes", "micros", "params", "float_ops", - "num_hidden_ops", "tensor_value", "device", "op_types", -}; - -static const char* const kCmds[] = { - "scope", "graph", "set", "help", -}; - -struct Options { - public: - virtual ~Options() {} - Options(int max_depth, tensorflow::int64 min_bytes, - tensorflow::int64 min_micros, tensorflow::int64 min_params, - tensorflow::int64 min_float_ops, - const std::vector<string>& device_regexes, const string& order_by, - const std::vector<string>& account_type_regexes, - const std::vector<string>& start_name_regexes, - const std::vector<string>& trim_name_regexes, - const std::vector<string>& show_name_regexes, - const std::vector<string>& hide_name_regexes, - bool account_displayed_op_only, const std::vector<string>& select, - bool viz, const string& dump_to_file = "") - : max_depth(max_depth), - min_bytes(min_bytes), - min_micros(min_micros), - min_params(min_params), - min_float_ops(min_float_ops), - device_regexes(device_regexes), - order_by(order_by), - account_type_regexes(account_type_regexes), - start_name_regexes(start_name_regexes), - trim_name_regexes(trim_name_regexes), - show_name_regexes(show_name_regexes), - hide_name_regexes(hide_name_regexes), - account_displayed_op_only(account_displayed_op_only), - select(select.begin(), select.end()), - viz(viz), - dump_to_file(dump_to_file) {} - - string ToString() const; - - int max_depth; - tensorflow::int64 min_bytes; - tensorflow::int64 min_micros; - tensorflow::int64 min_params; - tensorflow::int64 min_float_ops; - std::vector<string> device_regexes; - string order_by; - - std::vector<string> account_type_regexes; - std::vector<string> start_name_regexes; - std::vector<string> trim_name_regexes; - std::vector<string> show_name_regexes; - std::vector<string> hide_name_regexes; - bool account_displayed_op_only; - - std::set<string> select; - bool viz; - string dump_to_file; -}; - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_OPTIONS_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.cc deleted file mode 100644 index 6b2bc298cc..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.cc +++ /dev/null @@ -1,191 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.h" - -#include <stdio.h> -#include <utility> - -#include "tensorflow/c/c_api.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h" -#include "tensorflow/core/framework/tensor.h" -#include "tensorflow/core/lib/strings/stringprintf.h" -#include "tensorflow/core/platform/regexp.h" - -namespace tensorflow { -namespace tfprof { -ScopeNode* TFScope::CreateParentNode(const string& name) { - if (nodes_map_.find(name) != nodes_map_.end()) { - return nodes_map_[name].get(); - } - node_defs_.push_back(std::unique_ptr<NodeDef>(new NodeDef())); - node_defs_.back()->set_name(name); - node_defs_.back()->set_op(kTFScopeParent); - parent_nodes_[name] = - std::unique_ptr<TFNode>(new TFNode(node_defs_.back().get())); - nodes_map_[name] = - std::unique_ptr<ScopeNode>(new ScopeNode(parent_nodes_[name].get())); - return nodes_map_[name].get(); -} - -void TFScope::AddNode(TFNode* node) { - string name = node->node_def()->name(); - if (nodes_map_.find(node->node_def()->name()) == nodes_map_.end()) { - nodes_map_[name] = std::unique_ptr<ScopeNode>(new ScopeNode(node)); - } - - auto last_slash = name.find_last_of("/"); - while (last_slash != name.npos) { - name = name.substr(0, last_slash); - if (nodes_map_.find(name) == nodes_map_.end()) { - CHECK(CreateParentNode(name)); - } - last_slash = name.find_last_of("/"); - } -} - -void TFScope::Build() { - if (!roots_.empty()) return; - // Found roots, which are nodes without "/". - for (auto it = nodes_map_.begin(); it != nodes_map_.end(); it++) { - ScopeNode* node = it->second.get(); - auto last_slash = node->name().find_last_of("/"); - if (last_slash == string::npos) { - roots_.push_back(node); - } else { - const string prefix = node->name().substr(0, last_slash); - nodes_map_[prefix]->children.push_back(node); - } - } -} - -const ShowNode* TFScope::ShowInternal(const Options& opts) { - // Search from roots recursively to find start node, if start_name_regexes - // is specified. - std::vector<ScopeNode*> roots = roots_; - if (opts.start_name_regexes.size() != 1 || - opts.start_name_regexes[0] != ".*") { - roots = SearchRoot(roots, opts.start_name_regexes); - } - - ScopeNode* root = CreateParentNode(kTFProfRoot); - root->children.assign(roots.begin(), roots.end()); - Account({root}, opts); - - root = PrintScope({root}, opts, 1, 0)[0]; - return root; -} - -std::vector<ScopeNode*> TFScope::SearchRoot( - std::vector<ScopeNode*> roots, const std::vector<string>& regexes) { - std::vector<ScopeNode*> res; - if (roots.empty()) { - return res; - } - for (ScopeNode* root : roots) { - bool match_start_node = false; - for (const string& regex : regexes) { - if (RE2::FullMatch(root->name(), regex)) { - res.push_back(root); - match_start_node = true; - break; - } - } - if (match_start_node) { - // Found a start node at this branch, no need to continue. - continue; - } - std::vector<ScopeNode*> nroots = SearchRoot(root->children, regexes); - res.insert(res.end(), nroots.begin(), nroots.end()); - } - return res; -} - -std::vector<ScopeNode*> TFScope::PrintScope(const std::vector<ScopeNode*> roots, - const Options& opts, int depth, - int last_ident) { - std::vector<ScopeNode*> show_nodes; - - for (ScopeNode* node : roots) { - int nlast_ident = last_ident; - bool show = ShouldShow(node, opts, depth); - if (show) { - node->formatted_str.clear(); - if (opts.account_displayed_op_only) { - node->ResetTotalStats(); - node->AddSelfToTotalStats(); - } - nlast_ident += 2; - } - - std::vector<ScopeNode*> show_cnodes; - if (!ShouldTrim(node, opts.trim_name_regexes)) { - show_cnodes = PrintScope(node->children, opts, depth + 1, nlast_ident); - } - if (show) { - show_cnodes = SortNodes(show_cnodes, opts); - string children_str; - for (ScopeNode* sc : show_cnodes) { - children_str += sc->formatted_str; - node->mutable_proto()->add_children()->MergeFrom(sc->proto()); - if (opts.account_displayed_op_only) { - node->AggregateTotalStats(sc); - } - } - - node->formatted_str = - strings::Printf("%s%s\n", string(last_ident, ' ').c_str(), - node->Format(opts).c_str()); - - if (opts.select.find(kShown[5]) != opts.select.end()) { - std::unique_ptr<TFProfTensor> tfprof_tensor; - if (LookUpCheckPoint(node->name(), &tfprof_tensor)) { - string value_str; - tfprof_tensor->Display(&value_str, - node->mutable_proto()->mutable_tensor_value()); - node->formatted_str += value_str; - } - } - - node->formatted_str += children_str; - show_nodes.push_back(node); - } else { - show_nodes.insert(show_nodes.end(), show_cnodes.begin(), - show_cnodes.end()); - } - } - return show_nodes; -} - -void TFScope::Account(const std::vector<ScopeNode*>& roots, - const Options& opts) { - if (roots.empty()) return; - - for (ScopeNode* node : roots) { - node->ResetTotalStats(); - Account(node->children, opts); - - node->account = ShouldAccount(node, opts); - if (node->account) { - node->AddSelfToTotalStats(); - } - for (ScopeNode* c : node->children) { - node->AggregateTotalStats(c); - } - } -} -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.h deleted file mode 100644 index 3a8ca52b43..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.h +++ /dev/null @@ -1,88 +0,0 @@ -/* 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. -==============================================================================*/ - -// Build a tree structure based on the TensorFlow op names. -// For example, 'name1/name2' is a child of 'name1'. -// Stats are aggregated from descendants from ancestors. - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_SCOPE_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_SCOPE_H_ - -#include <map> -#include <memory> -#include <string> -#include <vector> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/core/errors.h" - -namespace tensorflow { -namespace tfprof { - -class ScopeNode : public ShowNode { - public: - explicit ScopeNode(TFNode* node) : ShowNode(node) {} - ~ScopeNode() override {} - - void AggregateTotalStats(ScopeNode* node) { - ShowNode::AggregateTotalStats(node); - } - - void AddSelfToTotalStats() { ShowNode::AddSelfToTotalStats(); } - - void ResetTotalStats() { ShowNode::ResetTotalStats(); } - - std::vector<ScopeNode*> children; -}; - -class TFScope : public TFShow { - public: - explicit TFScope(checkpoint::CheckpointReader* ckpt_reader) - : TFShow(ckpt_reader) {} - ~TFScope() override {} - - void AddNode(TFNode* node) override; - - void Build() override; - - private: - const ShowNode* ShowInternal(const Options& opts) override; - - ScopeNode* CreateParentNode(const string& name); - - std::vector<ScopeNode*> SearchRoot(std::vector<ScopeNode*> roots, - const std::vector<string>& regexes); - - std::vector<ScopeNode*> PrintScope(const std::vector<ScopeNode*> roots, - const Options& opts, int depth, - int last_ident); - - void Account(const std::vector<ScopeNode*>& roots, const Options& opts); - - std::vector<ScopeNode*> roots_; - std::vector<std::unique_ptr<NodeDef>> node_defs_; - std::map<string, std::unique_ptr<TFNode>> parent_nodes_; - std::map<string, std::unique_ptr<ScopeNode>> nodes_map_; -}; -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_SCOPE_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.cc deleted file mode 100644 index f7275d8ae4..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.cc +++ /dev/null @@ -1,266 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h" - -#include <memory> -#include <set> - -#include "tensorflow/core/lib/strings/str_util.h" -#include "tensorflow/core/lib/strings/stringprintf.h" -#include "tensorflow/core/platform/env.h" -#include "tensorflow/core/platform/regexp.h" - -namespace tensorflow { -namespace tfprof { -ShowNode::ShowNode(TFNode* node) : node(node), account(true) { - mutable_proto()->set_name(name()); - if (!node->device().empty()) { - mutable_proto()->set_device(node->device()); - } - mutable_proto()->set_exec_micros(node->op_exec_micros()); - mutable_proto()->set_requested_bytes(node->requested_byptes()); - mutable_proto()->set_float_ops(node->float_ops()); - - if (!node->shape().empty()) { - int64 params = 1; - bool complete_shape = true; - for (int64 d : node->shape()) { - // Sometimes parameters could be <0 when a dim is unknown. - if (d < 0) { - complete_shape = false; - break; - } - params *= d; - } - if (complete_shape) { - mutable_proto()->set_parameters(proto_.parameters() + params); - } else { - fprintf(stderr, "Incomplete shape."); - } - } -} - -string ShowNode::Format(const Options& opts) { - if (opts.select.empty()) { - return name(); - } - return strings::Printf("%s (%s)", name().c_str(), FormatMeta(opts).c_str()); -} - -string ShowNode::FormatMeta(const Options& opts) { - std::vector<string> info; - if (opts.select.find(kShown[2]) != opts.select.end()) { - const string shape = FormatShapes(node->shape()); - if (!shape.empty()) { - info.push_back(shape); - } - string params = FormatNumber(proto().total_parameters()) + " params"; - if (account) { - params = FormatNumber(proto().parameters()) + "/" + params; - } else { - params = "--/" + params; - } - info.push_back(params); - } - if (opts.select.find(kShown[3]) != opts.select.end()) { - string fops = FormatNumber(proto().total_float_ops()) + " flops"; - if (account) { - fops = FormatNumber(proto().float_ops()) + "/" + fops; - } else { - fops = "--/" + fops; - } - info.push_back(fops); - } - if (opts.select.find(kShown[0]) != opts.select.end()) { - string memory = FormatMemory(proto().total_requested_bytes()); - if (account) { - memory = FormatMemory(proto().requested_bytes()) + "/" + memory; - - } else { - memory = "--/" + memory; - } - info.push_back(memory); - } - if (opts.select.find(kShown[1]) != opts.select.end()) { - string time = FormatTime(proto().total_exec_micros()); - if (account) { - time = FormatTime(proto().exec_micros()) + "/" + time; - } else { - time = "--/" + time; - } - info.push_back(time); - } - if (opts.select.find(kShown[6]) != opts.select.end()) { - if (!proto().device().empty()) { - info.push_back(proto().device()); - } - } - if (opts.select.find(kShown[7]) != opts.select.end()) { - std::set<string> op_types = node->op_types(); - // Device is considered a type. - if (!proto().device().empty()) { - op_types.insert(proto().device()); - } - info.push_back(str_util::Join(op_types, "|")); - } - return str_util::Join(info, ", "); -} - -TFProfNode* ShowNode::mutable_proto() { return &proto_; } - -const TFProfNode& ShowNode::proto() const { return proto_; } - -void ShowNode::AggregateTotalStats(ShowNode* node) { - TFProfNode* node_pb = node->mutable_proto(); - mutable_proto()->set_total_exec_micros(proto().total_exec_micros() + - node_pb->total_exec_micros()); - mutable_proto()->set_total_requested_bytes(proto().total_requested_bytes() + - node_pb->total_requested_bytes()); - mutable_proto()->set_total_parameters(proto().total_parameters() + - node_pb->total_parameters()); - mutable_proto()->set_total_float_ops(proto().total_float_ops() + - node_pb->total_float_ops()); -} - -void ShowNode::AddSelfToTotalStats() { - mutable_proto()->set_total_exec_micros(proto().total_exec_micros() + - proto().exec_micros()); - mutable_proto()->set_total_requested_bytes(proto().total_requested_bytes() + - proto().requested_bytes()); - mutable_proto()->set_total_parameters(proto().total_parameters() + - proto().parameters()); - mutable_proto()->set_total_float_ops(proto().total_float_ops() + - proto().float_ops()); -} - -void ShowNode::ResetTotalStats() { - mutable_proto()->set_total_exec_micros(0); - mutable_proto()->set_total_requested_bytes(0); - mutable_proto()->set_total_parameters(0); - mutable_proto()->set_total_float_ops(0); -} - -const TFProfNode& TFShow::Show(const Options& opts) { - const ShowNode* root = ShowInternal(opts); - if (opts.dump_to_file.empty()) { - printf("%s", root->formatted_str.c_str()); - fflush(stdout); - } else { - Status s = WriteStringToFile(Env::Default(), opts.dump_to_file, - root->formatted_str); - if (!s.ok()) { - fprintf(stderr, "%s\n", s.ToString().c_str()); - } - } - return root->proto(); -} - -bool TFShow::LookUpCheckPoint(const string& name, - std::unique_ptr<TFProfTensor>* tensor) { - if (name == kTFProfRoot || !ckpt_reader_ || !tensor) { - return false; - } - std::unique_ptr<Tensor> out_tensor; - TF_Status* status = TF_NewStatus(); - ckpt_reader_->GetTensor(name, &out_tensor, status); - if (TF_GetCode(status) != TF_OK) { - fprintf(stderr, "%s\n", TF_Message(status)); - TF_DeleteStatus(status); - return false; - } - tensor->reset(new TFProfTensor(std::move(out_tensor))); - TF_DeleteStatus(status); - return true; -} - -bool TFShow::ShouldShow(ShowNode* node, const Options& opts, int depth) { - // Always show kTFProfRoot. - if (node->name() == kTFProfRoot) return true; - - if (!node->account) return false; - - if (node->proto().requested_bytes() < opts.min_bytes || - node->proto().exec_micros() < opts.min_micros || - node->proto().parameters() < opts.min_params || - node->proto().float_ops() < opts.min_float_ops || - depth > opts.max_depth || !ShouldShowIfExtra(node, opts, depth)) { - return false; - } - - bool show = false; - if (opts.device_regexes.size() == 1 && opts.device_regexes[0] == ".*") { - show = true; - } else { - for (const string& regex : opts.device_regexes) { - if (RE2::FullMatch(node->proto().device(), regex)) { - show = true; - break; - } - } - } - // Don't show if device_regexes don't cover it. - if (!show) return false; - - show = false; - if (opts.show_name_regexes.size() == 1 && opts.show_name_regexes[0] == ".*") { - show = true; - } else { - for (const string& regex : opts.show_name_regexes) { - if (RE2::FullMatch(node->name(), regex)) { - show = true; - break; - } - } - } - // Don't show if show_name_regexes don't cover it. - if (!show) return false; - // Don't show if hide_name_regexes cover it. - for (const string& regex : opts.hide_name_regexes) { - if (RE2::FullMatch(node->name(), regex)) return false; - } - return true; -} - -bool TFShow::ShouldTrim(ShowNode* node, const std::vector<string>& regexes) { - for (const string& regex : regexes) { - if (RE2::FullMatch(node->name(), regex)) { - return true; - } - } - return false; -} - -bool TFShow::ShouldAccount(ShowNode* node, const Options& opts) { - if (opts.account_type_regexes.size() == 1 && - opts.account_type_regexes[0] == ".*") { - return true; - } - for (const string& regex : opts.account_type_regexes) { - for (const string& type : node->node->op_types()) { - if (RE2::FullMatch(type, regex)) { - return true; - } - } - if (RE2::FullMatch(node->proto().device(), regex)) { - return true; - } - } - - return false; -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h deleted file mode 100644 index 4b5d6592e5..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h +++ /dev/null @@ -1,127 +0,0 @@ -/* 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. -==============================================================================*/ - -// Parent class and utilities for tfprof_graph and tfprof_scope. - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_SHOW_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_SHOW_H_ - -#include <algorithm> -#include <string> -#include <vector> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/core/errors.h" -#include "tensorflow/core/lib/strings/stringprintf.h" - -namespace tensorflow { -namespace tfprof { -class ShowNode { - public: - explicit ShowNode(TFNode* node); - virtual ~ShowNode() {} - - const string& name() const { return node->node_def()->name(); } - TFProfNode* mutable_proto(); - const TFProfNode& proto() const; - - string Format(const Options& opts); - - string FormatMeta(const Options& opts); - - TFNode* node; - bool account; - string formatted_str; - - protected: - void AggregateTotalStats(ShowNode* node); - - void AddSelfToTotalStats(); - - void ResetTotalStats(); - - TFProfNode proto_; -}; - -class TFShow { - public: - explicit TFShow(checkpoint::CheckpointReader* ckpt_reader) - : ckpt_reader_(ckpt_reader) {} - virtual ~TFShow() {} - virtual void AddNode(TFNode* node) = 0; - virtual void Build() = 0; - const TFProfNode& Show(const Options& opts); - - protected: - virtual const ShowNode* ShowInternal(const Options& opts) = 0; - - bool LookUpCheckPoint(const string& name, - std::unique_ptr<TFProfTensor>* tensor); - - // Overridden by subclass if extra requirements need to be met. - virtual bool ShouldShowIfExtra(ShowNode* node, const Options& opts, - int depth) { - return true; - } - - bool ShouldShow(ShowNode* node, const Options& opts, int depth); - - bool ShouldTrim(ShowNode* node, const std::vector<string>& regexes); - - bool ShouldAccount(ShowNode* node, const Options& opts); - - template <typename T> - std::vector<T*> SortNodes(const std::vector<T*>& nodes, const Options& opts) { - if (opts.order_by.empty() || nodes.empty()) { - return nodes; - } - std::vector<T*> sorted_nodes = nodes; - std::sort(sorted_nodes.begin(), sorted_nodes.end(), [&opts](const T* n1, - const T* n2) { - if (n1->name() == kTFProfRoot) return true; - if (n2->name() == kTFProfRoot) return false; - bool name_cmp = n1->name() < n2->name(); - if (opts.order_by == kOrderBy[0]) { - return name_cmp; - } else if (opts.order_by == kOrderBy[1]) { - return n1->proto().total_requested_bytes() > - n2->proto().total_requested_bytes(); - } else if (opts.order_by == kOrderBy[2]) { - return n1->proto().total_exec_micros() > - n2->proto().total_exec_micros(); - } else if (opts.order_by == kOrderBy[3]) { - return n1->proto().total_parameters() > n2->proto().total_parameters(); - } else if (opts.order_by == kOrderBy[4]) { - return n1->proto().total_float_ops() > n2->proto().total_float_ops(); - } - return name_cmp; - }); - return sorted_nodes; - } - - checkpoint::CheckpointReader* ckpt_reader_; -}; - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_SHOW_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show_test.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show_test.cc deleted file mode 100644 index 81396e31cc..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show_test.cc +++ /dev/null @@ -1,92 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h" - -#include <utility> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.pb.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/io/path.h" -#include "tensorflow/core/platform/env.h" -#include "tensorflow/core/platform/test.h" -#include "tensorflow/core/protobuf/config.pb.h" - -namespace tensorflow { -namespace tfprof { -class TFProfShowTest : public ::testing::Test { - protected: - TFProfShowTest() { - string graph_path = io::JoinPath( - testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/graph.pbtxt"); - std::unique_ptr<tensorflow::GraphDef> graph_pb(new tensorflow::GraphDef()); - TF_CHECK_OK(ReadGraphDefText(Env::Default(), graph_path, graph_pb.get())); - - std::unique_ptr<tensorflow::RunMetadata> run_meta_pb( - new tensorflow::RunMetadata()); - string run_meta_path = - io::JoinPath(testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/run_meta"); - TF_CHECK_OK( - ReadBinaryProto(Env::Default(), run_meta_path, run_meta_pb.get())); - - std::unique_ptr<OpLog> op_log_pb(new OpLog()); - string op_log_path = io::JoinPath( - testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/tfprof_log"); - TF_CHECK_OK(ReadBinaryProto(Env::Default(), op_log_path, op_log_pb.get())); - - string ckpt_path = - io::JoinPath(testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/ckpt"); - TF_Status* status = TF_NewStatus(); - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader( - new checkpoint::CheckpointReader(ckpt_path, status)); - CHECK(TF_GetCode(status) == TF_OK); - TF_DeleteStatus(status); - - tf_stats_.reset(new TFStats(std::move(graph_pb), std::move(run_meta_pb), - std::move(op_log_pb), std::move(ckpt_reader))); - } - - std::unique_ptr<TFStats> tf_stats_; -}; - -TEST_F(TFProfShowTest, DumpScopeMode) { - string dump_file = io::JoinPath(testing::TmpDir(), "dump"); - Options opts(5, 0, 0, 0, 0, {".*"}, "name", - {"Variable"}, // accout_type_regexes - {".*"}, {""}, {".*"}, {""}, false, - {"params", "bytes", "micros", "float_ops", "num_hidden_ops"}, - false, dump_file); - tf_stats_->PrintGraph("scope", opts); - - string dump_str; - TF_CHECK_OK(ReadFileToString(Env::Default(), dump_file, &dump_str)); - EXPECT_EQ( - "_TFProfRoot (--/450 params, --/0 flops, --/1.80KB, --/0us)\n DW " - "(3x3x3x6, 162/162 params, 0/0 flops, 648B/648B, 0us/0us)\n DW2 " - "(2x2x6x12, 288/288 params, 0/0 flops, 1.15KB/1.15KB, 0us/0us)\n", - dump_str); -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.cc deleted file mode 100644 index 54fce4772b..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.cc +++ /dev/null @@ -1,130 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h" - -#include <stdio.h> -#include <utility> - -#include "tensorflow/core/framework/step_stats.pb.h" - -namespace tensorflow { -namespace tfprof { -TFStats::TFStats(std::unique_ptr<GraphDef> graph, - std::unique_ptr<RunMetadata> run_meta, - std::unique_ptr<OpLog> op_log, - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader) - : graph_(std::move(graph)), - run_meta_(std::move(run_meta)), - op_log_(std::move(op_log)), - ckpt_reader_(std::move(ckpt_reader)) { - CHECK(graph_) << "Must at least have GraphDef"; - - printf("Parsing GraphDef...\n"); - ParseGraph(); - if (run_meta_) { - printf("Parsing RunMetadata...\n"); - ParseRunMeta(); - } - if (op_log_) { - printf("Parsing OpLog...\n"); - ParseOpLog(); - } - - if (ckpt_reader_) { - printf("Parsing Checkpoint...\n"); - for (const auto& v : ckpt_reader_->GetVariableToShapeMap()) { - auto node = nodes_map_.find(v.first); - if (node != nodes_map_.end()) { - node->second.AddOpType("_checkpoint_variables"); - } - } - } - - printf("Preparing Views...\n"); - scope_view_ = std::unique_ptr<TFScope>(new TFScope(ckpt_reader_.get())); - graph_view_ = std::unique_ptr<TFGraph>(new TFGraph(ckpt_reader_.get())); - for (auto it = nodes_map_.begin(); it != nodes_map_.end(); it++) { - scope_view_->AddNode(&it->second); - graph_view_->AddNode(&it->second); - } - scope_view_->Build(); - graph_view_->Build(); -} - -const TFProfNode& TFStats::PrintGraph(const string& cmd, const Options& opts) { - if (cmd == kCmds[0]) { - return scope_view_->Show(opts); - } else if (cmd == kCmds[1]) { - return graph_view_->Show(opts); - } else { - fprintf(stderr, "Unknown command: %s\n", cmd.c_str()); - return empty_node_; - } -} - -void TFStats::ParseGraph() { - for (const NodeDef& node : graph_->node()) { - CHECK(nodes_map_.find(node.name()) == nodes_map_.end()); - nodes_map_[node.name()] = TFNode(&node); - } - for (auto it = nodes_map_.begin(); it != nodes_map_.end(); it++) { - const NodeDef* node_def = it->second.node_def(); - for (string node_input : node_def->input()) { - // input name format can be: "^node:src_output" - auto prefix_pos = node_input.find(":"); - if (prefix_pos != node_input.npos) { - node_input.substr(0, prefix_pos); - } - if (node_input.substr(0, 1) == "^") { - node_input = node_input.substr(1); - } - auto input_node = nodes_map_.find(node_input); - if (input_node == nodes_map_.end()) { - continue; - } - it->second.AddInput(&input_node->second); - } - } -} - -void TFStats::ParseOpLog() { - for (const OpLogEntry& entry : op_log_->log_entries()) { - auto node = nodes_map_.find(entry.name()); - if (node == nodes_map_.end()) continue; - for (const string& type : entry.types()) { - node->second.AddOpType(type); - } - if (entry.float_ops()) { - node->second.AddFloatOps(entry.float_ops()); - } - } -} - -void TFStats::ParseRunMeta() { - if (!run_meta_->has_step_stats()) return; - - for (const auto& dev_stat : run_meta_->step_stats().dev_stats()) { - for (const auto& node_stat : dev_stat.node_stats()) { - auto node = nodes_map_.find(node_stat.node_name()); - if (node == nodes_map_.end()) { - continue; - } - node->second.AddStepStat(dev_stat.device(), &node_stat); - } - } -} -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h deleted file mode 100644 index 1246a2fae2..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h +++ /dev/null @@ -1,82 +0,0 @@ -/* 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. -==============================================================================*/ - -// Core API of tfprof. -// 1. Load protos generated from a tensorflow model. -// 2. Build in-memory representations of the tensorflow model, annotate the -// representation with various stats, such as params,times,memory,etc. -// 3. Accept command and options to selectively aggregate stats for analysis -// and print out the results. - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_STATS_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_STATS_H_ - -#include <map> -#include <memory> -#include <set> -#include <string> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_graph.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_node.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_scope.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_show.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.pb.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/attr_value.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/framework/step_stats.pb.h" -#include "tensorflow/core/lib/core/errors.h" -#include "tensorflow/core/lib/strings/stringprintf.h" -#include "tensorflow/core/protobuf/config.pb.h" - -namespace tensorflow { -namespace tfprof { - -class TFStats { - public: - TFStats(std::unique_ptr<GraphDef> graph, - std::unique_ptr<RunMetadata> run_meta, std::unique_ptr<OpLog> op_log, - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader); - ~TFStats() {} - - // Prints the results to stdout. Also returns the printed output in - // a proto. - const TFProfNode& PrintGraph(const string& cmd, const Options& opts); - - private: - void ParseGraph(); - - void ParseOpLog(); - - void ParseRunMeta(); - - std::unique_ptr<TFScope> scope_view_; - std::unique_ptr<TFGraph> graph_view_; - std::unique_ptr<GraphDef> graph_; - std::unique_ptr<RunMetadata> run_meta_; - std::unique_ptr<OpLog> op_log_; - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader_; - // Store TFNode instead of TFNode* to avoid large number of dynamic alloc. - std::map<string, TFNode> nodes_map_; - TFProfNode empty_node_; -}; - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_STATS_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats_test.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats_test.cc deleted file mode 100644 index 06b288fdce..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats_test.cc +++ /dev/null @@ -1,194 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h" - -#include <utility> - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_constants.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.pb.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/io/path.h" -#include "tensorflow/core/platform/env.h" -#include "tensorflow/core/platform/protobuf.h" -#include "tensorflow/core/platform/test.h" -#include "tensorflow/core/protobuf/config.pb.h" - -namespace tensorflow { -namespace tfprof { -class TFProfStatsTest : public ::testing::Test { - protected: - TFProfStatsTest() { - string graph_path = io::JoinPath( - testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/graph.pbtxt"); - std::unique_ptr<tensorflow::GraphDef> graph_pb(new tensorflow::GraphDef()); - TF_CHECK_OK(ReadGraphDefText(Env::Default(), graph_path, graph_pb.get())); - - std::unique_ptr<tensorflow::RunMetadata> run_meta_pb( - new tensorflow::RunMetadata()); - string run_meta_path = - io::JoinPath(testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/run_meta"); - TF_CHECK_OK( - ReadBinaryProto(Env::Default(), run_meta_path, run_meta_pb.get())); - - std::unique_ptr<OpLog> op_log_pb(new OpLog()); - string op_log_path = io::JoinPath( - testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/tfprof_log"); - TF_CHECK_OK(ReadBinaryProto(Env::Default(), op_log_path, op_log_pb.get())); - - string ckpt_path = - io::JoinPath(testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/ckpt"); - TF_Status* status = TF_NewStatus(); - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader( - new checkpoint::CheckpointReader(ckpt_path, status)); - CHECK(TF_GetCode(status) == TF_OK); - TF_DeleteStatus(status); - - tf_stats_.reset(new TFStats(std::move(graph_pb), std::move(run_meta_pb), - std::move(op_log_pb), std::move(ckpt_reader))); - } - - std::unique_ptr<TFStats> tf_stats_; -}; - -TEST_F(TFProfStatsTest, CustomOpType) { - Options opts(3, 0, 0, 0, 0, {".*"}, "name", - {kTrainableVarType}, // accout_type_regexes - {".*"}, {""}, {".*"}, {""}, false, - {"params", "bytes", "micros", "float_ops", "num_hidden_ops"}, - false); - const TFProfNode& root = tf_stats_->PrintGraph("scope", opts); - - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: " - "0\ntotal_exec_micros: 0\ntotal_requested_bytes: 1800\ntotal_parameters: " - "450\nchildren {\n name: \"DW\"\n exec_micros: 0\n requested_bytes: " - "648\n parameters: 162\n total_exec_micros: 0\n " - "total_requested_bytes: 648\n total_parameters: 162\n device: " - "\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n " - "total_float_ops: 0\n}\nchildren {\n name: \"DW2\"\n exec_micros: 0\n " - "requested_bytes: 1152\n parameters: 288\n total_exec_micros: 0\n " - "total_requested_bytes: 1152\n total_parameters: 288\n device: " - "\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n " - "total_float_ops: 0\n}\nfloat_ops: 0\ntotal_float_ops: 0\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -TEST_F(TFProfStatsTest, CheckPointOpType) { - Options opts( - 3, 0, 0, 0, 0, {".*"}, "name", {kCkptVarType}, // accout_type_regexes - {".*"}, {""}, {".*"}, {""}, false, - {"params", "bytes", "micros", "float_ops", "num_hidden_ops"}, false); - const TFProfNode& root = tf_stats_->PrintGraph("scope", opts); - - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: " - "0\ntotal_exec_micros: 0\ntotal_requested_bytes: 1800\ntotal_parameters: " - "450\nchildren {\n name: \"DW\"\n exec_micros: 0\n requested_bytes: " - "648\n parameters: 162\n total_exec_micros: 0\n " - "total_requested_bytes: 648\n total_parameters: 162\n device: " - "\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n " - "total_float_ops: 0\n}\nchildren {\n name: \"DW2\"\n exec_micros: 0\n " - "requested_bytes: 1152\n parameters: 288\n total_exec_micros: 0\n " - "total_requested_bytes: 1152\n total_parameters: 288\n device: " - "\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 0\n " - "total_float_ops: 0\n}\nfloat_ops: 0\ntotal_float_ops: 0\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -TEST_F(TFProfStatsTest, TestGraph) { - Options opts(100, 0, 10000, 0, 0, {".*"}, "name", {".*"}, - {"cost.*"}, // start_name_regexes - {""}, {".*"}, {""}, false, - {"params", "bytes", "micros", "float_ops", "num_hidden_ops"}, - false); - const TFProfNode& root = tf_stats_->PrintGraph("graph", opts); - - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: 0\ninputs: " - "0\ntotal_exec_micros: 0\ntotal_requested_bytes: 0\ntotal_parameters: " - "0\ntotal_inputs: 0\nfloat_ops: 0\ntotal_float_ops: 0\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -TEST_F(TFProfStatsTest, TestFloatOps) { - Options opts(10, 0, 0, 0, 1, {".*"}, "name", {".*"}, {".*"}, {""}, {".*"}, - {""}, false, {"float_ops"}, false); - const TFProfNode& root = tf_stats_->PrintGraph("scope", opts); - - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: " - "0\ntotal_exec_micros: 11\ntotal_requested_bytes: " - "5280\ntotal_parameters: 450\nchildren {\n name: \"Conv2D\"\n " - "exec_micros: 0\n requested_bytes: 432\n total_exec_micros: 0\n " - "total_requested_bytes: 432\n total_parameters: 0\n device: " - "\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 5832\n " - "total_float_ops: 5832\n}\nchildren {\n name: \"Conv2D_1\"\n " - "exec_micros: 10\n requested_bytes: 384\n total_exec_micros: 10\n " - "total_requested_bytes: 384\n total_parameters: 0\n device: " - "\"/job:localhost/replica:0/task:0/cpu:0\"\n float_ops: 4608\n " - "total_float_ops: 4608\n}\nfloat_ops: 0\ntotal_float_ops: 10440\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -TEST_F(TFProfStatsTest, TestAccountShownNameOnly) { - Options opts(100, 0, 0, 0, 0, {".*"}, "name", {".*"}, {".*"}, {""}, - {"unit_2_1.*DW"}, // show_name_regexes. - {""}, true, // account_displayed_op_only. - {"params"}, false); - const TFProfNode& root = tf_stats_->PrintGraph("scope", opts); - - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: " - "0\ntotal_exec_micros: 0\ntotal_requested_bytes: 0\ntotal_parameters: " - "0\nfloat_ops: 0\ntotal_float_ops: 0\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -TEST_F(TFProfStatsTest, TestShowTensorValue) { - Options opts(10, 0, 0, 0, 0, {".*"}, "name", {".*"}, {".*"}, {""}, - {"unit_1_0.*gamma"}, {""}, false, - {"tensor_value"}, // Show tensor value from checkpoint. - false); - const TFProfNode& root = tf_stats_->PrintGraph("scope", opts); - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: " - "0\ntotal_exec_micros: 11\ntotal_requested_bytes: " - "5280\ntotal_parameters: 450\nfloat_ops: 0\ntotal_float_ops: 10440\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.cc deleted file mode 100644 index c21626919f..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.cc +++ /dev/null @@ -1,78 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h" - -namespace tensorflow { -namespace tfprof { -void TFProfTensor::Display(string* formatted_str, - TFProfTensorProto* tfprof_tensor_pb) { - if (formatted_str) { - if (formatted_str_.length() >= kTFProfTenosrMaxDisplayLen) { - *formatted_str = - strings::StrCat(formatted_str_, "...omitted from display\n\n"); - } else { - *formatted_str = formatted_str_; - } - } - if (tfprof_tensor_pb) { - tfprof_tensor_pb->MergeFrom(tfprof_tensor_pb_); - } -} - -void TFProfTensor::Build() { - tfprof_tensor_pb_.set_dtype(tensor_->dtype()); - - switch (tensor_->dtype()) { - // Double for all floats. - case DataType::DT_FLOAT: - case DataType::DT_DOUBLE: { - std::vector<double> values_vec; - if (tensor_->dtype() == DataType::DT_FLOAT) { - GetValueVec<float, double>(&values_vec); - } else if (tensor_->dtype() == DataType::DT_DOUBLE) { - GetValueVec<double, double>(&values_vec); - } - BuildOutput<double>(0, 0, values_vec, &tfprof_tensor_pb_); - break; - } - // Int64 for all integers. - case DataType::DT_INT32: - case DataType::DT_INT64: { - std::vector<int64> values_vec; - if (tensor_->dtype() == DataType::DT_INT32) { - GetValueVec<int32, int64>(&values_vec); - } else if (tensor_->dtype() == DataType::DT_INT64) { - GetValueVec<int64, int64>(&values_vec); - } - BuildOutput<int64>(0, 0, values_vec, &tfprof_tensor_pb_); - break; - } - case DataType::DT_STRING: { - // Not supported by TensorFlow. - std::vector<string> values_vec; - GetValueVec<string, string>(&values_vec); - BuildOutput<string>(0, 0, values_vec, &tfprof_tensor_pb_); - break; - } - default: { - fprintf(stderr, "Not Supported type %d\n", tensor_->dtype()); - break; - } - } -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h deleted file mode 100644 index 471a1db417..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor.h +++ /dev/null @@ -1,120 +0,0 @@ -/* 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. -==============================================================================*/ - -// TFProf representation of a Tensor's value. -// 1. Multi-dimension tensor is flattened in row major, and stored in proto. -// 2. integer are up-casted to int64. floats are up-casted to double. string -// is not supported by TensorFlow CheckPointReader library, though it is -// supported in current code. - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_TENSOR_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_TENSOR_H_ - -#include <typeinfo> - -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/tensor.h" -#include "tensorflow/core/lib/strings/numbers.h" -#include "tensorflow/core/lib/strings/strcat.h" -#include "tensorflow/core/lib/strings/stringprintf.h" - -namespace tensorflow { -namespace tfprof { - -class TFProfTensor { - public: - explicit TFProfTensor(std::unique_ptr<Tensor> tensor) - : tensor_(std::move(tensor)) { - Build(); - } - - // If pointers are provided, they are filled by the method. - void Display(string* formatted_str, TFProfTensorProto* tfprof_tensor_pb); - - private: - // Max length of tensor value displayed to CLI. - const int64 kTFProfTenosrMaxDisplayLen = 10000; - // Max length after which a latency warning will be printed. - const int64 kTFProfTensorMaxWarnLen = 100000; - - void Build(); - - // It assumes the flatten values are stored in row-major, which is mentioned - // indirectly at various places: - // TODO(xpan): Further verifying it. - template <typename T> - int64 BuildOutput(int64 start, int depth, const std::vector<T>& values, - TFProfTensorProto* dim) { - formatted_str_ += "["; - int64 nstart = start; - for (int i = 0; i < tensor_->dim_size(depth); i++) { - // Last dimension, pull the values. - if (depth == tensor_->dims() - 1) { - std::ostringstream sstream; - sstream << values[nstart]; - - if (typeid(values[nstart]) == typeid(double)) { - double double_val; - CHECK(strings::safe_strtod(sstream.str().c_str(), &double_val)); - dim->add_value_double(double_val); - formatted_str_ += strings::Printf( - "%.2f ", dim->value_double(dim->value_double_size() - 1)); - } else if (typeid(values[nstart]) == typeid(int64)) { - int64 int64_val; - CHECK(strings::safe_strto64(sstream.str().c_str(), &int64_val)); - dim->add_value_int64(int64_val); - formatted_str_ += strings::Printf( - "%lld ", dim->value_int64(dim->value_int64_size() - 1)); - } else if (typeid(values[nstart]) == typeid(string)) { - dim->add_value_str(sstream.str()); - formatted_str_ = - strings::StrCat(formatted_str_, "'", - dim->value_str(dim->value_str_size() - 1) + "' "); - } else { - CHECK(false) << "Unsupported type: " << typeid(values[nstart]).name(); - } - ++nstart; - } else { - // Not-last dimension. Drill deeper. - nstart = BuildOutput<T>(nstart, depth + 1, values, dim); - } - } - if (formatted_str_.length() > kTFProfTenosrMaxDisplayLen) { - formatted_str_ = formatted_str_.substr(0, kTFProfTenosrMaxDisplayLen); - } - formatted_str_ += "],\n"; - return nstart; - } - - template <typename T, typename U> - void GetValueVec(std::vector<U>* value_vec) { - // TODO(xpan): Address the huge tensor problem. - if (tensor_->NumElements() > kTFProfTensorMaxWarnLen) { - fprintf(stderr, "Showing huge tensor, the tool might halt...\n"); - } - auto values = tensor_->flat<T>(); - for (int64 i = 0; i < tensor_->NumElements(); i++) { - value_vec->push_back(static_cast<U>(values(i))); - } - } - - TFProfTensorProto tfprof_tensor_pb_; - std::unique_ptr<Tensor> tensor_; - string formatted_str_; -}; -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_TENSOR_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor_test.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor_test.cc deleted file mode 100644 index d3f1e3c7b7..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_tensor_test.cc +++ /dev/null @@ -1,306 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.pb.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/io/path.h" -#include "tensorflow/core/platform/protobuf.h" -#include "tensorflow/core/platform/test.h" -#include "tensorflow/core/protobuf/config.pb.h" - -namespace tensorflow { -namespace tfprof { -class TFProfTensorTest : public ::testing::Test { - protected: - TFProfTensorTest() { - string graph_path = io::JoinPath( - testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/graph.pbtxt"); - std::unique_ptr<tensorflow::GraphDef> graph_pb(new tensorflow::GraphDef()); - TF_CHECK_OK(ReadGraphDefText(Env::Default(), graph_path, graph_pb.get())); - - std::unique_ptr<tensorflow::RunMetadata> run_meta_pb; - std::unique_ptr<OpLog> op_log_pb; - - string ckpt_path = - io::JoinPath(testing::TensorFlowSrcRoot(), - "contrib/tfprof/tools/tfprof/internal/testdata/ckpt"); - TF_Status* status = TF_NewStatus(); - std::unique_ptr<checkpoint::CheckpointReader> ckpt_reader( - new checkpoint::CheckpointReader(ckpt_path, status)); - CHECK(TF_GetCode(status) == TF_OK); - TF_DeleteStatus(status); - - tf_stats_.reset(new TFStats(std::move(graph_pb), std::move(run_meta_pb), - std::move(op_log_pb), std::move(ckpt_reader))); - } - - std::unique_ptr<TFStats> tf_stats_; -}; - -TEST_F(TFProfTensorTest, Basics) { - Options opts(3, 0, 0, 0, 0, {".*"}, "name", {"Variable"}, {".*"}, {""}, - {".*"}, {""}, false, {"tensor_value"}, // show the tensor value. - false); - const TFProfNode& root = tf_stats_->PrintGraph("scope", opts); - - TFProfNode expected; - CHECK(protobuf::TextFormat::ParseFromString( - "name: \"_TFProfRoot\"\nexec_micros: 0\nrequested_bytes: " - "0\ntotal_exec_micros: 0\ntotal_requested_bytes: 0\ntotal_parameters: " - "450\nchildren {\n name: \"DW\"\n exec_micros: 0\n requested_bytes: " - "0\n parameters: 162\n total_exec_micros: 0\n total_requested_bytes: " - "0\n total_parameters: 162\n float_ops: 0\n total_float_ops: 0\n " - "tensor_value {\n dtype: DT_FLOAT\n value_double: -0.00117808\n " - "value_double: -0.000709941\n value_double: -0.00174816\n " - "value_double: -0.000495372\n value_double: 0.000243039\n " - "value_double: -0.000126313\n value_double: -0.000663929\n " - "value_double: -0.000495198\n value_double: -0.000893934\n " - "value_double: -0.00179659\n value_double: 0.000408874\n " - "value_double: -0.00120166\n value_double: -0.00109484\n " - "value_double: -0.000200362\n value_double: 0.000726721\n " - "value_double: -0.000277568\n value_double: 0.00180584\n " - "value_double: 0.000997271\n value_double: -0.00185987\n " - "value_double: -0.00113401\n value_double: -0.000528852\n " - "value_double: -0.000197412\n value_double: 1.32871e-05\n " - "value_double: -0.000285896\n value_double: -0.000428898\n " - "value_double: -0.000424633\n value_double: 2.15488e-05\n " - "value_double: 0.00149753\n value_double: -0.000884576\n " - "value_double: -0.0013795\n value_double: -0.000650125\n " - "value_double: 0.00191612\n value_double: 4.71838e-05\n " - "value_double: 0.000400201\n value_double: 0.00239555\n " - "value_double: -0.00177706\n value_double: -0.000781899\n " - "value_double: -0.00145247\n value_double: 0.0020025\n " - "value_double: 0.000597419\n value_double: 0.00135456\n " - "value_double: 0.0015876\n value_double: -0.000993568\n " - "value_double: 0.0006509\n value_double: -0.000894533\n " - "value_double: -0.00129322\n value_double: 0.0003859\n " - "value_double: 0.000415186\n value_double: -0.000439212\n " - "value_double: 0.000442138\n value_double: 0.00212353\n " - "value_double: 0.000702953\n value_double: 0.000713424\n " - "value_double: -0.000304877\n value_double: -9.17046e-05\n " - "value_double: -0.000801103\n value_double: 0.000304854\n " - "value_double: -0.00070527\n value_double: -0.00106408\n " - "value_double: -0.000909906\n value_double: -4.49183e-05\n " - "value_double: 0.000104172\n value_double: -0.000438067\n " - "value_double: -0.000317689\n value_double: -0.000769914\n " - "value_double: -0.00157729\n value_double: 0.000220733\n " - "value_double: 0.00107268\n value_double: -0.000186449\n " - "value_double: -0.000807328\n value_double: 0.000456308\n " - "value_double: -0.000593729\n value_double: -0.000954873\n " - "value_double: -0.000268676\n value_double: 9.06328e-05\n " - "value_double: -0.000323473\n value_double: -0.000628768\n " - "value_double: 0.000664985\n value_double: 0.0020999\n " - "value_double: -0.000932228\n value_double: -0.00203203\n " - "value_double: 0.000565405\n value_double: 0.000167899\n " - "value_double: 0.00054897\n value_double: 0.000612407\n " - "value_double: -0.000619301\n value_double: 0.00169361\n " - "value_double: -0.000188057\n value_double: 0.000267652\n " - "value_double: -0.00127341\n value_double: -0.000218836\n " - "value_double: -0.000431722\n value_double: 5.41867e-05\n " - "value_double: 0.000296628\n value_double: 0.000819415\n " - "value_double: -0.000758993\n value_double: -0.000114477\n " - "value_double: 6.29219e-05\n value_double: 0.000726988\n " - "value_double: -0.00135974\n value_double: 2.28447e-05\n " - "value_double: 0.00120547\n value_double: -0.00136907\n " - "value_double: -0.00140188\n value_double: 0.000201145\n " - "value_double: -0.000774109\n value_double: 0.000798465\n " - "value_double: -0.00131861\n value_double: 3.08996e-05\n " - "value_double: -0.000637026\n value_double: 0.00228975\n " - "value_double: -0.000633757\n value_double: -0.00116047\n " - "value_double: 7.66039e-05\n value_double: 2.09167e-06\n " - "value_double: -0.000296448\n value_double: 0.000206795\n " - "value_double: 0.000674405\n value_double: -0.000722742\n " - "value_double: -9.32443e-05\n value_double: -0.00170917\n " - "value_double: -0.000505279\n value_double: 0.000628132\n " - "value_double: -0.00145929\n value_double: 0.00106077\n " - "value_double: -0.000796743\n value_double: 0.000498275\n " - "value_double: -0.0002914\n value_double: -0.00230622\n " - "value_double: -9.42872e-05\n value_double: 0.000200359\n " - "value_double: -0.00305027\n value_double: -0.0016218\n " - "value_double: 0.00137126\n value_double: -0.00215436\n " - "value_double: -0.000743827\n value_double: -0.00090007\n " - "value_double: -0.000762207\n value_double: -0.000149951\n " - "value_double: -0.0013102\n value_double: 0.00165781\n " - "value_double: 0.000343809\n value_double: -0.000826069\n " - "value_double: -4.67404e-05\n value_double: 0.0023931\n " - "value_double: 0.00165338\n value_double: -0.00050529\n " - "value_double: 0.000178771\n value_double: -0.000858287\n " - "value_double: -0.00157031\n value_double: -0.00165846\n " - "value_double: -0.000713672\n value_double: 0.00014357\n " - "value_double: 0.00203632\n value_double: -0.0010973\n " - "value_double: -9.89852e-05\n value_double: 0.000558808\n " - "value_double: 0.00087211\n value_double: 0.000661239\n " - "value_double: 0.000389605\n value_double: 0.00060653\n " - "value_double: -0.000330104\n }\n}\nchildren {\n name: \"DW2\"\n " - "exec_micros: 0\n requested_bytes: 0\n parameters: 288\n " - "total_exec_micros: 0\n total_requested_bytes: 0\n total_parameters: " - "288\n float_ops: 0\n total_float_ops: 0\n tensor_value {\n dtype: " - "DT_FLOAT\n value_double: 0.000704577\n value_double: " - "0.000127421\n value_double: 0.00105952\n value_double: " - "0.000423765\n value_double: -0.00025461\n value_double: " - "-0.000857203\n value_double: 0.000693494\n value_double: " - "0.000282214\n value_double: 0.00106185\n value_double: " - "-0.000836552\n value_double: -0.00116766\n value_double: " - "0.000733674\n value_double: -0.000669601\n value_double: " - "-0.000275175\n value_double: -0.000428215\n value_double: " - "-0.000495715\n value_double: -0.000125887\n value_double: " - "-0.000715204\n value_double: -0.00108936\n value_double: " - "0.000738267\n value_double: 0.000376081\n value_double: " - "0.00191442\n value_double: 0.001423\n value_double: -0.00093811\n " - " value_double: -5.91421e-05\n value_double: -0.000221507\n " - "value_double: -0.000104555\n value_double: -0.00069682\n " - "value_double: -0.000278325\n value_double: -0.00122748\n " - "value_double: -0.00112411\n value_double: -0.000440511\n " - "value_double: -0.000392247\n value_double: -0.000419606\n " - "value_double: -0.00167063\n value_double: -0.000988578\n " - "value_double: -0.00040159\n value_double: 0.00238918\n " - "value_double: -0.000892898\n value_double: -0.000875976\n " - "value_double: 0.00154401\n value_double: -0.000719911\n " - "value_double: 0.000753941\n value_double: -0.000119961\n " - "value_double: -0.000305115\n value_double: 9.97947e-05\n " - "value_double: -0.00128908\n value_double: -0.000584184\n " - "value_double: -0.000734685\n value_double: -0.00146612\n " - "value_double: 0.000670802\n value_double: 0.000924219\n " - "value_double: -0.000154409\n value_double: 0.000198231\n " - "value_double: -0.000340742\n value_double: -0.00159646\n " - "value_double: -1.19382e-05\n value_double: 0.00165203\n " - "value_double: 0.0017085\n value_double: -0.000199614\n " - "value_double: 0.000529526\n value_double: 0.000769364\n " - "value_double: 0.00135369\n value_double: 0.00132873\n " - "value_double: 0.000451174\n value_double: 0.000255218\n " - "value_double: 0.00102891\n value_double: -0.00160068\n " - "value_double: 0.000324269\n value_double: -0.000492347\n " - "value_double: 0.000925301\n value_double: 0.00281998\n " - "value_double: -0.000826404\n value_double: -0.000602903\n " - "value_double: 0.00126559\n value_double: 0.000924364\n " - "value_double: -9.19827e-05\n value_double: -5.59275e-05\n " - "value_double: 0.00107971\n value_double: -9.91756e-05\n " - "value_double: 0.000864708\n value_double: 0.00121747\n " - "value_double: 0.00146338\n value_double: 0.000186883\n " - "value_double: -0.00168195\n value_double: -0.00062029\n " - "value_double: 0.000658127\n value_double: 0.00115682\n " - "value_double: -0.00178359\n value_double: 0.000685606\n " - "value_double: -0.000503373\n value_double: -0.000312999\n " - "value_double: 0.000335383\n value_double: -1.08597e-05\n " - "value_double: -8.2499e-05\n value_double: -0.000469726\n " - "value_double: -0.00170868\n value_double: 0.000118957\n " - "value_double: -0.000460736\n value_double: -5.56372e-05\n " - "value_double: -0.00110148\n value_double: 0.00059123\n " - "value_double: 0.000386339\n value_double: -0.00139967\n " - "value_double: -0.000835664\n value_double: 0.00103421\n " - "value_double: -0.00104296\n value_double: -0.000687497\n " - "value_double: 1.1338e-05\n value_double: 0.00176484\n " - 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"value_double: 7.8429e-05\n value_double: 0.00161337\n " - "value_double: -0.000269005\n value_double: 0.000217822\n " - "value_double: 0.000599886\n value_double: 0.000317549\n " - "value_double: 0.00146597\n value_double: -0.00210947\n " - "value_double: -0.000823917\n value_double: -6.83766e-05\n " - "value_double: 0.000656085\n value_double: 0.000117134\n " - "value_double: -0.000390405\n value_double: 2.39565e-05\n " - "value_double: 0.00104837\n value_double: -0.000563671\n " - "value_double: 0.000634073\n value_double: -0.000554531\n " - "value_double: 0.000677971\n value_double: -0.000596207\n " - "value_double: -0.00103335\n value_double: 0.000645199\n " - "value_double: 0.00162195\n value_double: 0.000239246\n " - "value_double: 0.00113519\n value_double: 0.000787431\n " - "value_double: -0.000471688\n value_double: -0.000216625\n " - "value_double: -0.000537156\n value_double: 0.000551816\n " - "value_double: 0.00094337\n value_double: -0.000708127\n " - "value_double: 0.000956955\n value_double: -0.000904936\n " - "value_double: -0.000424413\n value_double: 0.000106455\n " - "value_double: -0.000443952\n value_double: 0.000185436\n " - "value_double: 0.000944397\n value_double: -0.000760572\n " - "value_double: 0.000560002\n value_double: 4.09886e-05\n " - "value_double: -0.00075076\n value_double: -0.000701856\n " - "value_double: -0.000234851\n value_double: -0.000131515\n " - "value_double: -0.000761718\n value_double: -0.000267808\n " - "value_double: -0.00039682\n value_double: 0.000542953\n " - "value_double: -0.000817685\n value_double: 0.00103851\n " - "value_double: -0.000427176\n value_double: 0.000517784\n " - "value_double: -0.000823552\n value_double: -0.000742637\n " - "value_double: 0.000529213\n value_double: -0.000372805\n " - "value_double: 1.85745e-05\n value_double: 0.00139891\n " - "value_double: -0.000128417\n value_double: -0.000404316\n " - "value_double: -0.000671571\n value_double: 0.000490311\n " - "value_double: -0.00118493\n value_double: -0.000897118\n " - "value_double: 0.000939601\n value_double: 0.000376399\n " - "value_double: 0.0014709\n value_double: 0.000134806\n " - "value_double: -0.000294469\n value_double: -0.000569142\n " - "value_double: 0.00127266\n value_double: -0.00140936\n " - "value_double: 0.000870083\n value_double: 0.000287246\n " - "value_double: 0.000537685\n value_double: 0.000125569\n " - "value_double: 0.000360276\n value_double: -0.000186268\n " - "value_double: 0.0011141\n value_double: -0.000605185\n " - "value_double: -0.0016281\n value_double: -0.000552758\n " - "value_double: -0.000196755\n value_double: -0.00265188\n " - "value_double: 0.000480997\n value_double: 0.00018776\n " - "value_double: -0.00199234\n value_double: 0.000959982\n " - "value_double: 0.00040334\n value_double: -0.000693596\n " - "value_double: 0.00157678\n value_double: -0.00134499\n " - "value_double: 0.00121909\n value_double: -0.000328734\n " - "value_double: 0.000148554\n value_double: -0.000209509\n " - "value_double: -0.000266303\n value_double: -0.00134084\n " - "value_double: 5.21371e-05\n value_double: 0.0005329\n " - "value_double: -0.000168858\n value_double: -0.00074875\n " - "value_double: 0.000959397\n value_double: -0.00159476\n " - "value_double: -0.000368838\n value_double: 0.0006077\n " - "value_double: -0.00117243\n value_double: -0.00146013\n " - "value_double: 0.00031519\n value_double: -0.000167911\n " - "value_double: 0.000482571\n value_double: -0.000752268\n " - "value_double: -0.00042363\n value_double: 0.00121219\n " - "value_double: -0.000208159\n value_double: 0.000128531\n " - "value_double: -0.000406308\n value_double: -0.000242663\n " - "value_double: -3.96673e-05\n value_double: 0.00144854\n " - "value_double: -0.000787328\n value_double: -0.000401958\n " - "value_double: 0.00114091\n value_double: -0.000739546\n " - "value_double: 0.000483236\n value_double: -0.000916945\n " - "value_double: -0.00129577\n value_double: -0.00186504\n " - "value_double: 0.000806804\n value_double: -0.000152251\n " - "value_double: 0.000662576\n value_double: -0.000533236\n " - "value_double: 0.00151019\n value_double: 0.00127805\n " - "value_double: 0.00115399\n value_double: -0.00130876\n " - "value_double: 2.99457e-06\n value_double: 0.000820777\n " - "value_double: 0.000878393\n value_double: -0.000562642\n " - "value_double: -0.00070442\n value_double: -0.00066277\n " - "}\n}\nfloat_ops: 0\ntotal_float_ops: 0\n", - &expected)); - EXPECT_EQ(expected.DebugString(), root.DebugString()); -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.cc b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.cc deleted file mode 100644 index 7610729a11..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.cc +++ /dev/null @@ -1,350 +0,0 @@ -/* 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. -==============================================================================*/ - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" - -#include <stdio.h> -#include <algorithm> -#include <memory> -#include <set> - -#include "tensorflow/core/lib/strings/numbers.h" -#include "tensorflow/core/lib/strings/str_util.h" -#include "tensorflow/core/lib/strings/strcat.h" -#include "tensorflow/core/lib/strings/stringprintf.h" -#include "tensorflow/core/platform/protobuf.h" -#include "tensorflow/core/platform/regexp.h" - -namespace tensorflow { -namespace tfprof { -string FormatNumber(int64 n) { - if (n < 1000) { - return strings::Printf("%lld", n); - } else if (n < 1000000) { - return strings::Printf("%.2fk", n / 1000.0); - } else if (n < 1000000000) { - return strings::Printf("%.2fm", n / 1000000.0); - } else { - return strings::Printf("%.2fb", n / 1000000000.0); - } -} - -string FormatTime(int64 micros) { - if (micros < 1000) { - return strings::Printf("%lldus", micros); - } else if (micros < 1000000) { - return strings::Printf("%.2fms", micros / 1000.0); - } else { - return strings::Printf("%.2fsec", micros / 1000000.0); - } -} - -string FormatMemory(int64 bytes) { - if (bytes < 1000) { - return strings::Printf("%lldB", bytes); - } else if (bytes < 1000000) { - return strings::Printf("%.2fKB", bytes / 1000.0); - } else { - return strings::Printf("%.2fMB", bytes / 1000000.0); - } -} - -string FormatShapes(const std::vector<int64>& shape) { - return str_util::Join(shape, "x"); -} - -string StringReplace(const string& str, const string& oldsub, - const string& newsub) { - string out = str; - RE2::GlobalReplace(&out, oldsub, newsub); - return out; -} - -Status ReadGraphDefText(Env* env, const string& fname, GraphDef* graph_def) { - string out; - Status s = ReadFileToString(env, fname, &out); - if (!s.ok()) return s; - if (protobuf::TextFormat::ParseFromString(out, graph_def)) { - return Status(); - } - return errors::InvalidArgument("Cannot parse proto string."); -} - -namespace { -string StripQuote(const string& s) { - int start = s.find_first_not_of("\"\'"); - int end = s.find_last_not_of("\"\'"); - if (start == s.npos || end == s.npos) return ""; - - return s.substr(start, end - start + 1); -} - -tensorflow::Status ReturnError(const std::vector<string> pieces, int idx) { - string val; - if (pieces.size() > idx + 1) { - val = pieces[idx + 1]; - } - return tensorflow::Status( - tensorflow::error::INVALID_ARGUMENT, - strings::StrCat("Invalid option '", pieces[idx], "' value: '", val, "'")); -} - -bool CaseEqual(StringPiece s1, StringPiece s2) { - if (s1.size() != s2.size()) return false; - return str_util::Lowercase(s1) == str_util::Lowercase(s2); -} - -bool StringToBool(StringPiece str, bool* value) { - CHECK(value != NULL) << "NULL output boolean given."; - if (CaseEqual(str, "true") || CaseEqual(str, "t") || CaseEqual(str, "yes") || - CaseEqual(str, "y") || CaseEqual(str, "1")) { - *value = true; - return true; - } - if (CaseEqual(str, "false") || CaseEqual(str, "f") || CaseEqual(str, "no") || - CaseEqual(str, "n") || CaseEqual(str, "0")) { - *value = false; - return true; - } - return false; -} -} // namespace - -tensorflow::Status ParseCmdLine(const string& line, string* cmd, - tensorflow::tfprof::Options* opts) { - std::vector<string> pieces = - str_util::Split(line, ' ', str_util::SkipEmpty()); - - std::vector<string> cmds_str(kCmds, kCmds + sizeof(kCmds) / sizeof(*kCmds)); - if (std::find(cmds_str.begin(), cmds_str.end(), pieces[0]) == - cmds_str.end()) { - return tensorflow::Status(tensorflow::error::INVALID_ARGUMENT, - "First string must be a valid command."); - } - *cmd = pieces[0]; - - for (int i = 1; i < pieces.size(); ++i) { - if (pieces[i] == string(tensorflow::tfprof::kOptions[0])) { - if (pieces.size() <= i + 1 || - !strings::safe_strto32(pieces[i + 1], &opts->max_depth)) { - return ReturnError(pieces, i); - } - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[1]) { - if (pieces.size() <= i + 1 || - !strings::safe_strto64(pieces[i + 1], &opts->min_bytes)) { - return ReturnError(pieces, i); - } - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[2]) { - if (pieces.size() <= i + 1 || - !strings::safe_strto64(pieces[i + 1], &opts->min_micros)) { - return ReturnError(pieces, i); - } - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[3]) { - if (pieces.size() <= i + 1 || - !strings::safe_strto64(pieces[i + 1], &opts->min_params)) { - return ReturnError(pieces, i); - } - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[4]) { - if (pieces.size() <= i + 1 || - !strings::safe_strto64(pieces[i + 1], &opts->min_float_ops)) { - return ReturnError(pieces, i); - } - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[5]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->device_regexes = str_util::Split(StripQuote(pieces[i + 1]), ',', - str_util::SkipEmpty()); - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[6]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - std::set<string> order_by_set( - kOrderBy, kOrderBy + sizeof(kOrderBy) / sizeof(*kOrderBy)); - auto order_by = order_by_set.find(pieces[i + 1]); - if (order_by == order_by_set.end()) { - return ReturnError(pieces, i); - } - opts->order_by = *order_by; - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[7]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->account_type_regexes = str_util::Split(StripQuote(pieces[i + 1]), - ',', str_util::SkipEmpty()); - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[8]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->start_name_regexes = str_util::Split(StripQuote(pieces[i + 1]), ',', - str_util::SkipEmpty()); - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[9]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->trim_name_regexes = str_util::Split(StripQuote(pieces[i + 1]), ',', - str_util::SkipEmpty()); - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[10]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->show_name_regexes = str_util::Split(StripQuote(pieces[i + 1]), ',', - str_util::SkipEmpty()); - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[11]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->hide_name_regexes = str_util::Split(StripQuote(pieces[i + 1]), ',', - str_util::SkipEmpty()); - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[12]) { - if ((pieces.size() > i + 1 && pieces[i + 1].find("-") == 0) || - pieces.size() == i + 1) { - opts->account_displayed_op_only = true; - } else if (!StringToBool(pieces[i + 1], - &opts->account_displayed_op_only)) { - return ReturnError(pieces, i); - } else { - ++i; - } - } else if (pieces[i] == tensorflow::tfprof::kOptions[13]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - std::set<string> shown_set(kShown, - kShown + sizeof(kShown) / sizeof(*kShown)); - std::vector<string> requested_vector = str_util::Split( - StripQuote(pieces[i + 1]), ',', str_util::SkipEmpty()); - std::set<string> requested_set(requested_vector.begin(), - requested_vector.end()); - for (const string& requested : requested_set) { - if (shown_set.find(requested) == shown_set.end()) { - return ReturnError(pieces, i); - } - } - opts->select = requested_set; - ++i; - } else if (pieces[i] == tensorflow::tfprof::kOptions[14]) { - if ((pieces.size() > i + 1 && pieces[i + 1].find("-") == 0) || - pieces.size() == i + 1) { - opts->viz = true; - } else if (!StringToBool(pieces[i + 1], &opts->viz)) { - return ReturnError(pieces, i); - } else { - ++i; - } - } else if (pieces[i] == tensorflow::tfprof::kOptions[15]) { - if (pieces.size() <= i + 1) { - return ReturnError(pieces, i); - } - opts->dump_to_file = StripQuote(pieces[i + 1]); - ++i; - } else { - return ReturnError(pieces, i); - } - } - return tensorflow::Status::OK(); -} - -void PrintHelp() { - printf( - "\nSee go/tfprof for detail tutorial.\n" - "\nCommands\n\n" - " scope: Each op has its op name in TensorFlow, such as 'n1', 'n1/n2', " - "'n1/n2/n3'. 'n1/n2' is a child of 'n1'. 'scope' command builds " - "a name scope tree and aggregates statistics based on it.\n\n" - " graph: ops in TensorFlow are organized as a graph based on their " - "the source (inputs) and sink (outputs). 'graph' command builds " - "a graph pointing *from output to input*, and aggregates " - "statistics based on it.\n\n" - " set: Set options that will be default for follow up commands.\n\n" - " help: Show helps.\n" - "\nOptions\n\n" - "Press Enter in CLI to see default option values.\n\n" - " -max_depth: Show ops that are at most this number of hops from " - "starting op in the tree/graph structure.\n\n" - " -min_bytes: Show ops that request at least this number of bytes.\n\n" - " -min_micros: Show ops that spend at least this number of micros to " - "run.\n\n" - " -min_params: Show ops that contains at least this number of " - "parameters.\n\n" - " -min_float_ops: Show ops that contain at least this number of " - "float operations. Only available if an op has " - "op.RegisterStatistics() defined and OpLog is " - "provided\n\n" - " -device_regexes: Show ops that a placed on the specified devices. " - "regexes are comma-separated.\n\n" - " -order_by: Order the results by [name|depth|bytes|micros|params|" - "float_ops]\n\n" - " -account_type_regexes: Account and display the ops whose types match " - "one of the type regexes specified. tfprof " - "allow user to define extra op types for ops " - "through tensorflow.tfprof.OpLog proto. regexes " - "are comma-sperated.\n\n" - " -start_name_regexes: Show ops starting from the ops that matches the " - "regexes, recursively. regexes are " - "comma-separated.\n\n" - " -trim_name_regexes: Hide ops starting from the ops that matches the " - "regexes, recursively, regexes are comma-seprated. " - "\n\n" - " -show_name_regexes: Show ops that match the regexes. regexes are " - "comma-seprated.\n\n" - " -hide_name_regexes: Hide ops that match the regexes. regexes are " - "comma-seprated.\n\n" - "" - " Notes: For each op, -acount_type_regexes is first evaluated, " - "only ops with types matching the specified regexes are accounted and " - "selected for displayed. -start/trim/show/hide_name_regexes are used " - "to further filter ops for display. -start_name_regexes is evaluated " - "first to search the starting ops to display. Descendants of starting " - "ops are then evaluated against show/hide_name_regexes to make display " - "decision. If an op matches trim_name_regexes, all its descendants are " - "hidden.\n" - "Ops statistics are *accounted even if they are hidden* as long as " - "they match the -account_xxx options.\n\n" - " -account_displayed_op_only: If True, only account the statistics of " - "ops eventually displayed. If False, account all " - "op statistics matching -account_type_regexes recursively.\n\n" - " -select: Comma-separated list of metrics to show: [bytes|micros|" - "params|float_ops|num_hidden_ops|tensor_value|device|op_types]." - "\n\n" - " -dump_to_file: Dump the output to a file, instead of terminal.\n\n" - "" - "Examples\n" - " Assuming a toy model:\n" - " intput(typeB)->conv2d_1(typeA)->conv2d_2(typeA)->" - "fc(typeA)->cost(typeA)->summarize(typeC)\n" - " Command:\n" - " tfprof> graph -account_type_regexes typeA -start_name_regexes " - "cost.* -show_name_regexes conv2d.* -max_depth 10\n\n" - " The above command only aggregate statistics of all ops of typeA (" - "hence ignoring input(typeB)). It will start looking for candidate to " - "display from cost.* and finally displays conv2d_1 and conv2d_2.\n\n"); - fflush(stdout); -} - -} // namespace tfprof -} // namespace tensorflow diff --git a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h b/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h deleted file mode 100644 index 6c1bba04fc..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h +++ /dev/null @@ -1,50 +0,0 @@ -/* 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. -==============================================================================*/ - -#ifndef THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_UTILS_H_ -#define THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_UTILS_H_ - -#include <string> -#include <vector> - -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/lib/core/errors.h" -#include "tensorflow/core/platform/env.h" - -namespace tensorflow { -namespace tfprof { -string FormatNumber(int64 n); - -string FormatTime(int64 micros); - -string FormatMemory(int64 bytes); - -string FormatShapes(const std::vector<int64>& shapes); - -tensorflow::Status ParseCmdLine(const string& line, string* cmd, - tensorflow::tfprof::Options* opts); - -string StringReplace(const string& str, const string& oldsub, - const string& newsub); - -Status ReadGraphDefText(Env* env, const string& fname, GraphDef* graph_def); - -void PrintHelp(); - -} // namespace tfprof -} // namespace tensorflow - -#endif // THIRD_PARTY_TENSORFLOW_CONTRIB_TFPROF_TOOLS_TFPROF_INTERNAL_TFPROF_UTILS_H_ diff --git a/tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.proto b/tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.proto deleted file mode 100644 index cae6e1e3a8..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.proto +++ /dev/null @@ -1,19 +0,0 @@ -syntax = "proto2"; - -package tensorflow.tfprof; - -message OpLogEntry { - // op name. - optional string name = 1; - // float_ops is filled by tfprof Python API when called. It requires the - // op has RegisterStatistics defined. Currently, Conv2D, MatMul, etc, are - // implemented. - optional int64 float_ops = 2; - // User can define extra op type information for an op. This allows the user - // to select a group of ops precisely using op_type as a key. - repeated string types = 3; -} - -message OpLog { - repeated OpLogEntry log_entries = 1; -}
\ No newline at end of file diff --git a/tensorflow/contrib/tfprof/tools/tfprof/tfprof_main.cc b/tensorflow/contrib/tfprof/tools/tfprof/tfprof_main.cc deleted file mode 100644 index 38b1588d72..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/tfprof_main.cc +++ /dev/null @@ -1,252 +0,0 @@ -/* 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. -==============================================================================*/ - -#include <stdio.h> -#include <stdlib.h> -#include <memory> -#include <set> -#include <string> -#include <utility> -#include <vector> - -#include "linenoise.h" -#include "tensorflow/c/c_api.h" -#include "tensorflow/c/checkpoint_reader.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_options.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_stats.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/internal/tfprof_utils.h" -#include "tensorflow/contrib/tfprof/tools/tfprof/tfprof_log.pb.h" -#include "tensorflow/core/framework/graph.pb.h" -#include "tensorflow/core/framework/types.h" -#include "tensorflow/core/lib/core/errors.h" -#include "tensorflow/core/lib/strings/str_util.h" -#include "tensorflow/core/platform/env.h" -#include "tensorflow/core/platform/init_main.h" -#include "tensorflow/core/protobuf/config.pb.h" -#include "tensorflow/core/util/command_line_flags.h" - -using tensorflow::str_util::Split; - -void completion(const char* buf, linenoiseCompletions* lc) { - tensorflow::string buf_str = tensorflow::string(buf); - if (buf_str.find(" ") == buf_str.npos) { - for (const char* opt : tensorflow::tfprof::kCmds) { - if (tensorflow::string(opt).find(buf_str) == 0) { - linenoiseAddCompletion(lc, opt); - } - } - return; - } - - tensorflow::string prefix; - int last_dash = buf_str.find_last_of(' '); - if (last_dash != tensorflow::string::npos) { - prefix = buf_str.substr(0, last_dash + 1); - buf_str = buf_str.substr(last_dash + 1, tensorflow::kint32max); - } - for (const char* opt : tensorflow::tfprof::kOptions) { - if (tensorflow::string(opt).find(buf_str) == 0) { - linenoiseAddCompletion(lc, (prefix + opt).c_str()); - } - } -} - -int main(int argc, char** argv) { - tensorflow::string FLAGS_graph_path = ""; - tensorflow::string FLAGS_run_meta_path = ""; - tensorflow::string FLAGS_op_log_path = ""; - tensorflow::string FLAGS_checkpoint_path = ""; - tensorflow::int32 FLAGS_max_depth = 4; - tensorflow::int64 FLAGS_min_bytes = 0; - tensorflow::int64 FLAGS_min_micros = 0; - tensorflow::int64 FLAGS_min_params = 0; - tensorflow::int64 FLAGS_min_float_ops = 0; - tensorflow::string FLAGS_device_regexes = ".*"; - tensorflow::string FLAGS_order_by = "name"; - tensorflow::string FLAGS_account_type_regexes = "Variable"; - tensorflow::string FLAGS_start_name_regexes = ".*"; - tensorflow::string FLAGS_trim_name_regexes = ""; - tensorflow::string FLAGS_show_name_regexes = ".*"; - tensorflow::string FLAGS_hide_name_regexes; - bool FLAGS_account_displayed_op_only = false; - tensorflow::string FLAGS_select = "params"; - bool FLAGS_viz = false; - tensorflow::string FLAGS_dump_to_file = ""; - for (int i = 0; i < argc; i++) { - fprintf(stderr, "%s\n", argv[i]); - } - - std::vector<tensorflow::Flag> flag_list = { - tensorflow::Flag("graph_path", &FLAGS_graph_path, - "GraphDef proto text file name"), - tensorflow::Flag("run_meta_path", &FLAGS_run_meta_path, - "RunMetadata proto binary file name"), - tensorflow::Flag("op_log_path", &FLAGS_op_log_path, - "tensorflow::tfprof::OpLog proto binary file name"), - tensorflow::Flag("checkpoint_path", &FLAGS_checkpoint_path, - "TensorFlow Checkpoint file name"), - tensorflow::Flag("max_depth", &FLAGS_max_depth, "max depth"), - tensorflow::Flag("min_bytes", &FLAGS_min_bytes, "min_bytes"), - tensorflow::Flag("min_micros", &FLAGS_min_micros, "min micros"), - tensorflow::Flag("min_params", &FLAGS_min_params, "min params"), - tensorflow::Flag("min_float_ops", &FLAGS_min_float_ops, "min float ops"), - tensorflow::Flag("device_regexes", &FLAGS_device_regexes, - "device regexes"), - tensorflow::Flag("order_by", &FLAGS_order_by, "order by"), - tensorflow::Flag("account_type_regexes", &FLAGS_start_name_regexes, - "start name regexes"), - tensorflow::Flag("trim_name_regexes", &FLAGS_trim_name_regexes, - "trim name regexes"), - tensorflow::Flag("show_name_regexes", &FLAGS_show_name_regexes, - "show name regexes"), - tensorflow::Flag("hide_name_regexes", &FLAGS_hide_name_regexes, - "hide name regexes"), - tensorflow::Flag("account_displayed_op_only", - &FLAGS_account_displayed_op_only, - "account displayed op only"), - tensorflow::Flag("select", &FLAGS_select, "select"), - tensorflow::Flag("dump_to_file", &FLAGS_dump_to_file, "dump to file"), - }; - tensorflow::string usage = tensorflow::Flags::Usage(argv[0], flag_list); - bool parse_ok = tensorflow::Flags::Parse(&argc, argv, flag_list); - if (!parse_ok) { - printf("%s", usage.c_str()); - return (2); - } - tensorflow::port::InitMain(argv[0], &argc, &argv); - - fprintf(stderr, "%s\n", FLAGS_graph_path.c_str()); - - std::vector<tensorflow::string> device_regexes = - Split(FLAGS_device_regexes, ',', tensorflow::str_util::SkipEmpty()); - std::vector<tensorflow::string> account_type_regexes = - Split(FLAGS_account_type_regexes, ',', tensorflow::str_util::SkipEmpty()); - std::vector<tensorflow::string> start_name_regexes = - Split(FLAGS_start_name_regexes, ',', tensorflow::str_util::SkipEmpty()); - std::vector<tensorflow::string> trim_name_regexes = - Split(FLAGS_trim_name_regexes, ',', tensorflow::str_util::SkipEmpty()); - std::vector<tensorflow::string> show_name_regexes = - Split(FLAGS_show_name_regexes, ',', tensorflow::str_util::SkipEmpty()); - std::vector<tensorflow::string> hide_name_regexes = - Split(FLAGS_hide_name_regexes, ',', tensorflow::str_util::SkipEmpty()); - std::vector<tensorflow::string> select = - Split(FLAGS_select, ',', tensorflow::str_util::SkipEmpty()); - - tensorflow::string cmd = ""; - if (argc == 1 && FLAGS_graph_path.empty()) { - printf("1) go/tfprof: Tutorial.\n"); - printf("2) tfprof help: Detail help information.\n"); - printf( - "3) tfprof --graph_path <GraphDef proto text file>: " - "Profiling model structure, tensor shape and # parameters.\n"); - printf( - "4) tfprof --graph_path <GraphDef proto text file> \\\n" - " --run_meta_path <RunMetadata proto binary file> \\\n" - " --op_log_path <tensorflow::tfprof::OpLog proto binary file> " - "\\\n" - " --checkpoint_path <TensorFlow Checkpoint file>: " - "Profiling everything!\n"); - return 0; - } else if (argc > 1) { - if (tensorflow::string(argv[1]) == tensorflow::tfprof::kCmds[3]) { - tensorflow::tfprof::PrintHelp(); - return 0; - } - if (tensorflow::string(argv[1]) == tensorflow::tfprof::kCmds[0] || - tensorflow::string(argv[1]) == tensorflow::tfprof::kCmds[1]) { - cmd = argv[1]; - } - } - - printf("Reading Files...\n"); - std::unique_ptr<tensorflow::GraphDef> graph(new tensorflow::GraphDef()); - TF_CHECK_OK(tensorflow::tfprof::ReadGraphDefText( - tensorflow::Env::Default(), FLAGS_graph_path, graph.get())); - - std::unique_ptr<tensorflow::RunMetadata> run_meta( - new tensorflow::RunMetadata()); - if (!ReadBinaryProto(tensorflow::Env::Default(), FLAGS_run_meta_path, - run_meta.get()) - .ok()) { - run_meta.release(); - } - - std::unique_ptr<tensorflow::tfprof::OpLog> op_log( - new tensorflow::tfprof::OpLog()); - if (!ReadBinaryProto(tensorflow::Env::Default(), FLAGS_op_log_path, - op_log.get()) - .ok()) { - op_log.release(); - } - - std::unique_ptr<tensorflow::checkpoint::CheckpointReader> ckpt_reader; - TF_Status* status = TF_NewStatus(); - if (!FLAGS_checkpoint_path.empty()) { - ckpt_reader.reset(new tensorflow::checkpoint::CheckpointReader( - FLAGS_checkpoint_path, status)); - if (TF_GetCode(status) != TF_OK) { - fprintf(stderr, "%s\n", TF_Message(status)); - TF_DeleteStatus(status); - return 1; - } - TF_DeleteStatus(status); - } - - tensorflow::tfprof::TFStats tf_stat(std::move(graph), std::move(run_meta), - std::move(op_log), - std::move(ckpt_reader)); - tensorflow::tfprof::Options opts( - FLAGS_max_depth, FLAGS_min_bytes, FLAGS_min_micros, FLAGS_min_params, - FLAGS_min_float_ops, device_regexes, FLAGS_order_by, account_type_regexes, - start_name_regexes, trim_name_regexes, show_name_regexes, - hide_name_regexes, FLAGS_account_displayed_op_only, select, FLAGS_viz, - FLAGS_dump_to_file); - - if (!cmd.empty()) { - tf_stat.PrintGraph(cmd, opts); - return 0; - } - - linenoiseSetCompletionCallback(completion); - linenoiseHistoryLoad(".tfprof_history.txt"); - - for (char* line = nullptr; (line = linenoise("tfprof> ")) != nullptr;) { - tensorflow::string line_s = tensorflow::string(line); - free(line); - - if (line_s.empty()) { - printf("%s", opts.ToString().c_str()); - continue; - } - linenoiseHistoryAdd(line_s.c_str()); - linenoiseHistorySave(".tfprof_history.txt"); - - tensorflow::tfprof::Options new_opts = opts; - tensorflow::Status s = - tensorflow::tfprof::ParseCmdLine(line_s, &cmd, &new_opts); - if (!s.ok()) { - fprintf(stderr, "E: %s\n", s.ToString().c_str()); - continue; - } - if (cmd == tensorflow::tfprof::kCmds[2]) { - opts = new_opts; - } else if (cmd == tensorflow::tfprof::kCmds[3]) { - tensorflow::tfprof::PrintHelp(); - } else { - tf_stat.PrintGraph(cmd, new_opts); - } - } - return 0; -} diff --git a/tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.proto b/tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.proto deleted file mode 100644 index 9afd41046e..0000000000 --- a/tensorflow/contrib/tfprof/tools/tfprof/tfprof_output.proto +++ /dev/null @@ -1,49 +0,0 @@ -syntax = "proto2"; - -import "tensorflow/core/framework/tensor_shape.proto"; -import "tensorflow/core/framework/types.proto"; - -package tensorflow.tfprof; - -message TFProfTensorProto { - optional DataType dtype = 1; - // Flatten tensor in row-major. - // Only one of the following array is set. - repeated double value_double = 2; - repeated int64 value_int64 = 3; - repeated string value_str = 4; -} - -message TFProfNode { - // op name. - optional string name = 1; - // tensor value restored from checkpoint. - optional TFProfTensorProto tensor_value = 15; - // op execution time. - optional int64 exec_micros = 2; - // Total requested bytes by the op. - optional int64 requested_bytes = 3; - // Number of parameters if available. - optional int64 parameters = 4; - // Number of float operations. - optional int64 float_ops = 13; - // Number of inputs to the op. - optional int64 inputs = 5; - // Device the op is assigned to. - optional string device = 10; - - // The following are the aggregated stats from all accounted descendants and - // the op itself. The actual descendants depend on the data structure used - // (scope, graph). - optional int64 total_exec_micros = 6; - optional int64 total_requested_bytes = 7; - optional int64 total_parameters = 8; - optional int64 total_float_ops = 14; - optional int64 total_inputs = 9; - - // shape information, if available. - repeated TensorShapeProto shapes = 11; - // Descendants of the graph. The actual descendants depend on the data - // structure used (scope, graph). - repeated TFProfNode children = 12; -}
\ No newline at end of file |