o i e9@s*dZddlZddlZddlZddlmZddlmZddlm Z ddl m Z ddl m Z ddlmZdd lmZdd lmZdaeZdad ZGd d d eZGdddeZeddd"ddZeddddZeddddZeddddZeddddZ eddGd d!d!e!Z"dS)#a!TensorFlow 2.0 Profiler for both Eager Mode and Graph Mode. The profiler has two mode: - Programmatic Mode: start(), stop() and Profiler class. It will perform when calling start() or create Profiler class and will stop when calling stop() or destroying Profiler class. - On-demand Mode: start_profiler_server(). It will perform profiling when receive profiling request. NOTE: Only one active profiler session is allowed. Use of simultaneous Programmatic Mode and On-demand Mode is undefined and will likely fail. NOTE: The Keras TensorBoard callback will automatically perform sampled profiling. Before enabling customized profiling, set the callback flag "profile_batches=[]" to disable automatic sampled profiling. customized profiling. N)_pywrap_events_writer)context)errors)gfile) tf_logging)_pywrap_profiler)compat) deprecatedz.profile-emptyc@ eZdZdS)ProfilerAlreadyRunningErrorN__name__ __module__ __qualname__rrO/var/www/myenv/lib/python3.10/site-packages/tensorflow/python/eager/profiler.pyr 6r c@r )ProfilerNotRunningErrorNr rrrrr:rrz 2020-07-01z-use `tf.profiler.experimental.start` instead.c Cst?tdur tdtjtjkrttazt d|dur#|niWnt j y8t dtdwWddS1sDwYdS)zStart profiling. Args: options: profiler options. Raises: ProfilerAlreadyRunningError: If another profiling session is running. NzAnother profiler is running.zAnother profiler session is running which is probably created by profiler server. Please avoid using profiler server and profiler APIs at the same time.)_profiler_lock _profilerr rdefault_execution_mode EAGER_MODEensure_initializedrProfilerSessionstartrAlreadyExistsErrorloggingwarning)optionsrrrr>s   "rz,use `tf.profiler.experimental.stop` instead.cCsht(tdur tdtjtjkrtjt}dat d7a Wd|S1s-wY|S)a Stop current profiling session and return its result. Returns: A binary string of tensorflow.tpu.Trace. User can write the string to file for offline analysis by tensorboard. Raises: ProfilerNotRunningError: If there is no active profiling session. Nz.Cannot stop profiling. No profiler is running.) rrrrrrexecutorwaitstop_run_num)resultrrrr#Xs      r#zE`tf.python.eager.profiler` has deprecated, use `tf.profiler` instead.cCsNt|D] }|trdSqtttj |d}| ttdS)zCreate an empty event file if not already exists. This event file indicates that we have a plugins/profile/ directory in the current logdir. Args: logdir: log directory. Nevents) r ListDirectoryendswith_EVENT_FILE_SUFFIXr EventsWriterras_bytesospathjoinInitWithSuffix)logdir file_name event_writerrrrmaybe_create_event_fileqs r3cCsvtj|ddtjd}t|t|t tj|dd}| |WddS1s4wYdS)zSave profile result to TensorBoard logdir. Args: logdir: log directory read by TensorBoard. result: profiling result returned by stop(). pluginsprofilez%Y-%m-%d_%H-%M-%Sz local.tracewbN) r,r-r.datetimenowstrftimerMakeDirsr3Openwrite)r0r% plugin_dirfrrrsaves   "r?z,use `tf.profiler.experimental.server.start`.cCs"tjtjkr tt|dS)aStart a profiler grpc server that listens to given port. The profiler server will keep the program running even the training finishes. Please shutdown the server with CTRL-C. It can be used in both eager mode and graph mode. The service defined in tensorflow/core/profiler/profiler_service.proto. Please use tensorflow/contrib/tpu/profiler/capture_tpu_profile to capture tracable file following https://cloud.google.com/tpu/docs/cloud-tpu-tools#capture_trace Args: port: port profiler server listens to. N)rrrrr start_server)portrrrstart_profiler_servers rBz/use `tf.profiler.experimental.Profile` instead.c@s(eZdZdZddZddZddZdS) ProfilerzContext-manager eager profiler api. Example usage: ```python with Profiler("/path/to/logdir"): # do some work ``` cCs ||_dSN)_logdir)selfr0rrr__init__ zProfiler.__init__cCs tdSrD)r)rFrrr __enter__rHzProfiler.__enter__cCst}t|j|dSrD)r#r?rE)rFtypvaluetbr%rrr__exit__szProfiler.__exit__N)r rr__doc__rGrIrMrrrrrCs   rCrD)#rNr7r, threadingtensorflow.python.clientrtensorflow.python.eagerrtensorflow.python.frameworkrtensorflow.python.platformrrr#tensorflow.python.profiler.internalrtensorflow.python.utilr"tensorflow.python.util.deprecationr rLockrr$r) Exceptionr rrr#r3r?rBobjectrCrrrrsH