BVh%dZddlZddlZddlmZddlmZddlmZ ddl m Z ddl m Z ddlmZGd d ej Zy) z6Test utilities for tf.data benchmarking functionality.N)session) dataset_ops)options)nest)context)testcJeZdZdZdZ ddZd dZ d dZ d dZy) DatasetBenchmarkBasez"Base class for dataset benchmarks.cbg}tjs tdt|D]l}|rt |}t |t |}t j }t |t j }|j||z ntj|S)aJBenchmark the iterable in eager mode. Runs the iterable `iters` times. In each iteration, the benchmark measures the time it takes to go execute the iterable. Args: iterable: The tf op or tf.data Dataset to benchmark. iters: Number of times to repeat the timing. warmup: If true, warms up the session caches by running an untimed run. Returns: A float, representing the median time (with respect to `iters`) it takes for the iterable to be executed `iters` num of times. Raises: RuntimeError: When executed in graph mode. z7Eager mode benchmarking is not supported in graph mode.) rexecuting_eagerly RuntimeErrorrangeiternexttimeappendnpmedian) selfiterableiterswarmupdeltas_iteratorstartends `/home/dcms/DCMS/lib/python3.12/site-packages/tensorflow/python/data/benchmarks/benchmark_base.py_run_eager_benchmarkz)DatasetBenchmarkBase._run_eager_benchmarks&F  $ $ &  C EE5\ ! > Xhhiike 8n IIKc mmC%K  ! 99V Ncg}tjr tdt|D]}t j |5}|r$|r|j ||j ||r|j |tj} |j |tj} ddd|j  z tj|S#1swY4xYw)a.Benchmarks the iterable in graph mode. Runs the iterable `iters` times. In each iteration, the benchmark measures the time it takes to go execute the iterable. Args: iterable: The tf op or tf.data Dataset to benchmark. iters: Number of times to repeat the timing. warmup: If true, warms up the session caches by running an untimed run. session_config: A ConfigProto protocol buffer with configuration options for the session. Applicable only for benchmarking in graph mode. initializer: The initializer op required to initialize the iterable. Returns: A float, representing the median time (with respect to `iters`) it takes for the iterable to be executed `iters` num of times. Raises: RuntimeError: When executed in eager mode. z7Graph mode benchmarking is not supported in eager mode.)configN) rr r rrSessionrunrrrr) rrrrsession_config initializerrrsessrrs r_run_graph_benchmarkz)DatasetBenchmarkBase._run_graph_benchmarkCs6F  "  C EE5\ ! ??. 1 T   HH[ ! ((8   ((;   iik  mmC%K  ! 99V   s A3C,,C5 c|tjr|j|||S|j||||S)aBenchmarks the op. Runs the op `iters` times. In each iteration, the benchmark measures the time it takes to go execute the op. Args: op: The tf op to benchmark. iters: Number of times to repeat the timing. warmup: If true, warms up the session caches by running an untimed run. session_config: A ConfigProto protocol buffer with configuration options for the session. Applicable only for benchmarking in graph mode. Returns: A float, representing the per-execution wall time of the op in seconds. This is the median time (with respect to `iters`) it takes for the op to be executed `iters` num of times. rrr)rrrr%)rr rr()roprrr%s rrun_op_benchmarkz%DatasetBenchmarkBase.run_op_benchmarkssK&  "  & &% & OO  $ $5 % PPr ctj}||j_|j |}|j |dz }t jr"|j|||}|t|z Stj|} | j} tj| dj} |j!| |||| j"}|t|z S)aBenchmarks the dataset. Runs the dataset `iters` times. In each iteration, the benchmark measures the time it takes to go through `num_elements` elements of the dataset. Args: dataset: Dataset to benchmark. num_elements: Number of dataset elements to iterate through each benchmark iteration. iters: Number of times to repeat the timing. warmup: If true, warms up the session caches by running an untimed run. apply_default_optimizations: Determines whether default optimizations should be applied. session_config: A ConfigProto protocol buffer with configuration options for the session. Applicable only for benchmarking in graph mode. Returns: A float, representing the per-element wall time of the dataset in seconds. This is the median time (with respect to `iters`) it takes for the dataset to go through `num_elements` elements, divided by `num_elements.` r*r)rrrr%r&) options_libOptionsexperimental_optimizationapply_default_optimizations with_optionsskiprr rfloatrmake_initializable_iteratorget_nextrflattenr+r(r&) rdataset num_elementsrrr2r%rmedian_durationr next_elementr+s r run_benchmarkz"DatasetBenchmarkBase.run_benchmarks>!!#G# %%A""7+Gll5tFD r )N)r.TN)r.TFN)NTFN) __name__ __module__ __qualname____doc__rr(r,r=rGr rr r sF*"R(, .`P805#' 91~&'&*&*;@.23r r )rLrnumpyrtensorflow.python.clientrtensorflow.python.data.opsrrr/tensorflow.python.data.utilrtensorflow.python.eagerrtensorflow.python.platformr Benchmarkr rMr rrUs4= ,2=,++^4>>^r