0hdZddlZddlZddlmZddlmZdZdZ d dZ Gdd ejZ d d Z y) zCommon utils for benchmarks.N) callbacks)distribution_utilcnd|vsd|vr td|jddjdS)alSplit the suffix of the benchmark name. For example, for the name = 'benchmark_layer_call__Conv2D_small_shape', the return value is ['Conv2D', 'small', 'shape']. This is to generate the metadata of the benchmark test. Args: name: A string, the benchmark name. Returns: A list of strings of the suffix in the benchmark name. ___z*The format of the benchmark name is wrong.) ValueErrorsplit)names `/var/www/html/engine/venv/lib/python3.12/site-packages/tf_keras/src/benchmarks/benchmark_util.pyget_benchmark_namer s= 43d?EFF ::d B  % %c **c g}|D]Z}|j|Dcgc]}|ddzf|ddzc}|j|Dcgc]}|ddzf|ddzc}\|Scc}wcc}w)zExtend the benchmark names with CPU and GPU suffix. Args: *params_list: A list of tuples represents the benchmark parameters. Returns: A list of strings with the benchmark name extended with CPU and GPU suffix. r_CPUN_GPU)extend) params_listbenchmark_paramsparamsparams r !generate_benchmark_params_cpu_gpur,s =C DEuQx& "U12Y. D  =C DEuQx& "U12Y. D    E Es A$ A) c,d||zdt|zdS)Nkeras_examplesbs_) model_nameimplementation parameters)str) keras_model batch_sizeimpls r get_keras_examples_metadatar#As%'%,c*o- rc(eZdZdZdZdZdZdZy) TimerCallBackz1Callback for logging time in each epoch or batch.c|g|_tj|_tj|_d|_y)NF)timestimeit default_timertimer startup_timerecorded_startup)selfs r __init__zTimerCallBack.__init__Ns/ )) "002 %rc.|j|_yN)r*epoch_start_timer-elogss r on_epoch_beginzTimerCallBack.on_epoch_beginTs $ rcp|jj|j|jz yr0)r'appendr*r1r2s r on_epoch_endzTimerCallBack.on_epoch_endWs% $**,)>)>>?rcp|js*|j|jz |_d|_yy)NT)r,r*r+r2s r on_batch_endzTimerCallBack.on_batch_endZs1$$ $ t/@/@ @D $(D !%rN)__name__ __module__ __qualname____doc__r.r5r8r:rr r%r%Ks;& -@)rr%c | td| td| td| dkr td|jd} ggg}}} ggg}}}|| z}tj| | }t |D]R}t j }|}tj|}|5|}|}||z }|}|j|||||z }dddj|||d t}|}|j|||||g| |} | j|j|j|j|jtj|j|j| |z |j|| |z z Ug}|jd tj| d |jdtj|d |jdtj|d |jdtj|d |jdtj|d |jd|d tj|}!| | d}"||!|"fS#1swYxYw)aRun models and measure the performance. Args: model_fn: Model function to be benchmarked. x: Input data. See `x` in the `fit()` method of `keras.Model`. y: Target data. See `y` in the `fit()` method of `keras.Model`. epochs: Integer. Number of epochs to train the model. If unspecified, `epochs` will default to 2. batch_size: Integer. Number of samples per gradient update. If unspecified, `batch_size` will default to 32. run_iters: Integer. Number of iterations to run the performance measurement. If unspecified, `run_iters` will default to 4. optimizer: String (name of optimizer) or optimizer instance. See `keras.optimizers`. loss: String (name of objective function), objective function or `keras.losses.Loss` instance. See `keras.losses`. metrics: Lists of metrics to be evaluated by the model during training. See `metrics` in the `compile()` method of `keras.Model`. verbose: 0, 1, 2. Verbosity mode. See `verbose` in the `fit()` method of `keras.Model`. If unspecified, `verbose` will default to 0. num_gpus: Number of GPUs to run the model. distribution_strategy: Distribution strategies. It could be `multi_worker_mirrored`, `one_device`, `mirrored`. If unspecified, `distribution_strategy` will default to 'off'. Note that, `TPU` and `parameter_server` are not supported yet. Returns: Performance summary, which contains build_time, compile_time, startup_time, avg_epoch_time, wall_time, exp_per_sec, epochs, distribution_strategy. Raise: ValueError: If `x` is none or if `optimizer` is not provided or if `loss` is not provided or if `num_gpus` is negative. NzInput data is required.zOptimizer is required.zLoss function is required.rz`num_gpus` cannot be negative)distribution_strategynum_gpus) optimizerlossmetricsr)xyr!epochs)rFrGr!rHrverbose build_time)r value compile_timer+avg_epoch_time exp_per_secrH)r shaperget_distribution_strategyranger(r)get_strategy_scopecompilefitr%r7r+npmeanr')#model_fnrFrGrHr! run_itersrCrDrErIrBrA num_examplesbuild_time_listcompile_time_liststartup_time_listavg_epoch_time_listwall_time_listexp_per_sec_listtotal_num_examplesstrategyrr* start_timestrategy_scopet0modelrJt1rLcbkt2end_time wall_timeextrass# r measure_performancerl`sb y233  122 566 A899771:L<>B(9&O<>B)9,. ::3hH9 $F$$W *==hG  (BJE2JB MM#   !7RKK )z.keras.cfit_graph) NN NNNrroff)r>r(numpyrU tf_keras.srcrtf_keras.src.benchmarksrr rr#Callbackr%rlr?rr ruse# "5+&,#6)I&&).    @&r