Add EMON, VTune, psrecord, ITTpy support in benchmarks#115
Add EMON, VTune, psrecord, ITTpy support in benchmarks#115masdevas wants to merge 1 commit intoIntelPython:mainfrom
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| def time_box_filter(func, *args, n_meas, time_limit, **kwargs): | ||
| def detect_LLC_size(): | ||
| with open('/sys/devices/system/cpu/cpu0/cache/index3/size', 'r') as f: |
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Add support for all systems or exception for non-Linux
| print('# Intel(R) Extension for Scikit-learn case result:') | ||
| print(json.dumps(output, indent=4)) | ||
| print('# Intel(R) Extension for Scikit-learn case finished.') |
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sklbench may not use sklearnex, so, this outputs will be confusing for some cases
| ################################################################################## | ||
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| #ruby interpreter, change it according to the path where ruby is installed in your system | ||
| #RUBY_PATH="c:\Ruby192\bin\ruby.exe" |
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Are these commented lines required to be included?
| fit_time, _ = bench.measure_function_time(regr.fit, X_train, y_train, box_filter_measurements=params.box_filter_measurements_fit, time_limit=params.time_limit_fit, params=params, stage='fit') | ||
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| # Time predict | ||
| predict_time, yp = bench.measure_function_time(regr.predict, X_test, params=params) | ||
| predict_time, yp = bench.measure_function_time(regr.predict, X_test, box_filter_measurements=params.box_filter_measurements_infer, time_limit=params.time_limit_infer, params=params, stage='infer') |
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Why only ridge regression includes box_filter_measurements, time_limit and params arguments?
| common_params = config['common'] | ||
| for params_set in config['cases']: | ||
| params = common_params.copy() | ||
| # print('PRE PARAMS:', params) |
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Remove commented code
| #RUBY_OPTIONS=--server -J-Xmx5g -J-Xms5g --1.8 | ||
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| #Number of threads to process data in parallel. Typically it should equal to the number of logical CPUs in your processing system. | ||
| PARALLELISM=24 |
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Avoid hardcoded number of threads
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| # Time fit | ||
| time, _ = bench.measure_function_time(dbscan.fit, X, params=params) | ||
| time, _ = bench.measure_function_time(dbscan.fit, X, params=params, stage='fit') |
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Try to align stage and stages arguments of bench.measure_function_time and bench.print_output if possible
| analysis_stage_collection = ['default'] | ||
| if analysis_prefix != None: | ||
| analysis_stage_collection.extend(['fit', 'infer']) | ||
| for analysis_stage in analysis_stage_collection: |
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Check that non-measured stage is not included in single benchmark output
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| def flush_caches(): | ||
| flush_datafile = 'data/flush_data.npy' | ||
| if os.path.exists(flush_datafile): |
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You can add a check to see if the file is in datasets_root
| try: | ||
| import itt | ||
| itt_module_installed = True | ||
| except: |
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| except: | |
| except ImportError: |
| iterations_to_flush = 3 | ||
| try: | ||
| from sklearnex.cluster import KMeans | ||
| except: |
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| except: | |
| except ImportError: |
| if key in analysis_config.keys(): | ||
| args = dict_to_cmd_args(analysis_config[key]) | ||
| return args | ||
| else: |
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What condition does this else belong to?
Same for the 107 line
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