# Copyright (c) 2018-2020, NVIDIA CORPORATION. All rights reserved. # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. from pytablewriter import MarkdownTableWriter class TrainingTable: def __init__(self, acc_unit='BLEU', time_unit='min', perf_unit='tok/s'): self.data = [] self.acc_unit = acc_unit self.time_unit = time_unit self.perf_unit = perf_unit self.time_unit_convert = {'s': 1, 'min': 1/60, 'h': 1/3600} def add(self, gpus, batch_size, accuracy, perf, time_to_train): time_to_train *= self.time_unit_convert[self.time_unit] if not accuracy: accuracy = 0.0 accuracy = round(accuracy, 2) self.data.append([gpus, batch_size, accuracy, perf, time_to_train]) def write(self, title, math): writer = MarkdownTableWriter() writer.table_name = f'{title}' header = [f'**GPUs**', f'**Batch Size / GPU**', f'**Accuracy - {math.upper()} ({self.acc_unit})**', f'**Throughput - {math.upper()} ({self.perf_unit})**', f'**Time to Train - {math.upper()} ({self.time_unit})**', ] writer.headers = header writer.value_matrix = self.data writer.write_table()