tools/accuracy_checker/accuracy_checker/progress_reporters.py

   1 """
   2 Copyright (c) 2019 Intel Corporation
   3
   4 Licensed under the Apache License, Version 2.0 (the "License");
   5 you may not use this file except in compliance with the License.
   6 You may obtain a copy of the License at
   7
   8       http://www.apache.org/licenses/LICENSE-2.0
   9
  10 Unless required by applicable law or agreed to in writing, software
  11 distributed under the License is distributed on an "AS IS" BASIS,
  12 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  13 See the License for the specific language governing permissions and
  14 limitations under the License.
  15 """
  16
  17 import time
  18
  19 from tqdm import tqdm
  20
  21 from .dependency import ClassProvider
  22 from .logging import print_info
  23
  24
  25 class ProgressReporter(ClassProvider):
  26     __provider_type__ = 'progress_reporter'
  27
  28     def __init__(self, dataset_size=None):
  29         self.finished = True
  30         self.dataset_size = None
  31         self.start_time = None
  32         self.prev_time = None
  33         if dataset_size is not None:
  34             self.reset(dataset_size)
  35
  36     def finish(self, objects_processed=True):
  37         self.finished = True
  38         if not objects_processed:
  39             return
  40
  41         process_time = time.time() - self.start_time
  42         print_info('{} objects processed in {:.3f} seconds'.format(self.dataset_size, process_time))
  43
  44     def reset(self, dataset_size):
  45         if not self.finished:
  46             self.finish(objects_processed=False)
  47
  48         self.dataset_size = dataset_size
  49         self.start_time = time.time()
  50         self.finished = False
  51
  52
  53 class PrintProgressReporter(ProgressReporter):
  54     __provider__ = 'print'
  55
  56     def __init__(self, dataset_size=None, print_interval=1000):
  57         super().__init__(dataset_size)
  58         self.print_interval = print_interval
  59
  60     def reset(self, dataset_size):
  61         self.dataset_size = dataset_size
  62         print_info('Total dataset size: {}'.format(dataset_size))
  63         self.start_time = time.time()
  64         self.prev_time = self.start_time
  65
  66     def update(self, batch_id, batch_size):
  67         if (batch_id + 1) % self.print_interval != 0:
  68             return
  69
  70         now = time.time()
  71         batch_time = now - self.prev_time
  72         self.prev_time = now
  73
  74         print_info('{} / {} processed in {:.3f}s'.format((batch_id + 1) * batch_size, self.dataset_size, batch_time))
  75
  76
  77 class TQDMReporter(ProgressReporter):
  78     __provider__ = 'bar'
  79
  80     def update(self, _batch_id, batch_size):
  81         self.tqdm.update(batch_size)
  82
  83     def finish(self, objects_processed=True):
  84         self.tqdm.close()
  85         super().finish(objects_processed)
  86
  87     def reset(self, dataset_size):
  88         super().reset(dataset_size)
  89         self.tqdm = tqdm(
  90             total=self.dataset_size, unit='frames', leave=False,
  91             bar_format='{l_bar}{bar}| {n_fmt}/{total_fmt} [{elapsed}<{remaining}]'
  92         )