# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import sys import time import numpy as np class Progbar(object): """Displays a progress bar. refers to https://github.com/keras-team/keras/blob/keras-2/keras/utils/generic_utils.py Arguments: target: Total number of steps expected, None if unknown. width: Progress bar width on screen. verbose: Verbosity mode, 0 (silent), 1 (verbose), 2 (semi-verbose) stateful_metrics: Iterable of string names of metrics that should *not* be averaged over time. Metrics in this list will be displayed as-is. All others will be averaged by the progbar before display. interval: Minimum visual progress update interval (in seconds). unit_name: Display name for step counts (usually "step" or "sample"). """ def __init__(self, target, width=30, verbose=1, interval=0.05, stateful_metrics=None, unit_name='step'): self.target = target self.width = width self.verbose = verbose self.interval = interval self.unit_name = unit_name if stateful_metrics: self.stateful_metrics = set(stateful_metrics) else: self.stateful_metrics = set() self._dynamic_display = ((hasattr(sys.stdout, 'isatty') and sys.stdout.isatty()) or 'ipykernel' in sys.modules or 'posix' in sys.modules or 'PYCHARM_HOSTED' in os.environ) self._total_width = 0 self._seen_so_far = 0 # We use a dict + list to avoid garbage collection # issues found in OrderedDict self._values = {} self._values_order = [] self._start = time.time() self._last_update = 0 def update(self, current, values=None, finalize=None): """Updates the progress bar. Arguments: current: Index of current step. values: List of tuples: `(name, value_for_last_step)`. If `name` is in `stateful_metrics`, `value_for_last_step` will be displayed as-is. Else, an average of the metric over time will be displayed. finalize: Whether this is the last update for the progress bar. If `None`, defaults to `current >= self.target`. """ if finalize is None: if self.target is None: finalize = False else: finalize = current >= self.target values = values or [] for k, v in values: if k not in self._values_order: self._values_order.append(k) if k not in self.stateful_metrics: # In the case that progress bar doesn't have a target value in the first # epoch, both on_batch_end and on_epoch_end will be called, which will # cause 'current' and 'self._seen_so_far' to have the same value. Force # the minimal value to 1 here, otherwise stateful_metric will be 0s. value_base = max(current - self._seen_so_far, 1) if k not in self._values: self._values[k] = [v * value_base, value_base] else: self._values[k][0] += v * value_base self._values[k][1] += value_base else: # Stateful metrics output a numeric value. This representation # means "take an average from a single value" but keeps the # numeric formatting. self._values[k] = [v, 1] self._seen_so_far = current now = time.time() info = ' - %.0fs' % (now - self._start) if self.verbose == 1: if now - self._last_update < self.interval and not finalize: return prev_total_width = self._total_width if self._dynamic_display: sys.stdout.write('\b' * prev_total_width) sys.stdout.write('\r') else: sys.stdout.write('\n') if self.target is not None: numdigits = int(np.log10(self.target)) + 1 bar = ('%' + str(numdigits) + 'd/%d [') % (current, self.target) prog = float(current) / self.target prog_width = int(self.width * prog) if prog_width > 0: bar += ('=' * (prog_width - 1)) if current < self.target: bar += '>' else: bar += '=' bar += ('.' * (self.width - prog_width)) bar += ']' else: bar = '%7d/Unknown' % current self._total_width = len(bar) sys.stdout.write(bar) if current: time_per_unit = (now - self._start) / current else: time_per_unit = 0 if self.target is None or finalize: if time_per_unit >= 1 or time_per_unit == 0: info += ' %.0fs/%s' % (time_per_unit, self.unit_name) elif time_per_unit >= 1e-3: info += ' %.0fms/%s' % (time_per_unit * 1e3, self.unit_name) else: info += ' %.0fus/%s' % (time_per_unit * 1e6, self.unit_name) else: eta = time_per_unit * (self.target - current) if eta > 3600: eta_format = '%d:%02d:%02d' % (eta // 3600, (eta % 3600) // 60, eta % 60) elif eta > 60: eta_format = '%d:%02d' % (eta // 60, eta % 60) else: eta_format = '%ds' % eta info = ' - ETA: %s' % eta_format for k in self._values_order: info += ' - %s:' % k if isinstance(self._values[k], list): avg = np.mean( self._values[k][0] / max(1, self._values[k][1])) if abs(avg) > 1e-3: info += ' %.4f' % avg else: info += ' %.4e' % avg else: info += ' %s' % self._values[k] self._total_width += len(info) if prev_total_width > self._total_width: info += (' ' * (prev_total_width - self._total_width)) if finalize: info += '\n' sys.stdout.write(info) sys.stdout.flush() elif self.verbose == 2: if finalize: numdigits = int(np.log10(self.target)) + 1 count = ('%' + str(numdigits) + 'd/%d') % (current, self.target) info = count + info for k in self._values_order: info += ' - %s:' % k avg = np.mean( self._values[k][0] / max(1, self._values[k][1])) if avg > 1e-3: info += ' %.4f' % avg else: info += ' %.4e' % avg info += '\n' sys.stdout.write(info) sys.stdout.flush() self._last_update = now def add(self, n, values=None): self.update(self._seen_so_far + n, values)