diff options
3 files changed, 66 insertions, 52 deletions
diff --git a/tensorflow/python/keras/_impl/keras/callbacks.py b/tensorflow/python/keras/_impl/keras/callbacks.py index b29bc39232..de013c7c3f 100644 --- a/tensorflow/python/keras/_impl/keras/callbacks.py +++ b/tensorflow/python/keras/_impl/keras/callbacks.py @@ -328,7 +328,7 @@ class ProgbarLogger(Callback): if k in logs: self.log_values.append((k, logs[k])) if self.verbose: - self.progbar.update(self.seen, self.log_values, force=True) + self.progbar.update(self.seen, self.log_values) @tf_export('keras.callbacks.History') diff --git a/tensorflow/python/keras/_impl/keras/utils/generic_utils.py b/tensorflow/python/keras/_impl/keras/utils/generic_utils.py index fa3b55c59e..462d600bf8 100644 --- a/tensorflow/python/keras/_impl/keras/utils/generic_utils.py +++ b/tensorflow/python/keras/_impl/keras/utils/generic_utils.py @@ -291,55 +291,73 @@ class Progbar(object): 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). """ - def __init__(self, target, width=30, verbose=1, interval=0.05): - self.width = width - if target is None: - target = -1 + def __init__(self, target, width=30, verbose=1, interval=0.05, + stateful_metrics=None): self.target = target - self.sum_values = {} - self.unique_values = [] - self.start = time.time() - self.last_update = 0 - self.interval = interval - self.total_width = 0 - self.seen_so_far = 0 + self.width = width self.verbose = verbose + self.interval = interval + 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) - - def update(self, current, values=None, force=False): + 'ipykernel' in sys.modules or + 'posix' in sys.modules) + 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): """Updates the progress bar. Arguments: current: Index of current step. - values: List of tuples (name, value_for_last_step). - The progress bar will display averages for these values. - force: Whether to force visual progress update. + 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. """ values = values or [] for k, v in values: - if k not in self.sum_values: - self.sum_values[k] = [ - v * (current - self.seen_so_far), current - self.seen_so_far - ] - self.unique_values.append(k) + if k not in self._values_order: + self._values_order.append(k) + if k not in self.stateful_metrics: + if k not in self._values: + self._values[k] = [v * (current - self._seen_so_far), + current - self._seen_so_far] + else: + self._values[k][0] += v * (current - self._seen_so_far) + self._values[k][1] += (current - self._seen_so_far) else: - self.sum_values[k][0] += v * (current - self.seen_so_far) - self.sum_values[k][1] += (current - self.seen_so_far) - self.seen_so_far = current + self._values[k] = v + self._seen_so_far = current now = time.time() - info = ' - %.0fs' % (now - self.start) + info = ' - %.0fs' % (now - self._start) if self.verbose == 1: - if (not force and (now - self.last_update) < self.interval and - current < self.target): + if (now - self._last_update < self.interval and + self.target is not None and current < self.target): return - prev_total_width = self.total_width + prev_total_width = self._total_width if self._dynamic_display: sys.stdout.write('\b' * prev_total_width) sys.stdout.write('\r') @@ -360,22 +378,21 @@ class Progbar(object): bar += '=' bar += ('.' * (self.width - prog_width)) bar += ']' - sys.stdout.write(bar) - self.total_width = len(bar) else: bar = '%7d/Unknown' % current - self.total_width = len(bar) + self._total_width = len(bar) sys.stdout.write(bar) if current: - time_per_unit = (now - self.start) / current + time_per_unit = (now - self._start) / current else: time_per_unit = 0 if self.target is not None and current < self.target: eta = time_per_unit * (self.target - current) if eta > 3600: - eta_format = '%d:%02d:%02d' % (eta // 3600, (eta % 3600) // 60, + eta_format = '%d:%02d:%02d' % (eta // 3600, + (eta % 3600) // 60, eta % 60) elif eta > 60: eta_format = '%d:%02d' % (eta // 60, eta % 60) @@ -391,35 +408,32 @@ class Progbar(object): else: info += ' %.0fus/step' % (time_per_unit * 1e6) - for k in self.unique_values: + for k in self._values_order: info += ' - %s:' % k - if isinstance(self.sum_values[k], list): - avg = np.mean(self.sum_values[k][0] / max(1, self.sum_values[k][1])) + 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.sum_values[k] + info += ' %s' % self._values[k] + + self._total_width += len(info) + if prev_total_width > self._total_width: + info += (' ' * (prev_total_width - self._total_width)) - self.total_width += len(info) - if prev_total_width > self.total_width: - info += (' ' * (prev_total_width - self.total_width)) if self.target is not None and current >= self.target: info += '\n' sys.stdout.write(info) sys.stdout.flush() - if current >= self.target: - sys.stdout.write('\n') - elif self.verbose == 2: if self.target is None or current >= self.target: - for k in self.unique_values: + for k in self._values_order: info += ' - %s:' % k - avg = np.mean( - self.sum_values[k][0] / max(1, self.sum_values[k][1])) + avg = np.mean(self._values[k][0] / max(1, self._values[k][1])) if avg > 1e-3: info += ' %.4f' % avg else: @@ -429,10 +443,10 @@ class Progbar(object): sys.stdout.write(info) sys.stdout.flush() - self.last_update = now + self._last_update = now def add(self, n, values=None): - self.update(self.seen_so_far + n, values) + self.update(self._seen_so_far + n, values) def make_batches(size, batch_size): diff --git a/tensorflow/tools/api/golden/tensorflow.keras.utils.-progbar.pbtxt b/tensorflow/tools/api/golden/tensorflow.keras.utils.-progbar.pbtxt index 3adc6b6faa..16e1cbe650 100644 --- a/tensorflow/tools/api/golden/tensorflow.keras.utils.-progbar.pbtxt +++ b/tensorflow/tools/api/golden/tensorflow.keras.utils.-progbar.pbtxt @@ -4,7 +4,7 @@ tf_class { is_instance: "<type \'object\'>" member_method { name: "__init__" - argspec: "args=[\'self\', \'target\', \'width\', \'verbose\', \'interval\'], varargs=None, keywords=None, defaults=[\'30\', \'1\', \'0.05\'], " + argspec: "args=[\'self\', \'target\', \'width\', \'verbose\', \'interval\', \'stateful_metrics\'], varargs=None, keywords=None, defaults=[\'30\', \'1\', \'0.05\', \'None\'], " } member_method { name: "add" @@ -12,6 +12,6 @@ tf_class { } member_method { name: "update" - argspec: "args=[\'self\', \'current\', \'values\', \'force\'], varargs=None, keywords=None, defaults=[\'None\', \'False\'], " + argspec: "args=[\'self\', \'current\', \'values\'], varargs=None, keywords=None, defaults=[\'None\'], " } } |