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import re | |
def read_data_from_tensorboard(log_path, tag): | |
"""Get raw data (steps and values) from tensorboard events. | |
Args: | |
log_path (str): Path to the tensorboard log. | |
tag (str): tag to be read. | |
""" | |
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator | |
# tensorboard event | |
event_acc = EventAccumulator(log_path) | |
event_acc.Reload() | |
scalar_list = event_acc.Tags()['scalars'] | |
print('tag list: ', scalar_list) | |
steps = [int(s.step) for s in event_acc.Scalars(tag)] | |
values = [s.value for s in event_acc.Scalars(tag)] | |
return steps, values | |
def read_data_from_txt_2v(path, pattern, step_one=False): | |
"""Read data from txt with 2 returned values (usually [step, value]). | |
Args: | |
path (str): path to the txt file. | |
pattern (str): re (regular expression) pattern. | |
step_one (bool): add 1 to steps. Default: False. | |
""" | |
with open(path) as f: | |
lines = f.readlines() | |
lines = [line.strip() for line in lines] | |
steps = [] | |
values = [] | |
pattern = re.compile(pattern) | |
for line in lines: | |
match = pattern.match(line) | |
if match: | |
steps.append(int(match.group(1))) | |
values.append(float(match.group(2))) | |
if step_one: | |
steps = [v + 1 for v in steps] | |
return steps, values | |
def read_data_from_txt_1v(path, pattern): | |
"""Read data from txt with 1 returned values. | |
Args: | |
path (str): path to the txt file. | |
pattern (str): re (regular expression) pattern. | |
""" | |
with open(path) as f: | |
lines = f.readlines() | |
lines = [line.strip() for line in lines] | |
data = [] | |
pattern = re.compile(pattern) | |
for line in lines: | |
match = pattern.match(line) | |
if match: | |
data.append(float(match.group(1))) | |
return data | |
def smooth_data(values, smooth_weight): | |
""" Smooth data using 1st-order IIR low-pass filter (what tensorflow does). | |
Reference: https://github.com/tensorflow/tensorboard/blob/f801ebf1f9fbfe2baee1ddd65714d0bccc640fb1/tensorboard/plugins/scalar/vz_line_chart/vz-line-chart.ts#L704 # noqa: E501 | |
Args: | |
values (list): A list of values to be smoothed. | |
smooth_weight (float): Smooth weight. | |
""" | |
values_sm = [] | |
last_sm_value = values[0] | |
for value in values: | |
value_sm = last_sm_value * smooth_weight + (1 - smooth_weight) * value | |
values_sm.append(value_sm) | |
last_sm_value = value_sm | |
return values_sm | |