| | import re
|
| |
|
| |
|
| | def read_data_from_tensorboard(log_path, tag):
|
| | """Get raw data (steps and values) from tensorboard events.
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| |
|
| | Args:
|
| | log_path (str): Path to the tensorboard log.
|
| | tag (str): tag to be read.
|
| | """
|
| | from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
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| |
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| |
|
| | event_acc = EventAccumulator(log_path)
|
| | event_acc.Reload()
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| | 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
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| |
|
| |
|
| | def read_data_from_txt_2v(path, pattern, step_one=False):
|
| | """Read data from txt with 2 returned values (usually [step, value]).
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| |
|
| | Args:
|
| | path (str): path to the txt file.
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| | 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 = []
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| |
|
| | pattern = re.compile(pattern)
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| | 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
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| |
|
| |
|
| | 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).
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| |
|
| | 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
|
| |
|
