49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
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import os
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import pandas as pd
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import seaborn as sns
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import matplotlib.pyplot as plt
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from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
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def tabulate_events(dpath):
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files = os.listdir(dpath)[0]
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summary_iterators = [EventAccumulator(os.path.join(dpath, files)).Reload()]
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tags = summary_iterators[0].Tags()['scalars']
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for it in summary_iterators:
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assert it.Tags()['scalars'] == tags
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out = {t: [] for t in tags}
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steps = []
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for tag in tags:
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steps = [e.step for e in summary_iterators[0].Scalars(tag)]
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for events in zip(*[acc.Scalars(tag) for acc in summary_iterators]):
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assert len(set(e.step for e in events)) == 1
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out[tag].append([e.value for e in events])
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return out, steps
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events, steps = tabulate_events('/home/vedant/pytorch_sac_ae/log/runs')
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data = []
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for tag, values in events.items():
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for run_idx, run_values in enumerate(values):
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for step_idx, value in enumerate(run_values):
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data.append({
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'tag': tag,
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'run': run_idx,
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'step': steps[step_idx],
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'value': value,
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})
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df = pd.DataFrame(data)
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print(df.head())
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plt.figure(figsize=(10,6))
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sns.lineplot(data=df, x='step', y='value', hue='tag', ci='sd')
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plt.show()
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