<jupyter_start><jupyter_text>GR Tuning Results<jupyter_code>%cd ~/Desktop/research_project_repo/research_project/experiments/vgg_gr_tuning/2021-05-01-02-11/
logs = !ls 
metrics = Metrics(logs)
df = metrics.get_metrics_df()
df<jupyter_output><empty_output><jupyter_text>Accuracy<jupyter_code>fig, ax = plt.subplots(figsize=(8, 5))         # Sample figsize in inches
sns.heatmap(df.pivot('iters','g_fc_uni','Accuracy'), annot=True, linewidths=.5, ax=ax)

# Source for the code below: https://github.com/mwaskom/seaborn/issues/1773
b, t = plt.ylim() 
b += 0.5 
t -= 0.5 
plt.ylim(b, t) 
ax.invert_yaxis()

plt.show()<jupyter_output><empty_output><jupyter_text>GPU Memory<jupyter_code>fig, ax = plt.subplots(figsize=(8, 5))         # Sample figsize in inches
sns.heatmap(df.pivot('iters','g_fc_uni','GPU Memory (MB)'), annot=True, linewidths=.5, ax=ax)

# Source for the code below: https://github.com/mwaskom/seaborn/issues/1773
b, t = plt.ylim() 
b += 0.5 
t -= 0.5 
plt.ylim(b, t) 
ax.invert_yaxis()

plt.show()<jupyter_output><empty_output><jupyter_text>GPU Usage<jupyter_code>fig, ax = plt.subplots(figsize=(8, 5))         # Sample figsize in inches
sns.heatmap(df.pivot('iters','g_fc_uni','GPU Usage (%)'), annot=True, linewidths=.5, ax=ax)

# Source for the code below: https://github.com/mwaskom/seaborn/issues/1773
b, t = plt.ylim() 
b += 0.5 
t -= 0.5 
plt.ylim(b, t) 
ax.invert_yaxis()

plt.show()<jupyter_output><empty_output>
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{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '280820', 'license': 'MIT', 'n_tokens_mistral': 662, 'n_tokens_neox': 618, 'n_words': 100, 'path': 'analysis/VGG_GR_Tuning.ipynb', 'repo_name': 'samuilstoychev/research_project', 'size': '1434'}