<jupyter_start><jupyter_text>all times are in us (seconds * 1e-6)<jupyter_code># times to construct res net
construct_df = df[df.type=='construct']
for inst, data in construct_df.groupby('inst'):
    plt.bar(data=data, x='alg', height='time')
    print(inst)
    plt.show()
for inst, inst_data in df.groupby('inst'):
    print(inst)
    for typ in ['low','high','gh']:
        fig,ax = plt.subplots(figsize=(16,4))
        xoff = 0
        for alg, data in inst_data[inst_data.type==typ].groupby('alg'):
            yoff = [0]*(data.iter.max()+1)
            for stage in pd.unique(data.stage):
                ys = data[data.stage==stage].time
                xs = [i*5+xoff-1.5 for i in range(len(ys))]
                ax.bar(xs, ys, label=alg+' '+stage, bottom=yoff)
                i = 0
                for val in ys:
                    yoff[i] += val
                    i += 1
            xoff += 1

        ax.set_xticks([i*5+2.5 for i in range(9)], minor=True)
        ax.grid(which='minor', axis='x')
        ax.set_title(typ)

        plt.legend()
        plt.show()<jupyter_output>girg10000.txt
{'fraction_non_alphanumeric': 0.15808491418247517, 'fraction_numerical': 0.02077687443541102, 'mean_word_length': 2.0523415977961434, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '496239', 'license': 'MIT', 'n_tokens_mistral': 412, 'n_tokens_neox': 385, 'n_words': 85, 'path': 'plots/paper_runtime2.ipynb', 'repo_name': 'chistopher/scale-free-flow', 'size': '1107'}