<jupyter_start><jupyter_text>Performance Regression AnalysisThis notebook is used to compare the current performance with that of a previously recorded snapshot.*Note*: executing the below cells for the first time after starting the notebook will take long<jupyter_code>:sccache 1
:dep prover-lab = { path = "../.." }
use prover_lab::benchmark::*;
let mut last = read_benchmark("default.last.mod_data")?;
let mut current = read_benchmark("default.mod_data")?;
last.sort(); // Will also determine order of other samples.
plot_benchmarks(&[&last, &current])<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.11282051282051282, 'fraction_numerical': 0.0017094017094017094, 'mean_word_length': 6.417721518987341, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, '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': '579578', 'license': 'Apache-2.0', 'n_tokens_mistral': 170, 'n_tokens_neox': 167, 'n_words': 57, 'path': 'language/move-prover/lab/data/regression/notebook.ipynb', 'repo_name': 'gustavoguimaraes/libra', 'size': '585'}