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--- |
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license: mit |
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dataset_info: |
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features: |
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- name: input_ids |
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sequence: int64 |
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- name: attention_mask |
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sequence: int64 |
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- name: labels |
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sequence: int64 |
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splits: |
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- name: train |
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num_bytes: 257967900 |
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num_examples: 20973 |
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- name: val |
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num_bytes: 45891300 |
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num_examples: 3731 |
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download_size: 10916827 |
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dataset_size: 303859200 |
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language: |
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- en |
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pretty_name: github-commits |
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size_categories: |
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- n<1K |
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--- |
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This dataset contains code changes in each commit of most starred python project, stored on GitHub. |
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## Code to reproduce the parsing process |
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To parse code we performed the following steps: |
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* Get list of most starred GitHub repos via API |
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* With **git** python package clone all the repos from the list to local machine and write code defference for each commit of every repo to the dataset. |
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* Clean dataset to remove to large commits, commits with not python code changes, commits with non-ASCII chars, etc. |
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* Group files changed in 1 commit into single sample of the dataset. |
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To reproduce these steps you need to: |
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1) run *src/github_parsing.ipynb* to parse repos from github |
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2) to clean the data and group dataset samples run *src/data_cleaning.ipynb* |
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## Dataset features |
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Dataset have the following features: |
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1) repo_name |
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2) commit_message |
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3) commit_changes - changes in code in all python files, contained in the commit |
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4) files_changed - number of files, changed in the commit |
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5) changes_len - number of chars in the code changes |
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For model training we used only *commit_message* feature as a label and *commit_changes* as an input for the model. |
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Code changes have the following structure: |
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``` |
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<filename> name_of_the_file <filename> |
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code_of_changes |
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<commit_msg> |
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``` |
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Special tokens used in the input: |
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* <file_name> - used to separate name of the file |
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* <code_del> and <code_add> used to separate added or deleted lines of code in the commit |
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* <commit_msg> used to separate commit message |
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Example of input for the model: |
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``` |
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<filename> a/tests/test_constraint.py b/tests/test_constraint.py<filename> |
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<code_del>--- a/tests/test_constraint.py<code_del> |
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<code_add>+++ b/tests/test_constraint.py<code_add> |
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@@ -87,10 +87,15 @@ def test_accurate_approximation_when_known(): |
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n_iter=10, |
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) |
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<code_del>- params = optimizer.res[0]["params"]<code_del> |
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<code_del>- x, y = params['x'], params['y']<code_del> |
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<code_add>+ # Exclude the last sampled point, because the constraint is not fitted on that.<code_add> |
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<code_add>+ res = np.array([[r['target'], r['constraint'], r['params']['x'], r['params']['y']] for r in optimizer.res[:-1]])<code_add> |
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<code_add>+<code_add> |
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<code_add>+ xy = res[:, [2, 3]]<code_add> |
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<code_add>+ x = res[:, 2]<code_add> |
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<code_add>+ y = res[:, 3]<code_add> |
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<code_del>- assert constraint_function(x, y) == approx(conmod.approx(np.array([x, y])), rel=1e-5, abs=1e-5)<code_del> |
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<code_add>+ assert constraint_function(x, y) == approx(conmod.approx(xy), rel=1e-5, abs=1e-5)<code_add> |
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<code_add>+ assert constraint_function(x, y) == approx(optimizer.space.constraint_values[:-1], rel=1e-5, abs=1e-5)<code_add> |
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def test_multiple_constraints(): |
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<commit_msg>In case of commit with the several files changed, different files are separated with 3 blank lines.<eos> |
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``` |
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In case of commit with the several files changed, different files are separated with 3 blank lines. |