Datasets:

semeru

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text-code-galeras-code-generation-from-docstring-3k-deduped

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Semeru Lab 7

def dist_from_wheel_url(name, url, session): # type: (str, str, PipSession) -> Distribution with LazyZipOverHTTP(url, session) as wheel: # For read-only ZIP files, ZipFile only needs methods read, # seek, seekable and tell, not the whole IO protocol. zip_file = ZipFile(wheel) # type: ignore # After context manager exit, wheel.name # is an invalid file by intention. return pkg_resources_distribution_for_wheel(zip_file, name, wheel.name)

.venv/lib/python3.8/site-packages/pip/_internal/network/lazy_wheel.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

lazy_wheel.py

dist_from_wheel_url

https://github.com/jindongwang/transferlearning.git

upd; format

def _configure_experiment_defaults(self): for option in self._exclude_autolog: if not self.experiment_kwargs.get(option): self.experiment_kwargs[option] = False

python/ray/tune/integration/comet.py

ray

Python

3d79815cd08c1be8e56c245e662f34366523847e

comet.py

_configure_experiment_defaults

https://github.com/ray-project/ray.git

Comet Integration (#20766) This PR adds a `CometLoggerCallback` to the Tune Integrations, allowing users to log runs from Ray to [Comet](https://www.comet.ml/site/). Co-authored-by: Michael Cullan <mjcullan@gmail.com> Co-authored-by: Antoni Baum <antoni.baum@protonmail.com>

def add_group_component(self, components, name, group): new_comp = components[components['component'].isin(set(group))].copy() group_cols = new_comp['col'].unique() if len(group_cols) > 0: new_comp = pd.DataFrame({'col': group_cols, 'component': name}) components = pd.concat([components, new_comp]) return components

python/prophet/forecaster.py

prophet

Python

10310ceb2da05837a198db6714d658a1e0a32478

forecaster.py

add_group_component

https://github.com/facebook/prophet.git

Change deprecated `append` to `concat` (#2114)

def permission_denied(request, exception, template_name=ERROR_403_TEMPLATE_NAME): try: template = loader.get_template(template_name) except TemplateDoesNotExist: if template_name != ERROR_403_TEMPLATE_NAME: # Reraise if it's a missing custom template. raise return HttpResponseForbidden( ERROR_PAGE_TEMPLATE % {"title": "403 Forbidden", "details": ""}, content_type="text/html", ) return HttpResponseForbidden( template.render(request=request, context={"exception": str(exception)}) )

django/views/defaults.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

defaults.py

permission_denied

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def transpose_qkv(X, num_heads): # Shape of input `X`: # (`batch_size`, no. of queries or key-value pairs, `num_hiddens`). # Shape of output `X`: # (`batch_size`, no. of queries or key-value pairs, `num_heads`, # `num_hiddens` / `num_heads`) X = X.reshape(X.shape[0], X.shape[1], num_heads, -1) # Shape of output `X`: # (`batch_size`, `num_heads`, no. of queries or key-value pairs, # `num_hiddens` / `num_heads`) X = X.transpose(0, 2, 1, 3) # Shape of `output`: # (`batch_size` * `num_heads`, no. of queries or key-value pairs, # `num_hiddens` / `num_heads`) return X.reshape(-1, X.shape[2], X.shape[3])

d2l/mxnet.py

d2l-zh

Python

b64b41d8c1ac23c43f7a4e3f9f6339d6f0012ab2

mxnet.py

transpose_qkv

https://github.com/d2l-ai/d2l-zh.git

[PaddlePaddle] Merge master into Paddle branch (#1186) * change 15.2 title in chinese version (#1109) change title ’15.2. 情感分析：使用递归神经网络‘ to ’15.2. 情感分析：使用循环神经网络‘ * 修改部分语义表述 (#1105) * Update r0.17.5 (#1120) * Bump versions in installation * 94行typo: （“bert.mall”）->（“bert.small”） (#1129) * line 313: "bert.mall" -> "bert.small" (#1130) * fix: update language as native reader (#1114) * Fix the translation of "stride" (#1115) * Update index.md (#1118) 修改部分语义表述 * Update self-attention-and-positional-encoding.md (#1133) 依照本书的翻译习惯，将pooling翻译成汇聚 * maybe a comment false (#1149) * maybe a little false * maybe a little false * A minor bug in the rcnn section (Chinese edition) (#1148) * Update bert.md (#1137) 一个笔误 # 假设batch_size=2，num_pred_positions=3 # 那么batch_idx应该是np.repeat( [0,1], 3 ) = [0,0,0,1,1,1] * Update calculus.md (#1135) * fix typo in git documentation (#1106) * fix: Update the Chinese translation in lr-scheduler.md (#1136) * Update lr-scheduler.md * Update chapter_optimization/lr-scheduler.md Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * fix translation for kaggle-house-price.md (#1107) * fix translation for kaggle-house-price.md * fix translation for kaggle-house-price.md Signed-off-by: sunhaizhou <haizhou.sun@smartmore.com> * Update weight-decay.md (#1150) * Update weight-decay.md 关于“k多选d”这一部分，中文读者使用排列组合的方式可能更容易理解 关于“给定k个变量，阶数的个数为...”这句话是有歧义的，不是很像中国话，应该是说“阶数为d的项的个数为...”。 并增加了一句对“因此即使是阶数上的微小变化，比如从$2$到$3$，也会显著增加我们模型的复杂性。”的解释 解释为何会增加复杂性以及为何需要细粒度工具。 * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Update chapter_multilayer-perceptrons/weight-decay.md yep Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Fix a spelling error (#1161) * Update gru.md (#1152) The key distinction between vanilla RNNs and GRUs is that the latter support gating of the hidden state. 翻译错误 * Unify the function naming (#1113) Unify naming of the function 'init_xavier()'. * Update mlp-concise.md (#1166) * Update mlp-concise.md 语句不通顺 * Update environment.md 语序异常 * Update config.ini * fix the imprecise description (#1168) Co-authored-by: yuande <yuande> * fix typo in chapter_natural-language-processing-pretraining/glove.md (#1175) * Fix some typos. (#1163) * Update batch-norm.md (#1170) fixing typos u->x in article * Update linear-regression.md (#1090) We invoke Stuart Russell and Peter Norvig who, in their classic AI text book Artificial Intelligence: A Modern Approach :cite:Russell.Norvig.2016, pointed out that 原译文把who也直接翻译出来了。 * Update mlp.md (#1117) * Update mlp.md 修改部分语义表述 * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Update chapter_multilayer-perceptrons/mlp.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> * Correct a translation error. (#1091) * Correct a translation error. * Update chapter_computer-vision/image-augmentation.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Update aws.md (#1121) * Update aws.md * Update chapter_appendix-tools-for-deep-learning/aws.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Update image-augmentation.md (#1093) * Update anchor.md (#1088) fix a minor issue in code * Update anchor.md * Update image-augmentation.md * fix typo and improve translation in chapter_linear-networks\softmax-regression.md (#1087) * Avoid `torch.meshgrid` user warning (#1174) Avoids the following user warning: ```python ~/anaconda3/envs/torch/lib/python3.10/site-packages/torch/functional.py:568: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at ../aten/src/ATen/native/TensorShape.cpp:2228.) return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined] ``` * bump to 2.0.0-beta1 * Update sequence.md * bump beta1 on readme * Add latex code block background to config * BLD: Bump python support version 3.9 (#1183) * BLD: Bump python support version 3.9 * Remove clear and manually downgrade protobuf 4.21.4 to 3.19.4 * BLD: Bump torch and tensorflow * Update Jenkinsfile * Update chapter_installation/index.md * Update chapter_installation/index.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Update config.ini * Update INFO.md * Update INFO.md * Drop mint to show code in pdf, use Inconsolata font, apply code cell color (#1187) * resolve the conflicts * revise from publisher (#1089) * revise from publisher * d2l api * post_latex * revise from publisher * revise ch11 * Delete d2l-Copy1.bib * clear cache * rm d2lbook clear * debug anchor * keep original d2l doc Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal> Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> Co-authored-by: Aston Zhang <asv325@gmail.com> * 重复语句 (#1188) Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Improve expression for chapter_preliminaries/pandas.md (#1184) * Update pandas.md * Improve expression * Improve expression * Update chapter_preliminaries/pandas.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Improce expression for chapter_preliminaries/linear-algebra.md (#1185) * Improce expression * Improve code comments * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md * Update chapter_preliminaries/linear-algebra.md Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> * Fix multibox_detection bugs * Update d2l to 0.17.5 version * restore older version * Upgrade pandas * change to python3.8 * Test warning log * relocate warning log * test logs filtering * Update gru.md * Add DeprecationWarning filter * Test warning log * Update attention mechanisms & computational performance * Update multilayer perceptron& linear & convolution networks & computer vision * Update recurrent&optimition&nlp pretraining & nlp applications * ignore warnings * Update index.md * Update linear networks * Update multilayer perceptrons&deep learning computation * Update preliminaries * Check and Add warning filter * Update kaggle-cifar10.md * Update object-detection-dataset.md * Update ssd.md fcn.md * Update hybridize.md * Update hybridize.md Signed-off-by: sunhaizhou <haizhou.sun@smartmore.com> Co-authored-by: zhou201505013 <39976863+zhou201505013@users.noreply.github.com> Co-authored-by: Xinwei Liu <xinzone@outlook.com> Co-authored-by: Anirudh Dagar <anirudhdagar6@gmail.com> Co-authored-by: Aston Zhang <22279212+astonzhang@users.noreply.github.com> Co-authored-by: hugo_han <57249629+HugoHann@users.noreply.github.com> Co-authored-by: gyro永不抽风 <1247006353@qq.com> Co-authored-by: CanChengZheng <zcc550169544@163.com> Co-authored-by: linlin <jajupmochi@gmail.com> Co-authored-by: iuk <liukun0104@gmail.com> Co-authored-by: yoos <49556860+liyunlongaaa@users.noreply.github.com> Co-authored-by: Mr. Justice Lawrence John Wargrave <65226618+RUCWargrave@users.noreply.github.com> Co-authored-by: Chiyuan Fu <fuchiyuan2019@outlook.com> Co-authored-by: Sunhuashan <48636870+Sunhuashan@users.noreply.github.com> Co-authored-by: Haiker Sun <haizhou.uestc2011@gmail.com> Co-authored-by: Ming Liu <akira.liu@njnu.edu.cn> Co-authored-by: goldmermaid <goldpiggy@berkeley.edu> Co-authored-by: silenceZheng66 <13754430639@163.com> Co-authored-by: Wenchao Yan <56541797+YWonchall@users.noreply.github.com> Co-authored-by: Kiki2049 <55939997+Kiki2049@users.noreply.github.com> Co-authored-by: Krahets <krahets@163.com> Co-authored-by: friedmainfunction <73703265+friedmainfunction@users.noreply.github.com> Co-authored-by: Jameson <miraclecome@gmail.com> Co-authored-by: P. Yao <12227516+YaoPengCN@users.noreply.github.com> Co-authored-by: Yulv-git <34329208+Yulv-git@users.noreply.github.com> Co-authored-by: Liu,Xiao <45966993+liuxiao916@users.noreply.github.com> Co-authored-by: YIN, Gang <1246410+yingang@users.noreply.github.com> Co-authored-by: Joe-HZ <58297431+Joe-HZ@users.noreply.github.com> Co-authored-by: lybloveyou <102609904+lybloveyou@users.noreply.github.com> Co-authored-by: VigourJiang <jiangfuqiang154@163.com> Co-authored-by: zxhd863943427 <74853597+zxhd863943427@users.noreply.github.com> Co-authored-by: LYF <27893441+liyufan@users.noreply.github.com> Co-authored-by: Aston Zhang <asv325@gmail.com> Co-authored-by: xiaotinghe <xiaotih@amazon.com> Co-authored-by: Ubuntu <ubuntu@ip-172-31-12-66.us-west-2.compute.internal> Co-authored-by: Holly-Max <60691735+Holly-Max@users.noreply.github.com> Co-authored-by: HinGwenWoong <peterhuang0323@qq.com> Co-authored-by: Shuai Zhang <cheungdaven@gmail.com>

async def test_device_diagnostics_error(hass, integration): dev_reg = async_get(hass) device = dev_reg.async_get_or_create( config_entry_id=integration.entry_id, identifiers={("test", "test")} ) with pytest.raises(ValueError): await async_get_device_diagnostics(hass, integration, device)

tests/components/zwave_js/test_diagnostics.py

core

Python

11d0dcf7ac4ddc2638f403ef0ee6b796ac5bbceb

test_diagnostics.py

test_device_diagnostics_error

https://github.com/home-assistant/core.git

Add zwave_js device diagnostics (#64504) * Add zwave_js device diagnostics * Add diagnostics as a dependency in manifest * Add failure scenario test * fix device diagnostics helper and remove dependency * tweak

def set_runtime_library_dirs(self, dirs): self.runtime_library_dirs = dirs[:]

python3.10.4/Lib/distutils/ccompiler.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

ccompiler.py

set_runtime_library_dirs

https://github.com/XX-net/XX-Net.git

add python 3.10.4 for windows

def exec(self): raise NotImplementedError

ppg2mel/train/solver.py

MockingBird

Python

b617a87ee40ab384767a27335313c2c65ee094ec

solver.py

exec

https://github.com/babysor/MockingBird.git

Init ppg extractor and ppg2mel (#375) * Init ppg extractor and ppg2mel * add preprocess and training * FIx known issues * Update __init__.py Allow to gen audio * Fix length issue * Fix bug of preparing fid * Fix sample issues * Add UI usage of PPG-vc

def _gen_md5_for_arraylike_obj(md5_gen, data): import numpy as np len_bytes = _hash_uint64_ndarray_as_bytes(np.array([len(data)], dtype="uint64")) md5_gen.update(len_bytes) if len(data) < EvaluationDataset.NUM_SAMPLE_ROWS_FOR_HASH * 2: md5_gen.update(_hash_array_like_obj_as_bytes(data)) else: head_rows = data[: EvaluationDataset.NUM_SAMPLE_ROWS_FOR_HASH] tail_rows = data[-EvaluationDataset.NUM_SAMPLE_ROWS_FOR_HASH :] md5_gen.update(_hash_array_like_obj_as_bytes(head_rows)) md5_gen.update(_hash_array_like_obj_as_bytes(tail_rows))

mlflow/models/evaluation/base.py

mlflow

Python

964f5ab75098c55f028f8acfeeae05df35ea68d5

base.py

_gen_md5_for_arraylike_obj

https://github.com/mlflow/mlflow.git

Evaluation Default evaluator (#5092) * init Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * rename module Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * revert black change Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * change module path Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * refactor Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * lazy load pyspark Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * revert export Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix curcit import Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix conftest.py Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * Revert "fix conftest.py" This reverts commit 2ea29c62bfffc5461bf77f3da15b5c00f51de19b. * fix tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * default evaluator Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update import Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update hash algo Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update import Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comment Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix lint Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add more tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix lint Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update shap explainer Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * remove scikitplot dep Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add pr curve Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add shap.summary_plot Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * log explainer Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * improve explainer code Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update shap init Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update explainer creating Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update predict_proba Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * refactor Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add multi-class metrics artifacts Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add log_loss metric Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * lazy load pyspark Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * address ben comments Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * prevent show shap logo, add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * support spark model Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add shap version check Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update docs, loose classifier label limit Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * multiclass classifier merge metrics/plots Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * zfill feature name Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add config max_num_classes_threshold_logging_roc_pr_curve_for_multiclass_classifier Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * refactor Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * improve label handling Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * refactor Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * add tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * black Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * increase plot dpi Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix test fixture Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix pylint Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update doc Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * use matplot rc_context Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix shap import Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * refactor EvaluationDataset Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * limit user specify shap algos Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * clean Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * update evaluation dataset Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * use svg fig Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * revert svg Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * curve dashline, legend display ap/roc, legend move out Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * linewidth 1 Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * keyword arguments for evaluate, fix tests Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * mark abc.abstractmethod, kw args for ModelEvaluator methods Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix pylint Signed-off-by: Weichen Xu <weichen.xu@databricks.com> * fix pylint Signed-off-by: Weichen Xu <weichen.xu@databricks.com>

def fit(self, X, y, sample_weight=None): allowed_strategies = ("mean", "median", "quantile", "constant") if self.strategy not in allowed_strategies: raise ValueError( "Unknown strategy type: %s, expected one of %s." % (self.strategy, allowed_strategies) ) y = check_array(y, ensure_2d=False, input_name="y") if len(y) == 0: raise ValueError("y must not be empty.") if y.ndim == 1: y = np.reshape(y, (-1, 1)) self.n_outputs_ = y.shape[1] check_consistent_length(X, y, sample_weight) if sample_weight is not None: sample_weight = _check_sample_weight(sample_weight, X) if self.strategy == "mean": self.constant_ = np.average(y, axis=0, weights=sample_weight) elif self.strategy == "median": if sample_weight is None: self.constant_ = np.median(y, axis=0) else: self.constant_ = [ _weighted_percentile(y[:, k], sample_weight, percentile=50.0) for k in range(self.n_outputs_) ] elif self.strategy == "quantile": if self.quantile is None or not np.isscalar(self.quantile): raise ValueError( "Quantile must be a scalar in the range [0.0, 1.0], but got %s." % self.quantile ) percentile = self.quantile * 100.0 if sample_weight is None: self.constant_ = np.percentile(y, axis=0, q=percentile) else: self.constant_ = [ _weighted_percentile(y[:, k], sample_weight, percentile=percentile) for k in range(self.n_outputs_) ] elif self.strategy == "constant": if self.constant is None: raise TypeError( "Constant target value has to be specified " "when the constant strategy is used." ) self.constant_ = check_array( self.constant, accept_sparse=["csr", "csc", "coo"], ensure_2d=False, ensure_min_samples=0, ) if self.n_outputs_ != 1 and self.constant_.shape[0] != y.shape[1]: raise ValueError( "Constant target value should have shape (%d, 1)." % y.shape[1] ) self.constant_ = np.reshape(self.constant_, (1, -1)) return self

sklearn/dummy.py

scikit-learn

Python

b28c5bba66529217ceedd497201a684e5d35b73c

dummy.py

fit

https://github.com/scikit-learn/scikit-learn.git

FIX DummyRegressor overriding constant (#22486)

def _normalize_mode(im): if im.mode in RAWMODE: im.load() return im if Image.getmodebase(im.mode) == "RGB": im = im.convert("P", palette=Image.Palette.ADAPTIVE) if im.palette.mode == "RGBA": for rgba in im.palette.colors.keys(): if rgba[3] == 0: im.info["transparency"] = im.palette.colors[rgba] break return im return im.convert("L")

src/PIL/GifImagePlugin.py

Pillow

Python

76871795f787756ab1978772b53237948bec377a

GifImagePlugin.py

_normalize_mode

https://github.com/python-pillow/Pillow.git

Resolved UNDONE by removing code

def iter_tree_files(root, on_error=None, follow_links=None): if on_error is not None and not callable(on_error): raise TypeError("on_error:{!r} is not callable.".format(on_error)) if follow_links is None: follow_links = True for entry in _iter_tree_entries_next( os.path.abspath(root), "", {}, on_error, follow_links ): if not entry.is_dir(follow_links): yield entry.path # Alias `iter_tree_files()` as `iter_tree()`. iter_tree = iter_tree_files

python/ray/_private/thirdparty/pathspec/util.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

util.py

iter_tree_files

https://github.com/ray-project/ray.git

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

def insidetextorientation(self): return self["insidetextorientation"]

packages/python/plotly/plotly/graph_objs/_pie.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_pie.py

insidetextorientation

https://github.com/plotly/plotly.py.git

switch to black .22

def forgeHeaders(items=None, base=None): items = items or {} for _ in list(items.keys()): if items[_] is None: del items[_] headers = OrderedDict(conf.httpHeaders if base is None else base) headers.update(items.items())

lib/request/basic.py

sqlmap

Python

216565fb05166d4bcf80b35a4f8f381e9f6b3d08

basic.py

forgeHeaders

https://github.com/sqlmapproject/sqlmap.git

Fixes #5275

def update(self, value=None, values=None, disabled=None, visible=None, size=(None, None)): if not self._widget_was_created(): # if widget hasn't been created yet, then don't allow return if values is not None: self.Values = values self.TKOptionMenu['menu'].delete(0, 'end') # Insert list of new options (tk._setit hooks them up to var) # self.TKStringVar.set(self.Values[0]) for new_value in self.Values: self.TKOptionMenu['menu'].add_command(label=new_value, command=tk._setit(self.TKStringVar, new_value)) if value is None: self.TKStringVar.set('') if size == (None, None): max_line_len = max([len(str(l)) for l in self.Values]) if len(self.Values) else 0 if self.AutoSizeText is False: width = self.Size[0] else: width = max_line_len + 1 self.TKOptionMenu.configure(width=width) else: self.TKOptionMenu.configure(width=size[0]) if value is not None: self.DefaultValue = value self.TKStringVar.set(value) if disabled == True: self.TKOptionMenu['state'] = 'disabled' elif disabled == False: self.TKOptionMenu['state'] = 'normal' if visible is False: self._pack_forget_save_settings() # self.TKOptionMenu.pack_forget() elif visible is True: self._pack_restore_settings() # self.TKOptionMenu.pack(padx=self.pad_used[0], pady=self.pad_used[1]) if visible is not None: self._visible = visible Update = update # ------------------------- OPTION MENU Element lazy functions ------------------------- # InputOptionMenu = OptionMenu # ---------------------------------------------------------------------- # # Listbox # # ---------------------------------------------------------------------- #

PySimpleGUI.py

PySimpleGUI

Python

ed2bc288ff17344f6406c49623036620f18e65bb

PySimpleGUI.py

update

https://github.com/PySimpleGUI/PySimpleGUI.git

Completed switching all elements over to the new way of handling visiblity

def hermite_prob_poly(n, x=None, polys=False): r return named_poly(n, dup_hermite_prob, ZZ, "probabilist's Hermite polynomial", (x,), polys)

sympy/polys/orthopolys.py

sympy

Python

5c9a4787c032d39abb80aae106030b177263a7cc

orthopolys.py

hermite_prob_poly

https://github.com/sympy/sympy.git

Probabilist's Hermite polynomials The plain or physicist's Hermite polynomials have leading coefficient 2^n, which leads to orthogonality with respect to the simplest possible form of the weight function exp(-x^2) and is the specific normalisation appearing in the solution to the Schrödinger equation for the quantum harmonic oscillator, but leads to unnecessary complications everywhere else. Removing the twos in the 3-term recurrence relation leads to the monic probabilist's version; its weight function of exp(-x^2/2) becomes the standard normal distribution after normalising. This version also forms the sign-alternated matching polynomial for the complete graph, a highly interesting connection to combinatorics.

def dijkstra_predecessor_and_distance(G, source, cutoff=None, weight="weight"): if source not in G: raise nx.NodeNotFound(f"Node {source} is not found in the graph") weight = _weight_function(G, weight) pred = {source: []} # dictionary of predecessors return (pred, _dijkstra(G, source, weight, pred=pred, cutoff=cutoff))

networkx/algorithms/shortest_paths/weighted.py

networkx

Python

b7d65ffc7183e9a01cdc07b79f8f06403cc4dda4

weighted.py

dijkstra_predecessor_and_distance

https://github.com/networkx/networkx.git

DOC: remove note re: non-existant param (#5648)

def _chunk_positional_ranges(self) -> tuple[tuple[int, int], ...]: ranges = [] stop = 0 for c in self._data.iterchunks(): start, stop = stop, stop + len(c) ranges.append((start, stop)) return tuple(ranges)

pandas/core/arrays/_mixins.py

pandas

Python

2d6a2c3e981208bf67bdd36cca726e8a399e487c

_mixins.py

_chunk_positional_ranges

https://github.com/pandas-dev/pandas.git

REF: move ArrowStringArray.__setitem__ and related methods to ArrowExtensionArray (#46439)

def _mesh(self): y, extendlen = self._proportional_y() # Use the vmin and vmax of the colorbar, which may not be the same # as the norm. There are situations where the colormap has a # narrower range than the colorbar and we want to accommodate the # extra contours. if (isinstance(self.norm, (colors.BoundaryNorm, colors.NoNorm)) or self.boundaries is not None): # not using a norm. y = y * (self.vmax - self.vmin) + self.vmin else: # Update the norm values in a context manager as it is only # a temporary change and we don't want to propagate any signals # attached to the norm (callbacks.blocked). with self.norm.callbacks.blocked(), \ cbook._setattr_cm(self.norm, vmin=self.vmin, vmax=self.vmax): y = self.norm.inverse(y) self._y = y X, Y = np.meshgrid([0., 1.], y) if self.orientation == 'vertical': return (X, Y, extendlen) else: return (Y, X, extendlen)

lib/matplotlib/colorbar.py

matplotlib

Python

fdb4ad372ab66177d99e478385c807e5843d6a0f

colorbar.py

_mesh

https://github.com/matplotlib/matplotlib.git

MNT: Use a context manager to change the norm in colorbar code This removes a deepcopy of the norm in Colorbar, instead updating the vmin/vmax via the context manager and ignoring any callback updates in the process.

def try_to_replace(self, provider, other, problems): rlist = self.reqts[other] unmatched = set() for s in rlist: matcher = self.get_matcher(s) if not matcher.match(provider.version): unmatched.add(s) if unmatched: # can't replace other with provider problems.add(('cantreplace', provider, other, frozenset(unmatched))) result = False else: # can replace other with provider self.remove_distribution(other) del self.reqts[other] for s in rlist: self.reqts.setdefault(provider, set()).add(s) self.add_distribution(provider) result = True return result

.venv/lib/python3.8/site-packages/pip/_vendor/distlib/locators.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

locators.py

try_to_replace

https://github.com/jindongwang/transferlearning.git

upd; format

def set_choices(self, choices, choices_names=None, none_choice_name=None): self.unselect() # Validate choices if choices is None: raise ValueError('Choices cannot be None.') if not isinstance(choices, Iterable): raise ValueError('Choices must be Iterable') if choices_names is None: choices_names = tuple(str(c) for c in choices) elif isinstance(choices_names, (list,tuple)): if len(choices_names) != len(choices): raise ValueError('mismatch len of choices and choices names') elif isinstance(choices_names, dict): choices_names = [ choices_names[x] for x in choices ] else: raise ValueError('unsupported type of choices_names') if not all( isinstance(x, str) for x in choices_names ): raise ValueError('all values in choices_names must be a str') choices = tuple(choices) self._set_choices(choices, choices_names, none_choice_name) self._send_choices()

xlib/mp/csw/DynamicSingleSwitch.py

DeepFaceLive

Python

ae8a1e0ff4b13e6e6a0155e346864805b2ca81dd

DynamicSingleSwitch.py

set_choices

https://github.com/iperov/DeepFaceLive.git

added Face Animator module

def get_batches_by_oldest(item_code, warehouse): batches = get_batch_qty(item_code=item_code, warehouse=warehouse) batches_dates = [ [batch, frappe.get_value("Batch", batch.batch_no, "expiry_date")] for batch in batches ] batches_dates.sort(key=lambda tup: tup[1]) return batches_dates @frappe.whitelist()

erpnext/stock/doctype/batch/batch.py

@frappe.whitelist()

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

batch.py

get_batches_by_oldest

https://github.com/frappe/erpnext.git

style: format code with black

def recover_args(flattened_args): assert ( len(flattened_args) % 2 == 0 ), "Flattened arguments need to be even-numbered. See `flatten_args`." args = [] kwargs = {} for name_index in range(0, len(flattened_args), 2): name, arg = flattened_args[name_index], flattened_args[name_index + 1] if name == DUMMY_TYPE: args.append(arg) else: kwargs[name] = arg return args, kwargs

python/ray/_private/signature.py

ray

Python

7f1bacc7dc9caf6d0ec042e39499bbf1d9a7d065

signature.py

recover_args

https://github.com/ray-project/ray.git

[CI] Format Python code with Black (#21975) See #21316 and #21311 for the motivation behind these changes.

def captured_output(stream_name): # type: (str) -> Iterator[StreamWrapper] orig_stdout = getattr(sys, stream_name) setattr(sys, stream_name, StreamWrapper.from_stream(orig_stdout)) try: yield getattr(sys, stream_name) finally: setattr(sys, stream_name, orig_stdout)

.venv/lib/python3.8/site-packages/pip/_internal/utils/misc.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

misc.py

captured_output

https://github.com/jindongwang/transferlearning.git

upd; format

def _recreate_cm(self): return self

python3.10.4/Lib/contextlib.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

contextlib.py

_recreate_cm

https://github.com/XX-net/XX-Net.git

add python 3.10.4 for windows

def _fill_disk_filename(conn, vm_name, disk, hypervisor, pool_caps): # Compute the filename without extension since it may not make sense for some pool types disk["filename"] = "{}_{}".format(vm_name, disk["name"]) # Compute the source file path base_dir = disk.get("pool", None) if hypervisor in ["qemu", "kvm", "xen"]: # Compute the base directory from the pool property. We may have either a path # or a libvirt pool name there. if not base_dir: base_dir = _get_images_dir() # If the pool is a known libvirt one, skip the filename since a libvirt volume will be created later if base_dir not in conn.listStoragePools(): # For path-based disks, keep the qcow2 default format if not disk.get("format"): disk["format"] = "qcow2" disk["filename"] = "{}.{}".format(disk["filename"], disk["format"]) disk["source_file"] = os.path.join(base_dir, disk["filename"]) else: if "pool" not in disk: disk["pool"] = base_dir pool_obj = conn.storagePoolLookupByName(base_dir) pool_xml = ElementTree.fromstring(pool_obj.XMLDesc()) pool_type = pool_xml.get("type") # Disk pools volume names are partition names, they need to be named based on the device name if pool_type == "disk": device = pool_xml.find("./source/device").get("path") all_volumes = pool_obj.listVolumes() if disk.get("source_file") not in all_volumes: indexes = [ int(re.sub("[a-z]+", "", vol_name)) for vol_name in all_volumes ] or [0] index = min( idx for idx in range(1, max(indexes) + 2) if idx not in indexes ) disk["filename"] = "{}{}".format(os.path.basename(device), index) # Is the user wanting to reuse an existing volume? if disk.get("source_file"): if not disk.get("source_file") in pool_obj.listVolumes(): raise SaltInvocationError( "{} volume doesn't exist in pool {}".format( disk.get("source_file"), base_dir ) ) disk["filename"] = disk["source_file"] del disk["source_file"] # Get the default format from the pool capabilities if not disk.get("format"): volume_options = ( [ type_caps.get("options", {}).get("volume", {}) for type_caps in pool_caps.get("pool_types") if type_caps["name"] == pool_type ] or [{}] )[0] # Still prefer qcow2 if possible if "qcow2" in volume_options.get("targetFormatType", []): disk["format"] = "qcow2" else: disk["format"] = volume_options.get("default_format", None) elif hypervisor == "bhyve" and vm_name: disk["filename"] = "{}.{}".format(vm_name, disk["name"]) disk["source_file"] = os.path.join( "/dev/zvol", base_dir or "", disk["filename"] ) elif hypervisor in ["esxi", "vmware"]: if not base_dir: base_dir = __salt__["config.get"]("virt:storagepool", "[0] ") disk["filename"] = "{}.{}".format(disk["filename"], disk["format"]) disk["source_file"] = "{}{}".format(base_dir, disk["filename"])

salt/modules/virt.py

salt

Python

f2a783643de61cac1ff3288b40241e5ce6e1ddc8

virt.py

_fill_disk_filename

https://github.com/saltstack/salt.git

Update to latest ``pyupgrade`` hook. Stop skipping it on CI. Signed-off-by: Pedro Algarvio <palgarvio@vmware.com>

def test_auto_create_auto_join_remote_room(self) -> None: # Register a first user; this should call _create_and_join_rooms self.get_success(self.handler.register_user(localpart="jeff")) _, kwargs = self.room_member_handler.update_membership.call_args self.assertEqual(kwargs["room_id"], self.room_id) self.assertEqual(kwargs["action"], "join") self.assertEqual(kwargs["remote_room_hosts"], ["remotetest"]) # Register a second user; this should call _join_rooms self.get_success(self.handler.register_user(localpart="jeff2")) _, kwargs = self.room_member_handler.update_membership.call_args self.assertEqual(kwargs["room_id"], self.room_id) self.assertEqual(kwargs["action"], "join") self.assertEqual(kwargs["remote_room_hosts"], ["remotetest"])

tests/handlers/test_register.py

synapse

Python

652d1669c5a103b1c20478770c4aaf18849c09a3

test_register.py

test_auto_create_auto_join_remote_room

https://github.com/matrix-org/synapse.git

Add missing type hints to tests.handlers. (#14680) And do not allow untyped defs in tests.handlers.

def logsumexp(x, axis=None, keepdims=False): return tf.reduce_logsumexp(x, axis, keepdims) @keras_export("keras.backend.round") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

keras/backend.py

@keras_export("keras.backend.round") @tf.__internal__.dispatch.add_dispatch_support @doc_controls.do_not_generate_docs

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

backend.py

logsumexp

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def test_patch_bot_owner_of_bot_with_can_create_users(self) -> None: cordelia = self.example_user("cordelia") self.login("hamlet") self.create_bot() bot_realm = get_realm("zulip") bot_email = "hambot-bot@zulip.testserver" bot_user = get_user(bot_email, bot_realm) do_change_can_create_users(bot_user, True) self.logout() # iago is an ordinary organization administrator, and thus doesn't have # sufficient permissions to change ownership of this bot. self.login("iago") bot_info = { "bot_owner_id": cordelia.id, } result = self.client_patch(f"/json/bots/{bot_user.id}", bot_info) self.assert_json_error( result, "Must be an organization owner", ) self.logout() # desdemona is the organization owner and should be allowed to change the bot's ownership. self.login("desdemona") result = self.client_patch(f"/json/bots/{bot_user.id}", bot_info) self.assert_json_success(result) bot_user.refresh_from_db() self.assertEqual(bot_user.bot_owner, cordelia)

zerver/tests/test_bots.py

zulip

Python

af5d0d6f5e5444332f9f8e565d97f4acdceaa72f

test_bots.py

test_patch_bot_owner_of_bot_with_can_create_users

https://github.com/zulip/zulip.git

bots: Don't allow admins to change owner of bot with can_create_users. Ordinary organization administrators shouldn't be allowed to change ownership of a bot with the can_create_users permission. This is a special permission that is granted manually by server administrators to an organization (to a UserProfile of the org owners' choice) after approval by a server administator. The code comments provide more detail about why this is sensitive.

def percentile_fn(data, percentile): return data[int((len(data) - 1) * percentile)] if len(data) > 0 else None

src/sentry/api/endpoints/project_dynamic_sampling.py

sentry

Python

923658b395545abc1b7f7a39cf64d198c9feea74

project_dynamic_sampling.py

percentile_fn

https://github.com/getsentry/sentry.git

feat(dynamic-sampling): Adds endpoint that returns onboarding flow trace info [TET-176] (#36113) This PR adds an endpoint for the dynamic sampling onboarding flow that: - Does a query to the transactions table to fetch a random sampleSize over the last passed statsPeriod date range. - If distrubutedTracing mode is enabled, then it runs a subsequent query to fetch the project breakdown in the traces from the first query - Calculates distribution function values like p50, p90, p95, p99, avg, max, min on the client side sample rates returned from the first query - Returns the percentage of transactions that did not have a sample rate

def equals(self, other): if not isinstance(other, PermutationGroup): return False set_self_gens = set(self.generators) set_other_gens = set(other.generators) # before reaching the general case there are also certain # optimisation and obvious cases requiring less or no actual # computation. if set_self_gens == set_other_gens: return True # in the most general case it will check that each generator of # one group belongs to the other PermutationGroup and vice-versa for gen1 in set_self_gens: if not other.contains(gen1): return False for gen2 in set_other_gens: if not self.contains(gen2): return False return True

sympy/combinatorics/perm_groups.py

sympy

Python

3e167a67bde4b4817666de48bf98d247bed86e2d

perm_groups.py

equals

https://github.com/sympy/sympy.git

Update sympy/combinatorics/perm_groups.py

def set_vars(): return {}

lib/gui/display_page.py

faceswap

Python

c1512fd41d86ef47a5d1ce618d6d755ef7cbacdf

display_page.py

set_vars

https://github.com/deepfakes/faceswap.git

Update code to support Tensorflow versions up to 2.8 (#1213) * Update maximum tf version in setup + requirements * - bump max version of tf version in launcher - standardise tf version check * update keras get_custom_objects for tf>2.6 * bugfix: force black text in GUI file dialogs (linux) * dssim loss - Move to stock tf.ssim function * Update optimizer imports for compatibility * fix logging for tf2.8 * Fix GUI graphing for TF2.8 * update tests * bump requirements.txt versions * Remove limit on nvidia-ml-py * Graphing bugfixes - Prevent live graph from displaying if data not yet available * bugfix: Live graph. Collect loss labels correctly * fix: live graph - swallow inconsistent loss errors * Bugfix: Prevent live graph from clearing during training * Fix graphing for AMD

async def get_tasks(self) -> dict: replies = await asyncio.gather( *[ self._client.get_task_info(node_id, timeout=DEFAULT_RPC_TIMEOUT) for node_id in self._client.get_all_registered_raylet_ids() ] ) result = defaultdict(dict) for reply in replies: tasks = reply.task_info_entries for task in tasks: data = self._message_to_dict( message=task, fields_to_decode=["task_id"], ) data = filter_fields(data, TaskState) result[data["task_id"]] = data return result

dashboard/state_aggregator.py

ray

Python

30ab5458a7e4ba2351d5e1beef8c8797b5946493

state_aggregator.py

get_tasks

https://github.com/ray-project/ray.git

[State Observability] Tasks and Objects API (#23912) This PR implements ray list tasks and ray list objects APIs. NOTE: You can ignore the merge conflict for now. It is because the first PR was reverted. There's a fix PR open now.

def measure(self): return self["measure"]

packages/python/plotly/plotly/graph_objs/_waterfall.py

plotly.py

Python

43e3a4011080911901176aab919c0ecf5046ddd3

_waterfall.py

measure

https://github.com/plotly/plotly.py.git

switch to black .22

def disabled_train(self, mode=True): return self

ldm/models/diffusion/ddpm.py

stablediffusion

Python

ca86da3a30c4e080d4db8c25fca73de843663cb4

ddpm.py

disabled_train

https://github.com/Stability-AI/stablediffusion.git

release more models

def test_no_auth(self) -> None: channel = self.make_request("GET", self.url, b"{}") self.assertEqual( 401, channel.code, msg=channel.json_body, ) self.assertEqual(Codes.MISSING_TOKEN, channel.json_body["errcode"])

tests/rest/admin/test_device.py

synapse

Python

1595052b2681fb86c1c1b9a6028c1bc0d38a2e4b

test_device.py

test_no_auth

https://github.com/matrix-org/synapse.git

Use literals in place of `HTTPStatus` constants in tests (#13479) Replace - `HTTPStatus.NOT_FOUND` - `HTTPStatus.FORBIDDEN` - `HTTPStatus.UNAUTHORIZED` - `HTTPStatus.CONFLICT` - `HTTPStatus.CREATED` Signed-off-by: Dirk Klimpel <dirk@klimpel.org>

def test_image_crafter_index(encoder_doc_array, tmpdir): create_test_img(path=str(tmpdir), file_name='1.jpg') with Flow().add(uses=ImageCrafter) as f: res = f.index(inputs=encoder_doc_array) assert len(res) == 1 doc = res[0] assert doc.mime_type == 'image/jpeg' assert doc.tensor is not None

tests/unit/helloworld/multimodal/test_executors.py

jina

Python

217a11bb8dc613ed1136b8b541a68e6d53ca4fc1

test_executors.py

test_image_crafter_index

https://github.com/jina-ai/jina.git

test: fix tests failing after new docarray patch (#4449) * test: fix tests failing after new docarray patch * test: fix failing tests

def orthographic_projection(X, camera): camera = camera.reshape((-1, 1, 3)) X_trans = X[:, :, :2] + camera[:, :, 1:] shape = paddle.shape(X_trans) X_2d = (camera[:, :, 0] * X_trans.reshape((shape[0], -1))).reshape(shape) return X_2d @register

ppdet/modeling/architectures/pose3d_metro.py

@register

PaddleDetection

Python

d4e34fe165c09db65fd00113708be1b711ac957c

pose3d_metro.py

orthographic_projection

https://github.com/PaddlePaddle/PaddleDetection.git

pose3d metro modeling (#6612) * pose3d metro modeling * delete extra comments

def to_euler(self, seq): extrinsic = _check_sequence(seq) i, j, k = seq.lower() i = _elementary_axis_index(i) j = _elementary_axis_index(j) k = _elementary_axis_index(k) if not extrinsic: i, k = k, i # check if sequence is symmetric symmetric = i == k if symmetric: k = 6 - i - j # parity of the permutation sign = (i - j) * (j - k) * (k - i) // 2 # permutate elements elements = [self.a, self.b, self.c, self.d] a = elements[0] b = elements[i] c = elements[j] d = elements[k] * sign if not symmetric: a, b, c, d = a - c, b + d, c + a, d - b # calculate angles half_sum = atan2(b, a) half_diff = atan2(d, c) angle_2 = 2*atan2(sqrt(c*c + d*d), sqrt(a*a + b*b)) # alternatively, we can use this to avoid the square root: # angle_2 = acos(2*(a*a + b*b)/(a*a + b*b + c*c + d*d) - 1) angle_1 = half_sum + half_diff angle_3 = half_sum - half_diff if extrinsic: angle_1, angle_3 = angle_3, angle_1 # for Tait-Bryan angles if not symmetric: angle_2 -= pi / 2 if extrinsic: angle_3 *= sign else: angle_1 *= sign return Matrix([angle_1, angle_2, angle_3])

sympy/algebras/quaternion.py

sympy

Python

1d8576449e7ab757f13f49a1d33faed602aa88fb

quaternion.py

to_euler

https://github.com/sympy/sympy.git

implemented to_euler and from_euler

def test_jupyter_file_output(tmp_path): scene_name = "SimpleScene" current_renderer = config.renderer with tempconfig({"scene_names": [scene_name], "renderer": "opengl"}): file_name = _generate_file_name() actual_path = tmp_path.with_name(file_name) with actual_path.open("w") as outfile: outfile.write("") assert actual_path.exists() assert actual_path.is_file() # needs manually set back to avoid issues across tests config.renderer = current_renderer

tests/opengl/test_ipython_magic_opengl.py

manim

Python

206db54af53a87985c0d243d75304ea620dad520

test_ipython_magic_opengl.py

test_jupyter_file_output

https://github.com/ManimCommunity/manim.git

Migrate more `os.path` to `pathlib` in tests (#2991) * Migrate more `os.path` to `pathlib` in tests * Convert test fixtures to pathlib * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix mypy errors in tests * migrate another pathlib instance Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Benjamin Hackl <devel@benjamin-hackl.at>

async def test_statistic_during_period_hole(recorder_mock, hass, hass_ws_client): id = 1

tests/components/recorder/test_websocket_api.py

core

Python

9b8f94363c0b4ecd1434ac1ac3bb82febd3889d0

test_websocket_api.py

test_statistic_during_period_hole

https://github.com/home-assistant/core.git

Fix statistic_during_period for data with holes (#81847)

async def test_valve_set_state(hass, hk_driver, events): entity_id = "switch.valve_test" hass.states.async_set(entity_id, None) await hass.async_block_till_done() acc = Valve(hass, hk_driver, "Valve", entity_id, 2, {CONF_TYPE: TYPE_FAUCET}) await acc.run() await hass.async_block_till_done() assert acc.category == 29 # Faucet assert acc.char_valve_type.value == 3 # Water faucet acc = Valve(hass, hk_driver, "Valve", entity_id, 3, {CONF_TYPE: TYPE_SHOWER}) await acc.run() await hass.async_block_till_done() assert acc.category == 30 # Shower assert acc.char_valve_type.value == 2 # Shower head acc = Valve(hass, hk_driver, "Valve", entity_id, 4, {CONF_TYPE: TYPE_SPRINKLER}) await acc.run() await hass.async_block_till_done() assert acc.category == 28 # Sprinkler assert acc.char_valve_type.value == 1 # Irrigation acc = Valve(hass, hk_driver, "Valve", entity_id, 5, {CONF_TYPE: TYPE_VALVE}) await acc.run() await hass.async_block_till_done() assert acc.aid == 5 assert acc.category == 29 # Faucet assert acc.char_active.value == 0 assert acc.char_in_use.value == 0 assert acc.char_valve_type.value == 0 # Generic Valve hass.states.async_set(entity_id, STATE_ON) await hass.async_block_till_done() assert acc.char_active.value == 1 assert acc.char_in_use.value == 1 hass.states.async_set(entity_id, STATE_OFF) await hass.async_block_till_done() assert acc.char_active.value == 0 assert acc.char_in_use.value == 0 # Set from HomeKit call_turn_on = async_mock_service(hass, "switch", "turn_on") call_turn_off = async_mock_service(hass, "switch", "turn_off") acc.char_active.client_update_value(1) await hass.async_block_till_done() assert acc.char_in_use.value == 1 assert call_turn_on assert call_turn_on[0].data[ATTR_ENTITY_ID] == entity_id assert len(events) == 1 assert events[-1].data[ATTR_VALUE] is None acc.char_active.client_update_value(0) await hass.async_block_till_done() assert acc.char_in_use.value == 0 assert call_turn_off assert call_turn_off[0].data[ATTR_ENTITY_ID] == entity_id assert len(events) == 2 assert events[-1].data[ATTR_VALUE] is None

tests/components/homekit/test_type_switches.py

core

Python

3b33e0d832b238b40360383099391e2093ea05cb

test_type_switches.py

test_valve_set_state

https://github.com/home-assistant/core.git

Add support for restoring HomeKit IIDs (#79913)

def deal_bb(result_token): # find out <thead></thead> parts. thead_pattern = '<thead>(.*?)</thead>' if re.search(thead_pattern, result_token) is None: return result_token thead_part = re.search(thead_pattern, result_token).group() origin_thead_part = copy.deepcopy(thead_part) # check "rowspan" or "colspan" occur in <thead></thead> parts or not . span_pattern = "<td rowspan=\"(\d)+\" colspan=\"(\d)+\">|<td colspan=\"(\d)+\" rowspan=\"(\d)+\">|<td rowspan=\"(\d)+\">|<td colspan=\"(\d)+\">" span_iter = re.finditer(span_pattern, thead_part) span_list = [s.group() for s in span_iter] has_span_in_head = True if len(span_list) > 0 else False if not has_span_in_head: # <thead></thead> not include "rowspan" or "colspan" branch 1. # 1. replace <td> to <td><b>, and </td> to </b></td> # 2. it is possible to predict text include <b> or </b> by Text-line recognition, # so we replace <b><b> to <b>, and </b></b> to </b> thead_part = thead_part.replace('<td>', '<td><b>')\ .replace('</td>', '</b></td>')\ .replace('<b><b>', '<b>')\ .replace('</b></b>', '</b>') else: # <thead></thead> include "rowspan" or "colspan" branch 2. # Firstly, we deal rowspan or colspan cases. # 1. replace > to ><b> # 2. replace </td> to </b></td> # 3. it is possible to predict text include <b> or </b> by Text-line recognition, # so we replace <b><b> to <b>, and </b><b> to </b> # Secondly, deal ordinary cases like branch 1 # replace ">" to "<b>" replaced_span_list = [] for sp in span_list: replaced_span_list.append(sp.replace('>', '><b>')) for sp, rsp in zip(span_list, replaced_span_list): thead_part = thead_part.replace(sp, rsp) # replace "</td>" to "</b></td>" thead_part = thead_part.replace('</td>', '</b></td>') # remove duplicated <b> by re.sub mb_pattern = "(<b>)+" single_b_string = "<b>" thead_part = re.sub(mb_pattern, single_b_string, thead_part) mgb_pattern = "(</b>)+" single_gb_string = "</b>" thead_part = re.sub(mgb_pattern, single_gb_string, thead_part) # ordinary cases like branch 1 thead_part = thead_part.replace('<td>', '<td><b>').replace('<b><b>', '<b>') # convert <tb><b></b></tb> back to <tb></tb>, empty cell has no <b></b>. # but space cell(<tb> </tb>) is suitable for <td><b> </b></td> thead_part = thead_part.replace('<td><b></b></td>', '<td></td>') # deal with duplicated <b></b> thead_part = deal_duplicate_bb(thead_part) # deal with isolate span tokens, which causes by wrong predict by structure prediction. # eg.PMC5994107_011_00.png thead_part = deal_isolate_span(thead_part) # replace original result with new thead part. result_token = result_token.replace(origin_thead_part, thead_part) return result_token

ppstructure/table/table_master_match.py

PaddleOCR

Python

ddaa2c2552e19635cd6cdf38619f1f176c358f89

table_master_match.py

deal_bb

https://github.com/PaddlePaddle/PaddleOCR.git

add SLANet

def _convert_other(other, raiseit=False, allow_float=False): if isinstance(other, Decimal): return other if isinstance(other, int): return Decimal(other) if allow_float and isinstance(other, float): return Decimal.from_float(other) if raiseit: raise TypeError("Unable to convert %s to Decimal" % other) return NotImplemented

python3.10.4/Lib/_pydecimal.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

_pydecimal.py

_convert_other

https://github.com/XX-net/XX-Net.git

add python 3.10.4 for windows

def _process_hidden_imports(self): # For each hidden import required by the module being hooked... for import_module_name in self.hiddenimports: try: # Graph node for this module. Do not implicitly create namespace packages for non-existent packages. caller = self.module_graph.find_node(self.module_name, create_nspkg=False) # Manually import this hidden import from this module. self.module_graph.import_hook(import_module_name, caller) # If this hidden import is unimportable, print a non-fatal warning. Hidden imports often become # desynchronized from upstream packages and hence are only "soft" recommendations. except ImportError: if self.warn_on_missing_hiddenimports: logger.warning('Hidden import "%s" not found!', import_module_name) # FIXME: This is pretty... intense. Attempting to cleanly "undo" prior module graph operations is a recipe for # subtle edge cases and difficult-to-debug issues. It would be both safer and simpler to prevent these # imports from being added to the graph in the first place. To do so: # # * Remove the _process_excluded_imports() method below. # * Remove the PostGraphAPI.del_imports() method, which cannot reasonably be supported by the following solution, # appears to be currently broken, and (in any case) is not called anywhere in the PyInstaller codebase. # * Override the ModuleGraph._safe_import_hook() superclass method with a new PyiModuleGraph._safe_import_hook() # subclass method resembling: # # def _safe_import_hook( # self, target_module_name, source_module, fromlist, # level=DEFAULT_IMPORT_LEVEL, attr=None): # # if source_module.identifier in self._module_hook_cache: # for module_hook in self._module_hook_cache[ # source_module.identifier]: # if target_module_name in module_hook.excludedimports: # return [] # # return super()._safe_import_hook( # target_module_name, source_module, fromlist, # level=level, attr=attr)

PyInstaller/depend/imphook.py

pyinstaller

Python

35451d0df77dd4e2c3ad613ee35cb28d99a9421e

imphook.py

_process_hidden_imports

https://github.com/pyinstaller/pyinstaller.git

depend: allow hooks to opt out of missing hidden import warnings Implement new standard hook variable, called `warn_on_missing_hiddenimports`. This optional boolean flag allows a hook to opt out from warnings generated by missing hidden imports originating from that hook.

def check_install_build_global(options, check_options=None): # type: (Values, Optional[Values]) -> None if check_options is None: check_options = options

.venv/lib/python3.8/site-packages/pip/_internal/cli/cmdoptions.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

cmdoptions.py

check_install_build_global

https://github.com/jindongwang/transferlearning.git

upd; format

def user_documents_path() -> Path: return PlatformDirs().user_documents_path

pipenv/patched/notpip/_vendor/platformdirs/__init__.py

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

__init__.py

user_documents_path

https://github.com/pypa/pipenv.git

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

def _config_changeable_items(self) -> dict: return Config(self._config_section, configfile=self._configfile).changeable_items

plugins/train/model/_base/model.py

faceswap

Python

ff6b0209dd5ad57b81b0aca570df7f39a7119bfb

model.py

_config_changeable_items

https://github.com/deepfakes/faceswap.git

Refactoring and TravisCI to Github Actions (#1239) * refactor training * travis to actions

def _import_module(name): __import__(name) return sys.modules[name]

.venv/lib/python3.8/site-packages/pip/_vendor/six.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

six.py

_import_module

https://github.com/jindongwang/transferlearning.git

upd; format

def keras_model_summary(name, data, step=None): summary_metadata = tf.compat.v1.SummaryMetadata() # Hard coding a plugin name. Please refer to go/tb-plugin-name-hardcode for # the rationale. summary_metadata.plugin_data.plugin_name = "graph_keras_model" # version number = 1 summary_metadata.plugin_data.content = b"1" try: json_string = data.to_json() except Exception as exc: # pylint: disable=broad-except # An exception should not break a model code. logging.warning( "Model failed to serialize as JSON. Ignoring... %s", exc ) return False with tf.summary.experimental.summary_scope( name, "graph_keras_model", [data, step] ) as (tag, _): with tf.device("cpu:0"): tensor = tf.constant(json_string, dtype=tf.string) return tf.summary.write( tag=tag, tensor=tensor, step=step, metadata=summary_metadata ) @keras_export("keras.callbacks.TensorBoard", v1=[])

keras/callbacks.py

@keras_export("keras.callbacks.TensorBoard", v1=[])

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

callbacks.py

keras_model_summary

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def test_operator_extra_link_multiple_operators(dag_run, task_2, task_3, viewer_client): response = viewer_client.get( f"{ENDPOINT}?dag_id={task_2.dag_id}&task_id={task_2.task_id}" f"&execution_date={DEFAULT_DATE}&link_name=airflow", follow_redirects=True, ) assert response.status_code == 200 response_str = response.data if isinstance(response.data, bytes): response_str = response_str.decode() assert json.loads(response_str) == {'url': 'https://airflow.apache.org/1.10.5/', 'error': None} response = viewer_client.get( f"{ENDPOINT}?dag_id={task_3.dag_id}&task_id={task_3.task_id}" f"&execution_date={DEFAULT_DATE}&link_name=airflow", follow_redirects=True, ) assert response.status_code == 200 response_str = response.data if isinstance(response.data, bytes): response_str = response_str.decode() assert json.loads(response_str) == {'url': 'https://airflow.apache.org/1.10.5/', 'error': None} # Also check that the other Operator Link defined for this operator exists response = viewer_client.get( f"{ENDPOINT}?dag_id={task_3.dag_id}&task_id={task_3.task_id}" f"&execution_date={DEFAULT_DATE}&link_name=google", follow_redirects=True, ) assert response.status_code == 200 response_str = response.data if isinstance(response.data, bytes): response_str = response_str.decode() assert json.loads(response_str) == {'url': 'https://www.google.com', 'error': None}

tests/www/views/test_views_extra_links.py

airflow

Python

08575ddd8a72f96a3439f73e973ee9958188eb83

test_views_extra_links.py

test_operator_extra_link_multiple_operators

https://github.com/apache/airflow.git

Change BaseOperatorLink interface to take a ti_key, not a datetime (#21798)

def to_json(self) -> dict: return { "id": self.id, "query": self.query, "opCode": self.op_code.name, "authoritativeAnswer": self.authoritative_answer, "truncation": self.truncation, "recursionDesired": self.recursion_desired, "recursionAvailable": self.recursion_available, "responseCode": self.response_code.name, "responseCodeHttpEquiv": self.response_code.http_equiv_status_code, "questions": [{ "name": question.name, "type": question.type.name, "class": question.class_.name, } for question in self.questions], "answers": [rr.to_json() for rr in self.answers], "authorities": [rr.to_json() for rr in self.authorities], "additionals": [rr.to_json() for rr in self.additionals], "size": self.size, "timestamp": self.timestamp, }

mitmproxy/dns.py

mitmproxy

Python

f2f918a17e8d06c638b1bb5b06b3150a786d77a0

dns.py

to_json

https://github.com/mitmproxy/mitmproxy.git

[dns] build and improve web UI

def no_verify_ssl(self) -> bool: return self.namespace.no_verify_ssl

certbot/certbot/configuration.py

certbot

Python

ae7967c8aed28a8416a329e5eeac117c1672c878

configuration.py

no_verify_ssl

https://github.com/certbot/certbot.git

docs: how to override the trusted CA certificates (#9357) * docs: how to override the trusted CA certificates * Update certbot/docs/using.rst Co-authored-by: ohemorange <ebportnoy@gmail.com> Co-authored-by: ohemorange <ebportnoy@gmail.com>

def _dictionary(self): # type: () -> Dict[str, Any] # NOTE: Dictionaries are not populated if not loaded. So, conditionals # are not needed here. retval = {} for variant in OVERRIDE_ORDER: retval.update(self._config[variant]) return retval

.venv/lib/python3.8/site-packages/pip/_internal/configuration.py

transferlearning

Python

f638f5d0e6c8ebed0e69a6584bc7f003ec646580

configuration.py

_dictionary

https://github.com/jindongwang/transferlearning.git

upd; format

def test_api_set_storage_path_not_provided(self): response = self.client.post( "/api/documents/bulk_edit/", json.dumps( { "documents": [self.doc1.id], "method": "set_storage_path", "parameters": {}, }, ), content_type="application/json", ) self.assertEqual(response.status_code, 400) self.async_task.assert_not_called()

src/documents/tests/test_api.py

paperless-ngx

Python

53baed03895f28f24113d376b089e3ef281b34ed

test_api.py

test_api_set_storage_path_not_provided

https://github.com/paperless-ngx/paperless-ngx.git

Increases test coverage of storage paths

def encrypt_file(self, file, key=0): # precondition assert isinstance(file, str) and isinstance(key, int) try: with open(file, "r") as fin: with open("encrypt.out", "w+") as fout: # actual encrypt-process for line in fin: fout.write(self.encrypt_string(line, key)) except: return False return True

XORcipher/XOR_cipher.py

Python

Python

f0af0c43340763724f139fa68aa1e5a9ffe458b4

XOR_cipher.py

encrypt_file

https://github.com/geekcomputers/Python.git

refactor: clean code Signed-off-by: slowy07 <slowy.arfy@gmail.com>

def test_finished_signal(qtbot): signal_triggered = False

tests/unit/misc/test_msgbox.py

qutebrowser

Python

0877fb0d78635692e481c8bde224fac5ad0dd430

test_msgbox.py

test_finished_signal

https://github.com/qutebrowser/qutebrowser.git

Run scripts/dev/rewrite_enums.py

def _install_setup_packages(self) -> None: setup_packages = [(pkg.unsafe_name, pkg.specs) for pkg in parse_requirements(_INSTALLER_REQUIREMENTS)] for pkg in setup_packages: if pkg not in self._env.missing_packages: continue self._env.missing_packages.pop(self._env.missing_packages.index(pkg)) pkg_str = self._format_package(*pkg) if self._env.is_conda: cmd = ["conda", "install", "-y"] else: cmd = [sys.executable, "-m", "pip", "install", "--no-cache-dir"] if self._env.is_admin: cmd.append("--user") cmd.append(pkg_str) clean_pkg = pkg_str.replace("\"", "") if self._subproc_installer(cmd, clean_pkg) != 0: logger.error("Unable to install package: %s. Process aborted", clean_pkg) sys.exit(1)

setup.py

faceswap

Python

03f6cb4e7e106bc227ad781a515338097fba26f9

setup.py

_install_setup_packages

https://github.com/deepfakes/faceswap.git

setup.py: implement logging

def attrs_dict(self): return OrderedDict( [ ("src", self.url), ("width", self.width), ("height", self.height), ("alt", self.alt), ] )

wagtail/images/models.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

models.py

attrs_dict

https://github.com/wagtail/wagtail.git

Reformat with black

def _call_ntimes(self, fun, times): gc.collect(generation=1) mem1 = self._get_mem() for x in range(times): ret = self.call(fun) del x, ret gc.collect(generation=1) mem2 = self._get_mem() self.assertEqual(gc.garbage, []) diff = mem2 - mem1 # can also be negative return diff

psutil/tests/__init__.py

psutil

Python

04e7aa604155736cce0abcc15c9b7b63d941b0e9

__init__.py

_call_ntimes

https://github.com/giampaolo/psutil.git

docs: fix simple typo, repeadetly -> repeatedly (#2123)

def get_filesystem_type(filepath): # We import it locally so that click autocomplete works import psutil root_type = "unknown" for part in psutil.disk_partitions(): if part.mountpoint == '/': root_type = part.fstype continue if filepath.startswith(part.mountpoint): return part.fstype return root_type

dev/breeze/src/airflow_breeze/utils/run_utils.py

airflow

Python

4ffd4f09532fceb67675fce4c1f5cd383eff992e

run_utils.py

get_filesystem_type

https://github.com/apache/airflow.git

Prepare Breeze2 for prime time :) (#22713) This is a review and clean-up for all the parameters and commands for Breeze2 in order to prepare it for being used by the contribugors. There are various small fixes here and there, removal of duplicated code, refactoring and moving code around as well as cleanup and review all the parameters used for all implemented commands. The parameters, default values and their behaviours were updated to match "new" life of Breeze rather than old one. Some improvements are made to the autocomplete and click help messages printed. Full list of choices is always displayed, parameters are groups according to their target audience, and they were sorted according to importance and frequency of use. Various messages have been colourised according to their meaning - warnings as yellow, errors as red and informational messages as bright_blue. The `dry-run` option has been added to just show what would have been run without actually running some potentially "write" commands (read commands are still executed) so that you can easily verify and manually copy and execute the commands with option to modify them before. The `dry_run` and `verbose` options are now used for all commands. The "main" command now runs "shell" by default similarly as the original Breeze. All "shortcut" parameters have been standardized - i.e common options (verbose/dry run/help) have one and all common flags that are likely to be used often have an assigned shortcute. The "stop" and "cleanup" command have been added as they are necessary for average user to complete the regular usage cycle. Documentation for all the important methods have been updated.

def input_mask(self): inputs = self.input if isinstance(inputs, list): return [getattr(x, "_keras_mask", None) for x in inputs] else: return getattr(inputs, "_keras_mask", None)

keras/engine/base_layer.py

keras

Python

84afc5193d38057e2e2badf9c889ea87d80d8fbf

base_layer.py

input_mask

https://github.com/keras-team/keras.git

Reformatting the codebase with black. PiperOrigin-RevId: 450093126

def get_item_details(item_code): return frappe.db.sql( , item_code, as_dict=True, )[0]

erpnext/stock/doctype/serial_no/serial_no.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

serial_no.py

get_item_details

https://github.com/frappe/erpnext.git

style: format code with black

def collect_qtqml_files(self): # No-op if requested Qt-based package is not available. if self.version is None: return [], [] # Not all PyQt5/PySide2 installs have QML files. In this case, location['Qml2ImportsPath'] is empty. # Furthermore, even if location path is provided, the directory itself may not exist. # # https://github.com/pyinstaller/pyinstaller/pull/3229#issuecomment-359735031 # https://github.com/pyinstaller/pyinstaller/issues/3864 # # In Qt 6, Qml2ImportsPath was deprecated in favor of QmlImportsPath. The former is not available in PySide6 # 6.4.0 anymore (but is in PyQt6 6.4.0). Use the new QmlImportsPath if available. if 'QmlImportsPath' in self.location: qml_src_dir = self.location['QmlImportsPath'] else: qml_src_dir = self.location['Qml2ImportsPath'] if not qml_src_dir or not os.path.isdir(qml_src_dir): logger.warning('%s: QML directory %r does not exist. QML files not packaged.', self, qml_src_dir) return [], [] qml_dst_dir = os.path.join(self.qt_rel_dir, 'qml') datas = [(qml_src_dir, qml_dst_dir)] binaries = [ # Produce ``/path/to/Qt/Qml/path_to_qml_binary/qml_binary, PyQt5/Qt/Qml/path_to_qml_binary``. ( qml_plugin_file, os.path.join(qml_dst_dir, os.path.dirname(os.path.relpath(qml_plugin_file, qml_src_dir))) ) for qml_plugin_file in misc.dlls_in_subdirs(qml_src_dir) ] return binaries, datas

PyInstaller/utils/hooks/qt/__init__.py

pyinstaller

Python

d789a7daa7712716c89259b987349917a89aece7

__init__.py

collect_qtqml_files

https://github.com/pyinstaller/pyinstaller.git

hookutils: reorganize the Qt hook utilities Reorganize the Qt module information to provide information necessary to deal with variations between different python Qt bindings (PySide2, PyQt5, PySide6, and PyQt6). Replace the existing table-like dictionary with list of entries, which is easier to format and document. From this list, we now generate two dictionaries; one that maps Qt module (shared library) names to the module info entries (the same role as the old dictionary), and one that maps python module names to the module info entries. The latter is necessary to accommodate python modules that do not have corresponding Qt shared libraries (header-only Qt modules, such as QtAxContainer; or statically-linked module, such as QSci), but we still need to provide information about plugins or translation files. The new information list is based on manual inspection of source code for Qt 5.15 and 6.3, and should provide comprehensive information about all plugin names and translation file basenames. In addition, most of the helper functions, which take a reference to the `QtLibraryInfo` class as their first argument, have been turned into methods of the `QtLibraryInfo` class. The corresponding hooks have also been adjusted.

def pytest_collection_modifyitems(items): for item in items: if inspect.iscoroutinefunction(item.obj): item.add_marker("asyncio") assert not inspect.isasyncgenfunction(item.obj)

IPython/conftest.py

ipython

Python

82d1a374575d9785708f144976cf139c76c7acb7

conftest.py

pytest_collection_modifyitems

https://github.com/ipython/ipython.git

make sure to run async tests there are some `async def` tests, but they are skipped without `mark("asyncio")`

def filter(self, *args, **kwargs): self._not_support_combined_queries("filter") return self._filter_or_exclude(False, args, kwargs)

django/db/models/query.py

django

Python

9c19aff7c7561e3a82978a272ecdaad40dda5c00

query.py

filter

https://github.com/django/django.git

Refs #33476 -- Reformatted code with Black.

def _output_non_grouped(self) -> None: output_dir = self._args.output_dir os.makedirs(output_dir, exist_ok=True) description = f"{'Copying' if self._args.keep_original else 'Moving'} and renaming" for idx, source in enumerate(tqdm(self._sorter.sorted_filelist, desc=description, file=sys.stdout, leave=False)): dest = os.path.join(output_dir, f"{idx:06d}_{os.path.basename(source)}") self._sort_file(source, dest)

tools/sort/sort.py

faceswap

Python

98d01760e469fd2108eed8d0b0a1ba6297c3177c

sort.py

_output_non_grouped

https://github.com/deepfakes/faceswap.git

Overhaul sort: - Standardize image data reading and writing - Optimize loading (just one pass required) - Make all sort groups binnable (to greater or lesser results) - Add sort by pitch - Deprecate multiple options - linting, docs + locales

def insert(self, index, ins_string):

pipenv/patched/notpip/_vendor/pyparsing/results.py

""" Inserts new element at location index in the list of parsed tokens. Similar to ``list.insert()``. Example:: numlist = Word(nums)[...] print(numlist.parse_string("0 123 321"))

pipenv

Python

f3166e673fe8d40277b804d35d77dcdb760fc3b3

results.py

insert

https://github.com/pypa/pipenv.git

check point progress on only bringing in pip==22.0.4 (#4966) * vendor in pip==22.0.4 * updating vendor packaging version * update pipdeptree to fix pipenv graph with new version of pip. * Vendoring of pip-shims 0.7.0 * Vendoring of requirementslib 1.6.3 * Update pip index safety restrictions patch for pip==22.0.4 * Update patches * exclude pyptoject.toml from black to see if that helps. * Move this part of the hash collection back to the top (like prior implementation) because it affects the outcome of this test now in pip 22.0.4

def mark_scope_as_experimental(): with configure_scope() as scope: scope.set_tag(EXPERIMENT_TAG, True)

src/sentry/utils/sdk.py

sentry

Python

9288539aeeac52990705aa6dd0abaebe0d12da21

sdk.py

mark_scope_as_experimental

https://github.com/getsentry/sentry.git

poc(sdk): Add experimental dsn for upcoming perf work (#36000) This adds an experimental dsn to the MultiplexingTransport to intentionally send specific flagged events solely to a separate dsn, which will help us avoid troubles with ingesting random errors into our main Sentry project.

async def test_handle_mqtt_on_callback(hass, caplog, mqtt_mock, mqtt_client_mock): # Simulate an ACK for mid == 1, this will call mqtt_mock._mqtt_handle_mid(mid) mqtt_client_mock.on_publish(mqtt_client_mock, None, 1) await hass.async_block_till_done() # Make sure the ACK has been received await hass.async_block_till_done() # Now call publish without call back, this will call _wait_for_mid(msg_info.mid) await mqtt.async_publish(hass, "no_callback/test-topic", "test-payload") # Since the mid event was already set, we should not see any timeout await hass.async_block_till_done() assert ( "Transmitting message on no_callback/test-topic: 'test-payload', mid: 1" in caplog.text ) assert "No ACK from MQTT server" not in caplog.text

tests/components/mqtt/test_init.py

core

Python

845bf80e725af8c921915906b0f796c7a8164d11

test_init.py

test_handle_mqtt_on_callback

https://github.com/home-assistant/core.git

Mqtt improve test coverage (#66279) Co-authored-by: Martin Hjelmare <marhje52@gmail.com>

def enhanced_hue_supported(self) -> bool: return ( self.color_capabilities is not None and lighting.Color.ColorCapabilities.Enhanced_hue in self.color_capabilities )

homeassistant/components/zha/core/channels/lighting.py

core

Python

df67a8cd4f8df91a153778009a74be1e3876ca53

lighting.py

enhanced_hue_supported

https://github.com/home-assistant/core.git

Fix ZHA light color temp support (#76305)

def set_pipeline(self, pipeline): self.pipeline = pipeline

src/sentry/pipeline/provider.py

sentry

Python

d246d2b6d3e014270941209e54f2f12e09ad9a81

provider.py

set_pipeline

https://github.com/getsentry/sentry.git

ref(py): Split up large file (#32862) Co-authored-by: getsantry[bot] <66042841+getsantry[bot]@users.noreply.github.com>

def _setup_dynamic(self) -> None: display.info('Provisioning %s cloud environment.' % self.platform, verbosity=1) config = self._read_config_template() aci = self._create_ansible_core_ci() response = aci.start() if not self.args.explain: credentials = response['aws']['credentials'] values = dict( ACCESS_KEY=credentials['access_key'], SECRET_KEY=credentials['secret_key'], SECURITY_TOKEN=credentials['session_token'], REGION='us-east-1', ) display.sensitive.add(values['SECRET_KEY']) display.sensitive.add(values['SECURITY_TOKEN']) config = self._populate_config_template(config, values) self._write_config(config)

test/lib/ansible_test/_internal/commands/integration/cloud/aws.py

ansible

Python

3eb0485dd92c88cc92152d3656d94492db44b183

aws.py

_setup_dynamic

https://github.com/ansible/ansible.git

ansible-test - Use more native type hints. (#78435) * ansible-test - Use more native type hints. Simple search and replace to switch from comments to native type hints for return types of functions with no arguments. * ansible-test - Use more native type hints. Conversion of simple single-line function annotation type comments to native type hints. * ansible-test - Use more native type hints. Conversion of single-line function annotation type comments with default values to native type hints. * ansible-test - Use more native type hints. Manual conversion of type annotation comments for functions which have pylint directives.

def managed(self): # type: () -> bool return t.cast(bool, self._get_cloud_config(self._MANAGED))

test/lib/ansible_test/_internal/commands/integration/cloud/__init__.py

ansible

Python

a06fa496d3f837cca3c437ab6e9858525633d147

__init__.py

managed

https://github.com/ansible/ansible.git

ansible-test - Code cleanup and refactoring. (#77169) * Remove unnecessary PyCharm ignores. * Ignore intentional undefined attribute usage. * Add missing type hints. Fix existing type hints. * Fix docstrings and comments. * Use function to register completion handler. * Pass strings to display functions. * Fix CompositeAction handling of dest argument. * Use consistent types in expressions/assignments. * Use custom function to keep linters happy. * Add missing raise for custom exception. * Clean up key/value type handling in cloud plugins. * Use dataclass instead of dict for results. * Add custom type_guard function to check lists. * Ignore return type that can't be checked (yet). * Avoid changing types on local variables.

def test_simple_imputer_constant_keep_empty_features(array_type, keep_empty_features): X = np.array([[np.nan, 2], [np.nan, 3], [np.nan, 6]]) X = _convert_container(X, array_type) fill_value = 10 imputer = SimpleImputer( strategy="constant", fill_value=fill_value, keep_empty_features=keep_empty_features, ) for method in ["fit_transform", "transform"]: X_imputed = getattr(imputer, method)(X) assert X_imputed.shape == X.shape constant_feature = ( X_imputed[:, 0].A if array_type == "sparse" else X_imputed[:, 0] ) assert_array_equal(constant_feature, fill_value) @pytest.mark.parametrize("array_type", ["array", "sparse"]) @pytest.mark.parametrize("strategy", ["mean", "median", "most_frequent"]) @pytest.mark.parametrize("keep_empty_features", [True, False])

sklearn/impute/tests/test_impute.py

@pytest.mark.parametrize("array_type", ["array", "sparse"]) @pytest.mark.parametrize("strategy", ["mean", "median", "most_frequent"]) @pytest.mark.parametrize("keep_empty_features", [True, False])

scikit-learn

Python

d8fa96c29828e3ca79ddd5d7466521ac4d95213c

test_impute.py

test_simple_imputer_constant_keep_empty_features

https://github.com/scikit-learn/scikit-learn.git

ENH keep features with all missing values during imputation (#24770) Co-authored-by: Chiara Marmo <cmarmo@users.noreply.github.com> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Jérémie du Boisberranger <34657725+jeremiedbb@users.noreply.github.com> Co-authored-by: Vitor SRG <vitorssrg@gmail.com> Fixes https://github.com/scikit-learn/scikit-learn/pull/16695 Fixes https://github.com/scikit-learn/scikit-learn/issues/16426 Fixes https://github.com/scikit-learn/scikit-learn/issues/16977

def test_copy_with_credential(self): expression = "col1, col2" op = DatabricksCopyIntoOperator( file_location=COPY_FILE_LOCATION, file_format='CSV', table_name='test', task_id=TASK_ID, expression_list=expression, credential={'AZURE_SAS_TOKEN': 'abc'}, ) assert ( op._create_sql_query() == f.strip() )

tests/providers/databricks/operators/test_databricks_sql.py

airflow

Python

401419432082d222b823e4f2a66f21e5cc3ab28d

test_databricks_sql.py

test_copy_with_credential

https://github.com/apache/airflow.git

Add new options to DatabricksCopyIntoOperator (#22076) This includes: * `encryption` - to specify encryption options for a given location * `credential` - to specify authentication options for a given location * `validate` - to control validation of schema & data

def _earlystop_notify_tuner(self, data): _logger.debug('Early stop notify tuner data: [%s]', data) data['type'] = MetricType.FINAL data['value'] = dump(data['value']) self.enqueue_command(CommandType.ReportMetricData, data)

nni/runtime/msg_dispatcher.py

nni

Python

98c1a77f61900d486f46d284c49fb65675dbee6a

msg_dispatcher.py

_earlystop_notify_tuner

https://github.com/microsoft/nni.git

Support multiple HPO experiments in one process (#4855)

def gradient(scalar_field, doit=True): coord_sys = _get_coord_systems(scalar_field) if len(coord_sys) == 0: return Vector.zero elif len(coord_sys) == 1: coord_sys = next(iter(coord_sys)) h1, h2, h3 = coord_sys.lame_coefficients() i, j, k = coord_sys.base_vectors() x, y, z = coord_sys.base_scalars() vx = Derivative(scalar_field, x) / h1 vy = Derivative(scalar_field, y) / h2 vz = Derivative(scalar_field, z) / h3 if doit: return (vx * i + vy * j + vz * k).doit() return vx * i + vy * j + vz * k else: if isinstance(scalar_field, (Add, VectorAdd)): return VectorAdd.fromiter(gradient(i) for i in scalar_field.args) if isinstance(scalar_field, (Mul, VectorMul)): s = _split_mul_args_wrt_coordsys(scalar_field) return VectorAdd.fromiter(scalar_field / i * gradient(i) for i in s) return Gradient(scalar_field)

sympy/vector/operators.py

sympy

Python

975df9b627556d176039ba3a0f3a2e3a3df9686c

operators.py

gradient

https://github.com/sympy/sympy.git

Fixed removals not fully performed earlier

def add_store(source, store, retcode=False, saltenv="base"): source = __salt__["cp.cache_file"](source, saltenv) # Since we're allowing a path, let's make sure it exists if not os.path.exists(source): msg = "cert_file not found: ".format(source) raise CommandExecutionError(msg) cmd = 'certutil.exe -addstore {} "{}"'.format(store, source) if retcode: return __salt__["cmd.retcode"](cmd) else: return __salt__["cmd.run"](cmd)

salt/modules/win_certutil.py

salt

Python

53b3ebc92648c2081c58865713b50a2859ae8310

win_certutil.py

add_store

https://github.com/saltstack/salt.git

Fix win_certutil module to handle paths with spaces

def base_dir(self) -> str: return self._base_dir

python/ray/data/datasource/partitioning.py

ray

Python

9f4cb9b3c9c27ae21bf7807595973231b6814648

partitioning.py

base_dir

https://github.com/ray-project/ray.git

[Datasets] Add Path Partitioning Support for All Content Types (#23624) Adds a content-type-agnostic partition parser with support for filtering files. Also adds some corner-case bug fixes and usability improvements for supporting more robust input path types.

def test_stylesheet_apply_takes_final_rule_in_specificity_clash(): css = ".a {background: red; color: lime;} .b {background: blue;}" stylesheet = _make_stylesheet(css) node = DOMNode(classes="a b", id="c") stylesheet.apply(node) assert node.styles.color == Color(0, 255, 0) # color: lime assert node.styles.background == Color(0, 0, 255) # background: blue

tests/css/test_stylesheet.py

textual

Python

4dd0d9fae43583638f34257f97d5749ca4f2c00c

test_stylesheet.py

test_stylesheet_apply_takes_final_rule_in_specificity_clash

https://github.com/Textualize/textual.git

Add various additional tests around CSS specificity

async def test_check_loop_async_integration(caplog): with pytest.raises(RuntimeError), patch( "homeassistant.util.async_.extract_stack", return_value=[ Mock( filename="/home/paulus/homeassistant/core.py", lineno="23", line="do_something()", ), Mock( filename="/home/paulus/homeassistant/components/hue/light.py", lineno="23", line="self.light.is_on", ), Mock( filename="/home/paulus/aiohue/lights.py", lineno="2", line="something()", ), ], ): hasync.check_loop() assert ( "Detected blocking call inside the event loop. This is causing stability issues. " "Please report issue for hue doing blocking calls at " "homeassistant/components/hue/light.py, line 23: self.light.is_on" in caplog.text )

tests/util/test_async.py

core

Python

dc58bc375ae203e3d394225f9c3a5a14d43cb2f3

test_async.py

test_check_loop_async_integration

https://github.com/home-assistant/core.git

Warn on`time.sleep` in event loop (#63766) Co-authored-by: Martin Hjelmare <marhje52@gmail.com>

def test_callback(self): # ensure that we are correctly testing the fallback when "get_extra_attributes" # is not implemented. mapping_provider = self.provider._user_mapping_provider with self.assertRaises(AttributeError): _ = mapping_provider.get_extra_attributes token = { "type": "bearer", "id_token": "id_token", "access_token": "access_token", } username = "bar" userinfo = { "sub": "foo", "username": username, } expected_user_id = "@%s:%s" % (username, self.hs.hostname) self.provider._exchange_code = simple_async_mock(return_value=token) self.provider._parse_id_token = simple_async_mock(return_value=userinfo) self.provider._fetch_userinfo = simple_async_mock(return_value=userinfo) auth_handler = self.hs.get_auth_handler() auth_handler.complete_sso_login = simple_async_mock() code = "code" state = "state" nonce = "nonce" client_redirect_url = "http://client/redirect" ip_address = "10.0.0.1" session = self._generate_oidc_session_token(state, nonce, client_redirect_url) request = _build_callback_request(code, state, session, ip_address=ip_address) self.get_success(self.handler.handle_oidc_callback(request)) auth_handler.complete_sso_login.assert_called_once_with( expected_user_id, "oidc", request, client_redirect_url, None, new_user=True, auth_provider_session_id=None, ) self.provider._exchange_code.assert_called_once_with(code) self.provider._parse_id_token.assert_called_once_with(token, nonce=nonce) self.provider._fetch_userinfo.assert_not_called() self.render_error.assert_not_called() # Handle mapping errors with patch.object( self.provider, "_remote_id_from_userinfo", new=Mock(side_effect=MappingException()), ): self.get_success(self.handler.handle_oidc_callback(request)) self.assertRenderedError("mapping_error") # Handle ID token errors self.provider._parse_id_token = simple_async_mock(raises=Exception()) self.get_success(self.handler.handle_oidc_callback(request)) self.assertRenderedError("invalid_token") auth_handler.complete_sso_login.reset_mock() self.provider._exchange_code.reset_mock() self.provider._parse_id_token.reset_mock() self.provider._fetch_userinfo.reset_mock() # With userinfo fetching self.provider._user_profile_method = "userinfo_endpoint" token = { "type": "bearer", "access_token": "access_token", } self.provider._exchange_code = simple_async_mock(return_value=token) self.get_success(self.handler.handle_oidc_callback(request)) auth_handler.complete_sso_login.assert_called_once_with( expected_user_id, "oidc", request, client_redirect_url, None, new_user=False, auth_provider_session_id=None, ) self.provider._exchange_code.assert_called_once_with(code) self.provider._parse_id_token.assert_not_called() self.provider._fetch_userinfo.assert_called_once_with(token) self.render_error.assert_not_called() # With an ID token, userinfo fetching and sid in the ID token self.provider._user_profile_method = "userinfo_endpoint" token = { "type": "bearer", "access_token": "access_token", "id_token": "id_token", } id_token = { "sid": "abcdefgh", } self.provider._parse_id_token = simple_async_mock(return_value=id_token) self.provider._exchange_code = simple_async_mock(return_value=token) auth_handler.complete_sso_login.reset_mock() self.provider._fetch_userinfo.reset_mock() self.get_success(self.handler.handle_oidc_callback(request)) auth_handler.complete_sso_login.assert_called_once_with( expected_user_id, "oidc", request, client_redirect_url, None, new_user=False, auth_provider_session_id=id_token["sid"], ) self.provider._exchange_code.assert_called_once_with(code) self.provider._parse_id_token.assert_called_once_with(token, nonce=nonce) self.provider._fetch_userinfo.assert_called_once_with(token) self.render_error.assert_not_called() # Handle userinfo fetching error self.provider._fetch_userinfo = simple_async_mock(raises=Exception()) self.get_success(self.handler.handle_oidc_callback(request)) self.assertRenderedError("fetch_error") # Handle code exchange failure from synapse.handlers.oidc import OidcError self.provider._exchange_code = simple_async_mock( raises=OidcError("invalid_request") ) self.get_success(self.handler.handle_oidc_callback(request)) self.assertRenderedError("invalid_request")

tests/handlers/test_oidc.py

synapse

Python

a121507cfec0ffce45a89f5a1019034eda5b0c70

test_oidc.py

test_callback

https://github.com/matrix-org/synapse.git

Adds misc missing type hints (#11953)

def bicubic_degradation(x, sf=3): x = util.imresize_np(x, scale=1 / sf) return x

ldm/modules/image_degradation/bsrgan.py

stablediffusion

Python

ca86da3a30c4e080d4db8c25fca73de843663cb4

bsrgan.py

bicubic_degradation

https://github.com/Stability-AI/stablediffusion.git

release more models

def plot(self, ax, box_kws, flier_kws, line_kws): self.draw_letter_value_plot(ax, box_kws, flier_kws, line_kws) self.annotate_axes(ax) if self.orient == "h": ax.invert_yaxis() _categorical_docs = dict( # Shared narrative docs categorical_narrative=dedent(), new_categorical_narrative=dedent(), # Shared function parameters input_params=dedent(), string_input_params=dedent(), categorical_data=dedent(), long_form_data=dedent(), order_vars=dedent(), stat_api_params=dedent(), orient=dedent(), color=dedent(), palette=dedent(), hue_norm=dedent(), saturation=dedent(), capsize=dedent(), errwidth=dedent(), width=dedent(), dodge=dedent(), linewidth=dedent(), native_scale=dedent(), formatter=dedent(), legend=dedent(), ax_in=dedent(), ax_out=dedent(), # Shared see also boxplot=dedent(), violinplot=dedent(), stripplot=dedent(), swarmplot=dedent(), barplot=dedent(), countplot=dedent(), pointplot=dedent(), catplot=dedent(), boxenplot=dedent(), ) _categorical_docs.update(_facet_docs)

seaborn/categorical.py

seaborn

Python

b1db0f72627e9fae8fda261514392d53906384cf

categorical.py

plot

https://github.com/mwaskom/seaborn.git

Cleanup and merge #2909 (#2955) * Sorting boxenplot * Boxenplot separate kws Removed `kwargs` which were used to draw the median lines and scatter plot of outliers previously. Added separate kwargs - `box_kws`, `line_kws` (drawing the median lines) and `flier_kws` (for the scatter of outliers). Updated the matching docstring. * In the previous commit most code on the categorical.py file was auto-reformatted. Here it is reverted and only the changes to `seaborn.categorical.boxenplot` and `seaborn.categorical._LVPlotter` are kept. * Reinserted blank lines in docstring. * - Removed redundant indention in `boxenplot` function - Removed commented out code in the `plot` function * Removed default kwargs from `plot` * Removing commented out code * Reverted to ternary expressions * Replaced default kwargs assignment to box_kws Disentangled the nested for loop for default kwargs assignment * Removed remaining `kwargs` item in docstring * Resolved incorrect reference in the box_kws item on the docstring. * Resolved incorrect descriptions for box_kws, line_kws and flier_kws. * Changed line_kws update to source arguments frmo box_kws if there is only a single data point. * Added line_kws test * Added flier_kws test, renamed line_kws test * Tests - further work is required in expanding the tests. Two current issues (a) most are not testing when multiple categories are used on the x-axis, but only a single one. (b) the tests for the box_kws functionality are very slim. * Fix lint issues * Fix pinned tests * Update release notes * Cleanup boxenplot colors test Co-authored-by: EitanHemed <37670372+EitanHemed@users.noreply.github.com>

def get_all_transfers(date, shareholder): condition = " " # if company: # condition = 'AND company = %(company)s ' return frappe.db.sql( .format( condition=condition ), {"date": date, "shareholder": shareholder}, as_dict=1, )

erpnext/accounts/report/share_ledger/share_ledger.py

erpnext

Python

494bd9ef78313436f0424b918f200dab8fc7c20b

share_ledger.py

get_all_transfers

https://github.com/frappe/erpnext.git

style: format code with black

def sqeuclidean_row_norms(X, num_threads): if X.dtype == np.float64: return np.asarray(_sqeuclidean_row_norms64(X, num_threads)) if X.dtype == np.float32: return np.asarray(_sqeuclidean_row_norms32(X, num_threads)) raise ValueError( "Only float64 or float32 datasets are supported at this time, " f"got: X.dtype={X.dtype}." )

sklearn/metrics/_pairwise_distances_reduction/_dispatcher.py

scikit-learn

Python

239e16319116ab7445c0557bb08783ab2d60673d

_dispatcher.py

sqeuclidean_row_norms

https://github.com/scikit-learn/scikit-learn.git

MAINT Introduce `MiddleTermComputer`, an abstraction generalizing `GEMMTermComputer` (#24807) Co-authored-by: Julien Jerphanion <git@jjerphan.xyz> Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org>

def test_groupby_extension_agg(self): super().test_groupby_extension_agg()

pandas/tests/extension/json/test_json.py

pandas

Python

24652cf178c12562585639cba39c46d62b95f107

test_json.py

test_groupby_extension_agg

https://github.com/pandas-dev/pandas.git

TST: Convert skip -> xfail (#46427)

def test_login_deactivate_user_error(self) -> None: user_profile = self.example_user("hamlet") realm = user_profile.realm self.assertTrue(email_auth_enabled(realm)) url = f"{realm.uri}/login/?" + urlencode({"is_deactivated": user_profile.delivery_email}) result = self.client_get(url) self.assertEqual(result.status_code, 200) self.assert_in_response( f"Your account {user_profile.delivery_email} has been deactivated.", result ) auth_dict = realm.authentication_methods_dict() auth_dict["Email"] = False do_set_realm_authentication_methods(realm, auth_dict, acting_user=None) result = self.client_get(url) self.assertEqual(result.status_code, 200) self.assert_in_response( f"Your account {user_profile.delivery_email} has been deactivated.", result )

zerver/tests/test_signup.py

zulip

Python

61de767967bb6af077165075260eda3293f95970

test_signup.py

test_login_deactivate_user_error

https://github.com/zulip/zulip.git

login page: Show form-independent errors even if email auth disabled. These used to only be shown conditional on the {% if password_auth_enabled %} in the template. Meaning that if you had an org with email auth disabled and a deactivated user tried to log in, they wouldn't see the error shown and get confused. This switches the position of where these error will be shown (above the login+password form instead of below it), but it looks fine.

def location_name(self) -> str | None: return self._location_name

homeassistant/components/mqtt/device_tracker/schema_discovery.py

core

Python

bcae6d604e2967c7475f0caa4b1b5e4e76ab88bf

schema_discovery.py

location_name

https://github.com/home-assistant/core.git

Improve MQTT type hints part 8 (#81034) * Improve typing device_tracker discovery * Improve typing device_tracker yaml * Add test source_type attribute * Follow up comment * Initialize at `__init__` not at class level. * Use full name for return variable * Correct import, remove assert * Use AsyncSeeCallback

def __await__(self): return self.__run().__await__()

gradio/utils.py

gradio

Python

51c8c34486bfddca5948e46e498de44e21ab6496

utils.py

__await__

https://github.com/gradio-app/gradio.git

Async Request Class (#1595) * Implement Request class and its tests. * Add new requirements * Reformat codebase. * Fix formatting. * Add library level requirements. * Convert validated_data property to get_validated_data function. * Fix the client fixture. * Update test/test_utils.py * Update test/test_utils.py * Fix the client fixture. * Add missing initialization for Request._validated_data * Fix async test problem with test_tunneling.py * Update gradio/utils.py * Update gradio/utils.py * Fix formatting. Co-authored-by: Ömer Faruk Özdemir <farukozderim@gmail.com>

async def enter_async_context(self, cm): _cm_type = type(cm) _exit = _cm_type.__aexit__ result = await _cm_type.__aenter__(cm) self._push_async_cm_exit(cm, _exit) return result

python3.10.4/Lib/contextlib.py

XX-Net

Python

8198943edd73a363c266633e1aa5b2a9e9c9f526

contextlib.py

enter_async_context

https://github.com/XX-net/XX-Net.git

add python 3.10.4 for windows

def strip_to_restore(self, text): text, puncs = self._strip_to_restore(text) return text, puncs

TTS/tts/utils/text/punctuation.py

TTS

Python

8d85af84cd5f1748f979fddcbc4aab1449f61ecb

punctuation.py

strip_to_restore

https://github.com/coqui-ai/TTS.git

Implement Punctuation class

def batch_encode_candidates(self, text, **kwargs): r # Always using a fixed sequence length to encode in order to stack candidates into a batch. kwargs["padding"] = PaddingStrategy.MAX_LENGTH batch_text = text batch_text_pair = kwargs.pop("text_pair", None) return_tensors = kwargs.pop("return_tensors", None) output_data = { "input_ids": [], "attention_mask": [], "token_type_ids": [], } for idx, candidate_text in enumerate(batch_text): if batch_text_pair is not None: candidate_text_pair = batch_text_pair[idx] else: candidate_text_pair = None encoded_candidates = super().__call__(candidate_text, candidate_text_pair, return_tensors=None, **kwargs) encoded_input_ids = encoded_candidates.get("input_ids") encoded_attention_mask = encoded_candidates.get("attention_mask") encoded_token_type_ids = encoded_candidates.get("token_type_ids") if encoded_input_ids is not None: output_data["input_ids"].append(encoded_input_ids) if encoded_attention_mask is not None: output_data["attention_mask"].append(encoded_attention_mask) if encoded_token_type_ids is not None: output_data["token_type_ids"].append(encoded_token_type_ids) output_data = dict((key, item) for key, item in output_data.items() if len(item) != 0) return BatchEncoding(output_data, tensor_type=return_tensors)

src/transformers/models/realm/tokenization_realm.py

transformers

Python

22454ae492eca4bb749fa6d770dffc91d17dab87

tokenization_realm.py

batch_encode_candidates

https://github.com/huggingface/transformers.git

Add REALM (#13292) * REALM initial commit * Retriever OK (Update new_gelu). * Encoder prediction score OK * Encoder pretrained model OK * Update retriever comments * Update docs, tests, and imports * Prune unused models * Make embedder as a module `RealmEmbedder` * Add RealmRetrieverOutput * Update tokenization * Pass all tests in test_modeling_realm.py * Prune RealmModel * Update docs * Add training test. * Remove completed TODO * Style & Quality * Prune `RealmModel` * Fixup * Changes: 1. Remove RealmTokenizerFast 2. Update docstrings 3. Add a method to RealmTokenizer to handle candidates tokenization. * Fix up * Style * Add tokenization tests * Update `from_pretrained` tests * Apply suggestions * Style & Quality * Copy BERT model * Fix comment to avoid docstring copying * Make RealmBertModel private * Fix bug * Style * Basic QA * Save * Complete reader logits * Add searcher * Complete searcher & reader * Move block records init to constructor * Fix training bug * Add some outputs to RealmReader * Add finetuned checkpoint variable names parsing * Fix bug * Update REALM config * Add RealmForOpenQA * Update convert_tfrecord logits * Fix bugs * Complete imports * Update docs * Update naming * Add brute-force searcher * Pass realm model tests * Style * Exclude RealmReader from common tests * Fix * Fix * convert docs * up * up * more make style * up * upload * up * Fix * Update src/transformers/__init__.py * adapt testing * change modeling code * fix test * up * up * up * correct more * make retriever work * update * make style * finish main structure * Resolve merge conflict * Make everything work * Style * Fixup * Fixup * Update training test * fix retriever * remove hardcoded path * Fix * Fix modeling test * Update model links * Initial retrieval test * Fix modeling test * Complete retrieval tests * Fix * style * Fix tests * Fix docstring example * Minor fix of retrieval test * Update license headers and docs * Apply suggestions from code review * Style * Apply suggestions from code review * Add an example to RealmEmbedder * Fix Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

def weight_intercept(self, coef): if not self.base_loss.is_multiclass: if self.fit_intercept: intercept = coef[-1] weights = coef[:-1] else: intercept = 0.0 weights = coef else: # reshape to (n_classes, n_dof) if coef.ndim == 1: weights = coef.reshape((self.base_loss.n_classes, -1), order="F") else: weights = coef if self.fit_intercept: intercept = weights[:, -1] weights = weights[:, :-1] else: intercept = 0.0 return weights, intercept

sklearn/linear_model/_linear_loss.py

scikit-learn

Python

ff9344f3d8d11d38fa3a2497199113e5bac9537c

_linear_loss.py

weight_intercept

https://github.com/scikit-learn/scikit-learn.git

FEA add (single) Cholesky Newton solver to GLMs (#24637) * FEA add NewtonSolver, CholeskyNewtonSolver and QRCholeskyNewtonSolver * ENH better singular hessian special solve * CLN fix some typos found by reviewer * TST assert ConvergenceWarning is raised * MNT add BaseCholeskyNewtonSolver * WIP colinear design in GLMs * FIX _solve_singular * FIX false unpacking in * TST add tests for unpenalized GLMs * TST fix solutions of glm_dataset * ENH add SVDFallbackSolver * CLN remove SVDFallbackSolver * ENH use gradient step for singular hessians * ENH print iteration number in warnings * TST improve test_linalg_warning_with_newton_solver * CLN LinAlgWarning fron scipy.linalg * ENH more robust hessian * ENH increase maxls for lbfgs to make it more robust * ENH add hessian_warning for too many negative hessian values * CLN some warning messages * ENH add lbfgs_step * ENH use lbfgs_step for hessian_warning * TST make them pass * TST tweek rtol for lbfgs * TST add rigoros test for GLMs * TST improve test_warm_start * ENH improve lbfgs options for better convergence * CLN fix test_warm_start * TST fix assert singular values in datasets * CLN address most review comments * ENH enable more vebosity levels for lbfgs * DOC add whatsnew * CLN remove xfail and clean a bit * CLN docstring about minimum norm * More informative repr for the glm_dataset fixture cases * Forgot to run black * CLN remove unnecessary filterwarnings * CLN address review comments * Trigger [all random seeds] on the following tests: test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * CLN add comment for lbfgs ftol=64 * machine precision * CLN XXX code comment * Trigger [all random seeds] on the following tests: test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * CLN link issue and remove code snippet in comment * Trigger [all random seeds] on the following tests: test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * CLN add catch_warnings * Trigger [all random seeds] on the following tests: test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * Trigger [all random seeds] on the following tests: test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * [all random seeds] test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * Trigger with -Werror [all random seeds] test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * ENH increase maxls to 50 * [all random seeds] test_glm_regression test_glm_regression_hstacked_X test_glm_regression_vstacked_X test_glm_regression_unpenalized test_glm_regression_unpenalized_hstacked_X test_glm_regression_unpenalized_vstacked_X test_warm_start * Revert "Trigger with -Werror [all random seeds]" This reverts commit 99f4cf99ca41b4ad2bdad537ad60f936970e3a88. * TST add catch_warnings to filterwarnings * TST adapt tests for newton solvers * CLN cleaner gradient step with gradient_times_newton * DOC add whatsnew * ENH always use lbfgs as fallback * TST adapt rtol * TST fix test_linalg_warning_with_newton_solver * CLN address some review comments * Improve tests related to convergence warning on collinear data * overfit -> fit * Typo in comment * Apply suggestions from code review * ENH fallback_lbfgs_solve - Do not use lbfgs steps, fall back complete to lbfgs * ENH adapt rtol * Improve test_linalg_warning_with_newton_solver * Better comments * Fixed Hessian casing and improved warning messages * [all random seeds] test_linalg_warning_with_newton_solver * Ignore ConvergenceWarnings for now if convergence is good * CLN remove counting of warnings * ENH fall back to lbfgs if line search did not converge * DOC better comment on performance bottleneck * Update GLM related examples to use the new solver * CLN address reviewer comments * EXA improve some wordings * CLN do not pop "solver in parameter constraints * CLN fix typos * DOC fix docstring * CLN remove solver newton-qr-cholesky * DOC update PR number in whatsnew * CLN address review comments * CLN remove unnecessary catch_warnings * CLN address some review comments * DOC more precise whatsnew * CLN use init_zero_coef * CLN use and test init_zero_coef * CLN address some review comments * CLN mark NewtonSolver as private by leading underscore * CLN exact comments for inner_solve * TST add test_newton_solver_verbosity * TST extend test_newton_solver_verbosity * TST logic in test_glm_regression_unpenalized * TST use count_nonzero * CLN remove super rare line search checks * MNT move Newton solver to new file _newton_solver.py Co-authored-by: Olivier Grisel <olivier.grisel@ensta.org> Co-authored-by: Julien Jerphanion <git@jjerphan.xyz>

def _run_executable(self, prog, args, run_from_path, runtime): # Run the test in a clean environment to make sure they're really self-contained. prog_env = copy.deepcopy(os.environ) prog_env['PATH'] = '' del prog_env['PATH'] # For Windows we need to keep minimal PATH for successful running of some tests. if is_win: # Minimum Windows PATH is in most cases: C:\Windows\system32;C:\Windows prog_env['PATH'] = os.pathsep.join(winutils.get_system_path()) exe_path = prog if run_from_path: # Run executable in the temp directory. Add the directory containing the executable to $PATH. Basically, # pretend we are a shell executing the program from $PATH. prog_cwd = str(self._tmpdir) prog_name = os.path.basename(prog) prog_env['PATH'] = os.pathsep.join([prog_env.get('PATH', ''), os.path.dirname(prog)]) else: # Run executable in the directory where it is. prog_cwd = os.path.dirname(prog) # The executable will be called with argv[0] as relative not absolute path. prog_name = os.path.join(os.curdir, os.path.basename(prog)) args = [prog_name] + args # Using sys.stdout/sys.stderr for subprocess fixes printing messages in Windows command prompt. Py.test is then # able to collect stdout/sterr messages and display them if a test fails. return self._run_executable_(args, exe_path, prog_env, prog_cwd, runtime)

PyInstaller/utils/conftest.py

pyinstaller

Python

be94db4587c16f3f6498d64d563c7ce740e11863

conftest.py

_run_executable

https://github.com/pyinstaller/pyinstaller.git

tests: do not attempt to re-run executable after a failed run Remove the re-runs of a failed executable. This functionality was originally intended for executables whose execution timed out (when running in "regular" mode, where we expect the program to exit). However, it ended up subtly broken ever since cf9dfec8018c96511f8c8caffc2b2e965350f2f9 changed the program exit code for unhandled exceptions from -1 to 1 to match the behavior of python interpreter. Consequently, every time that a test executable fails due to unhandled exception, it is re-run again. This unnecessarily prolongs the test time (especially for onefile executables) and bloats/obfuscates the captured test output (since we end up with bootloader log of two runs instead of just one). Remove this built-in re-run functionality altogether, because re-runs usually mask some other issue that should be fixed.

def unscale_gradients(self, optimizer=None): if self.state.use_fp16 and self.native_amp: if optimizer is None: # TODO: this unscales all optimizers where we should only unscale the one where parameters are. optimizer = self._optimizers elif not isinstance(optimizer, (tuple, list)): optimizer = [optimizer] for opt in optimizer: while isinstance(opt, AcceleratedOptimizer): opt = opt.optimizer self.scaler.unscale_(opt)

src/accelerate/accelerator.py

accelerate

Python

fb5ed62c102c0323486b89805e1888495de3db15

accelerator.py

unscale_gradients

https://github.com/huggingface/accelerate.git

Convert documentation to the new front (#271) * Main conversion * Doc styling * Style * New front deploy * Fixes * Fixes * Fix new docstrings * Style

def test_coin_api_load_df_for_ta(get_bitcoin, mocker): mock_load = mocker.patch( base + "due_diligence.pycoingecko_model.CoinGeckoAPI.get_coin_market_chart_by_id" ) _, symbol = get_bitcoin coin_map_df = prepare_all_coins_df().set_index("Symbol").loc[symbol.upper()].iloc[0] with open( "tests/openbb_terminal/cryptocurrency/json/test_cryptocurrency_helpers/btc_usd_test_data.json", encoding="utf8", ) as f: sample_return = json.load(f) mock_load.return_value = sample_return mock_return, vs = load_ta_data( coin_map_df=coin_map_df, source="cg", currency="usd", days=30, ) assert mock_return.shape == (31, 4) assert vs == "usd" @pytest.mark.record_stdout @pytest.mark.vcr

tests/openbb_terminal/cryptocurrency/test_cryptocurrency_helpers.py

@pytest.mark.record_stdout @pytest.mark.vcr

OpenBBTerminal

Python

9068ad01249c1e1adaca3ef9a704d70da7e3a17b

test_cryptocurrency_helpers.py

test_coin_api_load_df_for_ta

https://github.com/OpenBB-finance/OpenBBTerminal.git

Refactored Crypto Tests (#1743) * Refactored tests * Removed unused command * Added tests * Tests : remove cassettes files + add fixture * Black * Tests : skip tests Co-authored-by: didierlopes.eth <dro.lopes@campus.fct.unl.pt> Co-authored-by: minhhoang1023 <40023817+minhhoang1023@users.noreply.github.com> Co-authored-by: Chavithra PARANA <chavithra@gmail.com>

def choose_parent_view(self, request): kwargs = {"model_admin": self} view_class = self.choose_parent_view_class return view_class.as_view(**kwargs)(request)

wagtail/contrib/modeladmin/options.py

wagtail

Python

d10f15e55806c6944827d801cd9c2d53f5da4186

options.py

choose_parent_view

https://github.com/wagtail/wagtail.git

Reformat with black

def is_within_directory(directory, target): # type: (str, str) -> bool abs_directory = os.path.abspath(directory) abs_target = os.path.abspath(target) prefix = os.path.commonprefix([abs_directory, abs_target]) return prefix == abs_directory

.venv/lib/python3.8/site-packages/pip/_internal/utils/unpacking.py

transferlearning

Python