id list | project string | origin_file list | test_list list | prob_info list | type list | node list | language string | toolfunc_count int64 | func_count int64 | pytest_info dict |
|---|---|---|---|---|---|---|---|---|---|---|
[
"transformers.src.transformers.audio_utils.hertz_to_mel",
"transformers.src.transformers.audio_utils.mel_filter_bank"
] | transformers | [
"transformers/audio_utils.py",
"transformers/audio_utils.py",
"transformers/models/clap/feature_extraction_clap.py"
] | [
"tests/models/audio_spectrogram_transformer/test_feature_extraction_audio_spectrogram_transformer.py",
"tests/models/clap/test_feature_extraction_clap.py",
"tests/models/univnet/test_feature_extraction_univnet.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 1127,
"func_start_lineno": 26,
"func_end_lineno": 59,
"func_code": "def hertz_to_mel(freq: Union[float, np.ndarray], mel_scale: str = \"htk\") -> Union[float, np.ndarray]:\n \"\"\"\n Convert frequency from hertz to mels.\n\n Args:\n ... | [
"function_empty"
] | [
"transformers.audio_utils.hertz_to_mel",
"transformers.audio_utils.mel_filter_bank",
"transformers.models.clap.feature_extraction_clap.ClapFeatureExtractor.__init__"
] | Python | 2 | 2 | {
"total_num": 77,
"base_passed_num": 47
} |
[
"transformers.src.transformers.image_processing_utils.get_size_dict",
"transformers.src.transformers.image_transforms.resize",
"transformers.src.transformers.models.blip.image_processing_blip.BlipImageProcessor::resize",
"transformers.src.transformers.models.blip.image_processing_blip.BlipImageProcessor::prep... | transformers | [
"transformers/image_processing_utils.py",
"transformers/image_transforms.py",
"transformers/models/blip/image_processing_blip.py",
"transformers/models/blip/image_processing_blip.py"
] | [
"tests/models/blip/test_image_processing_blip.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 287,
"func_start_lineno": 208,
"func_end_lineno": 249,
"func_code": "def get_size_dict(\n size: Union[int, Iterable[int], Dict[str, int]] = None,\n max_size: Optional[int] = None,\n height_width_order: bool = True,\n default_to_square: b... | [
"function_empty",
"Development"
] | [
"transformers.image_processing_utils.get_size_dict",
"transformers.image_transforms.resize",
"transformers.models.blip.image_processing_blip.BlipImageProcessor.resize",
"transformers.models.blip.image_processing_blip.BlipImageProcessor.preprocess"
] | Python | 3 | 4 | {
"total_num": 20,
"base_passed_num": 12
} |
[
"transformers.src.transformers.image_processing_utils.get_size_dict",
"transformers.src.transformers.image_transforms.get_resize_output_image_size",
"transformers.src.transformers.image_transforms.resize",
"transformers.src.transformers.models.chinese_clip.image_processing_chinese_clip.ChineseCLIPImageProcess... | transformers | [
"transformers/image_processing_utils.py",
"transformers/image_transforms.py",
"transformers/image_transforms.py",
"transformers/models/chinese_clip/image_processing_chinese_clip.py"
] | [
"tests/models/chinese_clip/test_image_processing_chinese_clip.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 287,
"func_start_lineno": 208,
"func_end_lineno": 249,
"func_code": "def get_size_dict(\n size: Union[int, Iterable[int], Dict[str, int]] = None,\n max_size: Optional[int] = None,\n height_width_order: bool = True,\n default_to_square: b... | [
"function_empty",
"Development"
] | [
"transformers.image_processing_utils.get_size_dict",
"transformers.image_transforms.get_resize_output_image_size",
"transformers.image_transforms.resize",
"transformers.models.chinese_clip.image_processing_chinese_clip.ChineseCLIPImageProcessor.resize"
] | Python | 3 | 4 | {
"total_num": 21,
"base_passed_num": 12
} |
[
"transformers.src.transformers.image_utils.infer_channel_dimension_format",
"transformers.src.transformers.image_utils.get_image_size",
"transformers.src.transformers.image_transforms.resize",
"transformers.src.transformers.models.fuyu.image_processing_fuyu.FuyuImageProcessor::resize"
] | transformers | [
"transformers/image_utils.py",
"transformers/image_utils.py",
"transformers/image_transforms.py",
"transformers/models/fuyu/image_processing_fuyu.py"
] | [
"tests/models/fuyu/test_image_processing_fuyu.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 811,
"func_start_lineno": 220,
"func_end_lineno": 254,
"func_code": "def infer_channel_dimension_format(\n image: np.ndarray, num_channels: Optional[Union[int, Tuple[int, ...]]] = None\n) -> ChannelDimension:\n \"\"\"\n Infers the channel d... | [
"function_empty"
] | [
"transformers.image_utils.infer_channel_dimension_format",
"transformers.image_utils.get_image_size",
"transformers.image_transforms.resize",
"transformers.models.fuyu.image_processing_fuyu.FuyuImageProcessor.resize"
] | Python | 4 | 4 | {
"total_num": 4,
"base_passed_num": 1
} |
[
"transformers.src.transformers.models.musicgen_melody.feature_extraction_musicgen_melody.MusicgenMelodyFeatureExtractor::_extract_stem_indices",
"transformers.src.transformers.models.musicgen_melody.feature_extraction_musicgen_melody.MusicgenMelodyFeatureExtractor::__call__"
] | transformers | [
"transformers/models/musicgen_melody/feature_extraction_musicgen_melody.py",
"transformers/models/musicgen_melody/feature_extraction_musicgen_melody.py"
] | [
"tests/models/musicgen_melody/test_feature_extraction_musicgen_melody.py"
] | [
{
"class_start_lineno": 39,
"class_end_lineno": 331,
"func_start_lineno": 146,
"func_end_lineno": 179,
"func_code": " def _extract_stem_indices(self, audio, sampling_rate=None):\n \"\"\"\n Extracts stems from the output of the [Demucs](https://github.com/adefossez/demucs/tree/ma... | [
"function_empty"
] | [
"transformers.models.musicgen_melody.feature_extraction_musicgen_melody.MusicgenMelodyFeatureExtractor._extract_stem_indices",
"transformers.models.musicgen_melody.feature_extraction_musicgen_melody.MusicgenMelodyFeatureExtractor.__call__"
] | Python | 2 | 2 | {
"total_num": 18,
"base_passed_num": 15
} |
[
"transformers.src.transformers.utils.backbone_utils._align_output_features_output_indices",
"transformers.src.transformers.utils.backbone_utils.get_aligned_output_features_output_indices"
] | transformers | [
"transformers/utils/backbone_utils.py",
"transformers/utils/backbone_utils.py",
"transformers/models/rt_detr/configuration_rt_detr_resnet.py"
] | [
"tests/models/rt_detr/test_modeling_rt_detr_resnet.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 377,
"func_start_lineno": 77,
"func_end_lineno": 105,
"func_code": "def _align_output_features_output_indices(\n out_features: Optional[List[str]],\n out_indices: Optional[Union[List[int], Tuple[int]]],\n stage_names: List[str],\n):\n \"... | [
"function_empty"
] | [
"transformers.utils.backbone_utils._align_output_features_output_indices",
"transformers.utils.backbone_utils.get_aligned_output_features_output_indices",
"transformers.models.rt_detr.configuration_rt_detr_resnet.RTDetrResNetConfig.__init__"
] | Python | 2 | 2 | {
"total_num": 8,
"base_passed_num": 0
} |
[
"transformers.src.transformers.image_utils.get_image_size",
"transformers.src.transformers.image_transforms.get_resize_output_image_size",
"transformers.src.transformers.image_transforms.resize",
"transformers.src.transformers.models.video_llava.image_processing_video_llava.VideoLlavaImageProcessor::resize"
] | transformers | [
"transformers/image_utils.py",
"transformers/image_transforms.py",
"transformers/image_transforms.py",
"transformers/models/video_llava/image_processing_video_llava.py"
] | [
"tests/models/video_llava/test_image_processing_video_llava.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 811,
"func_start_lineno": 281,
"func_end_lineno": 302,
"func_code": "def get_image_size(image: np.ndarray, channel_dim: ChannelDimension = None) -> Tuple[int, int]:\n \"\"\"\n Returns the (height, width) dimensions of the image.\n\n Args:\n... | [
"function_empty"
] | [
"transformers.image_utils.get_image_size",
"transformers.image_transforms.get_resize_output_image_size",
"transformers.image_transforms.resize",
"transformers.models.video_llava.image_processing_video_llava.VideoLlavaImageProcessor.resize"
] | Python | 4 | 4 | {
"total_num": 18,
"base_passed_num": 6
} |
[
"transformers.src.transformers.image_processing_utils.get_size_dict",
"transformers.src.transformers.image_utils.get_image_size",
"transformers.src.transformers.image_transforms.get_resize_output_image_size",
"transformers.src.transformers.image_transforms.resize",
"transformers.src.transformers.models.vide... | transformers | [
"transformers/image_processing_utils.py",
"transformers/image_utils.py",
"transformers/image_transforms.py",
"transformers/image_transforms.py",
"transformers/models/videomae/image_processing_videomae.py"
] | [
"tests/models/videomae/test_image_processing_videomae.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 287,
"func_start_lineno": 208,
"func_end_lineno": 249,
"func_code": "def get_size_dict(\n size: Union[int, Iterable[int], Dict[str, int]] = None,\n max_size: Optional[int] = None,\n height_width_order: bool = True,\n default_to_square: b... | [
"function_empty"
] | [
"transformers.image_processing_utils.get_size_dict",
"transformers.image_utils.get_image_size",
"transformers.image_transforms.get_resize_output_image_size",
"transformers.image_transforms.resize",
"transformers.models.videomae.image_processing_videomae.VideoMAEImageProcessor.resize"
] | Python | 5 | 5 | {
"total_num": 13,
"base_passed_num": 6
} |
[
"transformers.src.transformers.image_processing_utils.get_size_dict",
"transformers.src.transformers.image_utils.get_image_size",
"transformers.src.transformers.image_transforms.get_resize_output_image_size",
"transformers.src.transformers.image_transforms.resize",
"transformers.src.transformers.models.vivi... | transformers | [
"transformers/image_processing_utils.py",
"transformers/image_utils.py",
"transformers/image_transforms.py",
"transformers/image_transforms.py",
"transformers/models/vivit/image_processing_vivit.py"
] | [
"tests/models/vivit/test_image_processing_vivit.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 287,
"func_start_lineno": 208,
"func_end_lineno": 249,
"func_code": "def get_size_dict(\n size: Union[int, Iterable[int], Dict[str, int]] = None,\n max_size: Optional[int] = None,\n height_width_order: bool = True,\n default_to_square: b... | [
"function_empty",
"Development"
] | [
"transformers.image_processing_utils.get_size_dict",
"transformers.image_utils.get_image_size",
"transformers.image_transforms.get_resize_output_image_size",
"transformers.image_transforms.resize",
"transformers.models.vivit.image_processing_vivit.VivitImageProcessor.resize"
] | Python | 4 | 5 | {
"total_num": 14,
"base_passed_num": 7
} |
[
"transformers.src.transformers.utils.generic._get_frameworks_and_test_func",
"transformers.src.transformers.models.wav2vec2.tokenization_wav2vec2.Wav2Vec2CTCTokenizer::decode",
"transformers.src.transformers.models.wav2vec2.tokenization_wav2vec2.Wav2Vec2CTCTokenizer::convert_tokens_to_string",
"transformers.s... | transformers | [
"transformers/utils/generic.py",
"transformers/models/wav2vec2/tokenization_wav2vec2.py",
"transformers/models/wav2vec2/tokenization_wav2vec2.py",
"transformers/models/wav2vec2/tokenization_wav2vec2.py"
] | [
"tests/models/wav2vec2/test_tokenization_wav2vec2.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 856,
"func_start_lineno": 98,
"func_end_lineno": 116,
"func_code": "def _get_frameworks_and_test_func(x):\n \"\"\"\n Returns an (ordered since we are in Python 3.7+) dictionary framework to test function, which places the framework\n we can... | [
"function_empty",
"Development"
] | [
"transformers.utils.generic._get_frameworks_and_test_func",
"transformers.models.wav2vec2.tokenization_wav2vec2.Wav2Vec2CTCTokenizer.decode",
"transformers.models.wav2vec2.tokenization_wav2vec2.Wav2Vec2CTCTokenizer.convert_tokens_to_string",
"transformers.models.wav2vec2.tokenization_wav2vec2.Wav2Vec2CTCToken... | Python | 1 | 4 | {
"total_num": 102,
"base_passed_num": 79
} |
[
"transformers.src.transformers.audio_utils.hertz_to_mel",
"transformers.src.transformers.audio_utils.mel_filter_bank",
"transformers.src.transformers.audio_utils.window_function",
"transformers.src.transformers.models.whisper.feature_extraction_whisper.WhisperFeatureExtractor::_np_extract_fbank_features"
] | transformers | [
"transformers/audio_utils.py",
"transformers/audio_utils.py",
"transformers/models/whisper/feature_extraction_whisper.py",
"transformers/audio_utils.py",
"transformers/models/whisper/feature_extraction_whisper.py"
] | [
"tests/models/whisper/test_feature_extraction_whisper.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 1127,
"func_start_lineno": 26,
"func_end_lineno": 59,
"func_code": "def hertz_to_mel(freq: Union[float, np.ndarray], mel_scale: str = \"htk\") -> Union[float, np.ndarray]:\n \"\"\"\n Convert frequency from hertz to mels.\n\n Args:\n ... | [
"function_empty",
"Development"
] | [
"transformers.audio_utils.hertz_to_mel",
"transformers.audio_utils.mel_filter_bank",
"transformers.models.whisper.feature_extraction_whisper.WhisperFeatureExtractor.__init__",
"transformers.audio_utils.window_function",
"transformers.models.whisper.feature_extraction_whisper.WhisperFeatureExtractor._np_extr... | Python | 3 | 4 | {
"total_num": 19,
"base_passed_num": 8
} |
[
"transformers.src.transformers.utils.import_utils.create_import_structure_from_path",
"transformers.src.transformers.utils.import_utils.define_import_structure"
] | transformers | [
"transformers/utils/import_utils.py",
"transformers/utils/import_utils.py"
] | [
"tests/utils/test_dynamic_module_utils.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 2158,
"func_start_lineno": 1846,
"func_end_lineno": 2037,
"func_code": "def create_import_structure_from_path(module_path):\n \"\"\"\n This method takes the path to a file/a folder and returns the import structure.\n If a file is given, it ... | [
"function_empty"
] | [
"transformers.utils.import_utils.create_import_structure_from_path",
"transformers.utils.import_utils.define_import_structure"
] | Python | 2 | 2 | {
"total_num": 10,
"base_passed_num": 0
} |
[
"transformers.src.transformers.modeling_rope_utils._compute_default_rope_parameters",
"transformers.src.transformers.modeling_rope_utils._compute_linear_scaling_rope_parameters",
"transformers.src.transformers.modeling_rope_utils._compute_llama3_parameters"
] | transformers | [
"transformers/modeling_rope_utils.py",
"transformers/modeling_rope_utils.py",
"transformers/modeling_rope_utils.py"
] | [
"tests/utils/test_modeling_rope_utils.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 560,
"func_start_lineno": 29,
"func_end_lineno": 68,
"func_code": "def _compute_default_rope_parameters(\n config: Optional[PretrainedConfig] = None,\n device: Optional[\"torch.device\"] = None,\n seq_len: Optional[int] = None,\n **rope_... | [
"function_empty"
] | [
"transformers.modeling_rope_utils._compute_default_rope_parameters",
"transformers.modeling_rope_utils._compute_linear_scaling_rope_parameters",
"transformers.modeling_rope_utils._compute_llama3_parameters"
] | Python | 3 | 3 | {
"total_num": 10,
"base_passed_num": 2
} |
[
"UniRef.detectron2.structures.boxes.Boxes::__getitem__",
"UniRef.detectron2.structures.instances.Instances::set",
"UniRef.detectron2.structures.instances.Instances::__getitem__"
] | UniRef | [
"detectron2/structures/boxes.py",
"detectron2/structures/instances.py",
"detectron2/structures/instances.py"
] | [
"tests/structures/test_instances.py"
] | [
{
"class_start_lineno": 130,
"class_end_lineno": 307,
"func_start_lineno": 213,
"func_end_lineno": 235,
"func_code": " def __getitem__(self, item) -> \"Boxes\":\n \"\"\"\n Args:\n item: int, slice, or a BoolTensor\n\n Returns:\n Boxes: Create a new :... | [
"function_empty"
] | [
"detectron2.structures.boxes.Boxes.__getitem__",
"detectron2.structures.instances.Instances.set",
"detectron2.structures.instances.Instances.__getitem__"
] | Python | 3 | 3 | {
"total_num": 10,
"base_passed_num": 0
} |
[
"UniRef.detectron2.modeling.roi_heads.fast_rcnn._log_classification_stats",
"UniRef.detectron2.modeling.box_regression.Box2BoxTransform::get_deltas",
"UniRef.detectron2.modeling.box_regression.Box2BoxTransformRotated::get_deltas",
"UniRef.detectron2.modeling.box_regression._dense_box_regression_loss",
"UniR... | UniRef | [
"detectron2/modeling/roi_heads/fast_rcnn.py",
"detectron2/modeling/box_regression.py",
"detectron2/modeling/box_regression.py",
"detectron2/modeling/box_regression.py",
"detectron2/modeling/roi_heads/fast_rcnn.py"
] | [
"tests/modeling/test_fast_rcnn.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 462,
"func_start_lineno": 87,
"func_end_lineno": 114,
"func_code": "def _log_classification_stats(pred_logits, gt_classes, prefix=\"fast_rcnn\"):\n \"\"\"\n Log the classification metrics to EventStorage.\n\n Args:\n pred_logits: Rx(... | [
"function_empty"
] | [
"detectron2.modeling.roi_heads.fast_rcnn._log_classification_stats",
"detectron2.modeling.box_regression.Box2BoxTransform.get_deltas",
"detectron2.modeling.box_regression.Box2BoxTransformRotated.get_deltas",
"detectron2.modeling.box_regression._dense_box_regression_loss",
"detectron2.modeling.roi_heads.fast... | Python | 5 | 5 | {
"total_num": 5,
"base_passed_num": 2
} |
[
"UniRef.detectron2.data.detection_utils.check_metadata_consistency",
"UniRef.detectron2.data.detection_utils.create_keypoint_hflip_indices",
"UniRef.detectron2.structures.instances.Instances::set",
"UniRef.detectron2.data.detection_utils.annotations_to_instances"
] | UniRef | [
"detectron2/data/detection_utils.py",
"detectron2/data/detection_utils.py",
"detectron2/structures/instances.py",
"detectron2/structures/instances.py",
"detectron2/data/detection_utils.py"
] | [
"tests/data/test_detection_utils.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 623,
"func_start_lineno": 564,
"func_end_lineno": 590,
"func_code": "def check_metadata_consistency(key, dataset_names):\n \"\"\"\n Check that the datasets have consistent metadata.\n\n Args:\n key (str): a metadata key\n data... | [
"function_empty"
] | [
"detectron2.data.detection_utils.check_metadata_consistency",
"detectron2.data.detection_utils.create_keypoint_hflip_indices",
"detectron2.structures.instances.Instances.set",
"detectron2.structures.instances.Instances.__setattr__",
"detectron2.data.detection_utils.annotations_to_instances"
] | Python | 4 | 4 | {
"total_num": 10,
"base_passed_num": 7
} |
[
"UniRef.detectron2.structures.instances.Instances::set",
"UniRef.detectron2.tracking.hungarian_tracker.BaseHungarianTracker::_initialize_extra_fields"
] | UniRef | [
"detectron2/structures/instances.py",
"detectron2/structures/instances.py",
"detectron2/tracking/hungarian_tracker.py"
] | [
"tests/tracking/test_hungarian_tracker.py"
] | [
{
"class_start_lineno": 7,
"class_end_lineno": 192,
"func_start_lineno": 68,
"func_end_lineno": 79,
"func_code": " def set(self, name: str, value: Any) -> None:\n \"\"\"\n Set the field named `name` to `value`.\n The length of `value` must be the number of instances,\n ... | [
"function_empty"
] | [
"detectron2.structures.instances.Instances.set",
"detectron2.structures.instances.Instances.__setattr__",
"detectron2.tracking.hungarian_tracker.BaseHungarianTracker._initialize_extra_fields"
] | Python | 2 | 2 | {
"total_num": 2,
"base_passed_num": 1
} |
[
"UniRef.detectron2.data.catalog._DatasetCatalog::get",
"UniRef.detectron2.data.datasets.coco.convert_to_coco_dict"
] | UniRef | [
"detectron2/data/catalog.py",
"detectron2/data/datasets/coco.py"
] | [
"tests/data/test_coco.py"
] | [
{
"class_start_lineno": 13,
"class_end_lineno": 78,
"func_start_lineno": 40,
"func_end_lineno": 58,
"func_code": " def get(self, name):\n \"\"\"\n Call the registered function and return its results.\n\n Args:\n name (str): the name that identifies a dataset, e... | [
"function_empty",
"Development"
] | [
"detectron2.data.catalog._DatasetCatalog.get",
"detectron2.data.datasets.coco.convert_to_coco_dict"
] | Python | 1 | 2 | {
"total_num": 3,
"base_passed_num": 1
} |
[
"UniRef.detectron2.utils.registry.locate",
"UniRef.detectron2.utils.registry._convert_target_to_string"
] | UniRef | [
"detectron2/utils/registry.py",
"detectron2/utils/registry.py"
] | [
"tests/test_registry.py"
] | [
{
"class_start_lineno": 1,
"class_end_lineno": 60,
"func_start_lineno": 40,
"func_end_lineno": 60,
"func_code": "def locate(name: str) -> Any:\n \"\"\"\n Locate and return an object ``x`` using an input string ``{x.__module__}.{x.__qualname__}``,\n such as \"module.submodule.class_name\... | [
"Development"
] | [
"detectron2.utils.registry.locate",
"detectron2.utils.registry._convert_target_to_string"
] | Python | 0 | 2 | {
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"skfolio.datasets._base.download_dataset",
"skfolio.datasets._base.load_nasdaq_dataset"
] | Python | 5 | 5 | {
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[
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] | d3rlpy | [
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"d3rlpy/models/encoders.py",
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] | [
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] | [
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"func_code": " def __call__(self, episode: EpisodeBase, index: int) -> Transition:\n _validate_index(episode, index)\n\n observation = retrieve_observation(episode.observations, i... | [
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] | [
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"d3rlpy.models.encoders.DefaultEncoderFactory.create",
"d3rlpy.models.builders.create_discrete_q_function"
] | Python | 0 | 4 | {
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} |
[
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"d3rlpy.d3rlpy.models.builders.create_discrete_q_function",
"d3rlpy.d3rlpy.models.encoders.DefaultEncoderFactory::create_with_action",
"d3rlpy.d3rlpy.models.builders.create_continuous_q_function"
] | d3rlpy | [
"d3rlpy/models/encoders.py",
"d3rlpy/models/builders.py",
"d3rlpy/models/encoders.py",
"d3rlpy/models/builders.py"
] | [
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] | [
{
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"func_code": " def create(self, observation_shape: Shape) -> Encoder:\n factory: Union[PixelEncoderFactory, VectorEncoderFactory]\n if len(observation_shape) == 3:\n ... | [
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] | [
"d3rlpy.models.encoders.DefaultEncoderFactory.create",
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"d3rlpy.models.encoders.DefaultEncoderFactory.create_with_action",
"d3rlpy.models.builders.create_continuous_q_function"
] | Python | 0 | 4 | {
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} |
[
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"d3rlpy.d3rlpy.models.torch.q_functions.ensemble_q_function._reduce_quantile_ensemble",
"d3rlpy.d3rlpy.models.torch.q_functions.mean_q_function.DiscreteMeanQFunctionForwarder::compute_error",
"d3rlpy.d3rlpy.models.torch... | d3rlpy | [
"d3rlpy/models/torch/q_functions/ensemble_q_function.py",
"d3rlpy/models/torch/q_functions/ensemble_q_function.py",
"d3rlpy/models/torch/q_functions/mean_q_function.py",
"d3rlpy/models/torch/q_functions/ensemble_q_function.py",
"d3rlpy/models/torch/q_functions/ensemble_q_function.py"
] | [
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] | [
{
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"BugFix"
] | [
"d3rlpy.models.torch.q_functions.ensemble_q_function._gather_quantiles_by_indices",
"d3rlpy.models.torch.q_functions.ensemble_q_function._reduce_quantile_ensemble",
"d3rlpy.models.torch.q_functions.mean_q_function.DiscreteMeanQFunctionForwarder.compute_error",
"d3rlpy.models.torch.q_functions.ensemble_q_funct... | Python | 0 | 4 | {
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} |
[
"d3rlpy.d3rlpy.dataset.transition_pickers.BasicTransitionPicker::__call__",
"d3rlpy.d3rlpy.preprocessing.reward_scalers.MinMaxRewardScaler::fit_with_transition_picker"
] | d3rlpy | [
"d3rlpy/dataset/transition_pickers.py",
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] | [
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] | [
{
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"func_code": " def __call__(self, episode: EpisodeBase, index: int) -> Transition:\n _validate_index(episode, index)\n\n observation = retrieve_observation(episode.observations, i... | [
"BugFix"
] | [
"d3rlpy.dataset.transition_pickers.BasicTransitionPicker.__call__",
"d3rlpy.preprocessing.reward_scalers.MinMaxRewardScaler.fit_with_transition_picker"
] | Python | 0 | 2 | {
"total_num": 15,
"base_passed_num": 12
} |
[
"datachain.src.datachain.lib.file.File::ensure_cached",
"datachain.src.datachain.lib.file.File::open",
"datachain.src.datachain.lib.file.File::_symlink_to"
] | datachain | [
"datachain/lib/file.py",
"datachain/lib/file.py",
"datachain/lib/file.py"
] | [
"tests/unit/lib/test_file.py"
] | [
{
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"func_code": " def ensure_cached(self) -> None:\n if self._catalog is None:\n raise RuntimeError(\n \"cannot download file to cache because catalog is not s... | [
"BugFix"
] | [
"datachain.lib.file.File.ensure_cached",
"datachain.lib.file.File.open",
"datachain.lib.file.File._symlink_to"
] | Python | 0 | 3 | {
"total_num": 33,
"base_passed_num": 0
} |
[
"datachain.src.datachain.lib.signal_schema.SignalSchema::_get_flat_tree",
"datachain.src.datachain.lib.signal_schema.SignalSchema::get_column_type",
"datachain.src.datachain.lib.signal_schema.SignalSchema::mutate"
] | datachain | [
"datachain/lib/signal_schema.py",
"datachain/lib/signal_schema.py",
"datachain/lib/signal_schema.py"
] | [
"tests/unit/lib/test_signal_schema.py"
] | [
{
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] | [
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"datachain.lib.signal_schema.SignalSchema.get_column_type",
"datachain.lib.signal_schema.SignalSchema.mutate"
] | Python | 0 | 3 | {
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"base_passed_num": 56
} |
[
"datachain.src.datachain.lib.webdataset.Builder::add",
"datachain.src.datachain.lib.webdataset.get_tar_groups"
] | datachain | [
"datachain/lib/webdataset.py",
"datachain/lib/webdataset.py"
] | [
"tests/unit/lib/test_webdataset.py"
] | [
{
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"func_code": " def add(self, file: tarfile.TarInfo):\n fstream = File(path=file.name)\n ext = fstream.get_file_ext()\n stem = fstream.get_file_stem()\n\n if self... | [
"BugFix"
] | [
"datachain.lib.webdataset.Builder.add",
"datachain.lib.webdataset.get_tar_groups"
] | Python | 0 | 2 | {
"total_num": 7,
"base_passed_num": 3
} |
[
"haystack.haystack.utils.auth.EnvVarSecret::resolve_value",
"haystack.haystack.components.rankers.transformers_similarity.TransformersSimilarityRanker::warm_up"
] | haystack | [
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] | [
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] | [
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"func_code": " def resolve_value(self) -> Optional[Any]:\n \"\"\"Resolve the secret to an atomic value. The semantics of the value is secret-dependent.\"\"\"\n out = None\n ... | [
"BugFix"
] | [
"haystack.utils.auth.EnvVarSecret.resolve_value",
"haystack.components.rankers.transformers_similarity.TransformersSimilarityRanker.warm_up"
] | Python | 0 | 2 | {
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} |
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] | transformers | [
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] | [
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] | [
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"BugFix"
] | [
"transformers.models.llava_next.image_processing_llava_next.LlavaNextImageProcessor.pad",
"transformers.models.llava_next.image_processing_llava_next.LlavaNextImageProcessor._pad_for_patching"
] | Python | 0 | 2 | {
"total_num": 13,
"base_passed_num": 0
} |
[
"langchain.libs.langchain.langchain.agents.agent.AgentExecutor::_perform_agent_action",
"langchain.libs.langchain.langchain.agents.agent_iterator.AgentExecutorIterator::__iter__"
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] | [
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"langchain.agents.agent.AgentExecutor._iter_next_step",
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] | Python | 0 | 2 | {
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} |
[
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] | cloudnetpy | [
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] | [
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] | Python | 2 | 2 | {
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} |
[
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] | cloudnetpy | [
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] | [
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"tests/unit/test_mrr.py",
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{
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} |
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] | cloudnetpy | [
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] | [
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] | [
{
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] | Python | 2 | 4 | {
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} |
[
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"cloudnetpy.concat_lib.concatenate_files",
"cloudnetpy.concat_lib._Concat._write_initial_data",
"cloudnetpy.concat_lib._Concat.concat_data"
] | Python | 2 | 4 | {
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} |
[
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] | cloudnetpy | [
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} |
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} |
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] | cloudnetpy | [
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{
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] | Python | 2 | 4 | {
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} |
[
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] | cloudnetpy | [
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] | [
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] | Python | 1 | 2 | {
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} |
[
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] | cloudnetpy | [
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] | [
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} |
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] | Python | 1 | 3 | {
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} |
[
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"cloudnetpy.cloudnetpy.categ... | cloudnetpy | [
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"cloudnetpy/categorize/atmos_utils.py",
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"cloudnetpy.categorize.atmos_utils.calc_mixing_ratio",
"cloudnetpy.categorize.atmos_ut... | Python | 3 | 5 | {
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} |
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] | cloudnetpy | [
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] | Python | 1 | 4 | {
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} |
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] | Python | 2 | 3 | {
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} |
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] | cloudnetpy | [
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} |
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] | cloudnetpy | [
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} |
[
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] | [
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] | Python | 0 | 2 | {
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} |
[
"datachain.src.datachain.catalog.loader.get_metastore",
"datachain.src.datachain.catalog.loader.get_catalog"
] | datachain | [
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} |
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"datachain/func/func.py",
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{
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] | Python | 0 | 5 | {
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} |
[
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"datachain/lib/signal_schema.py",
"datachain/lib/convert/python_to_sql.py",
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] | [
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] | [
{
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"datachain.lib.convert.python_to_sql.python_to_sql",
"datachain.lib.signal_schema.SignalSchema.db_signals"
] | Python | 1 | 3 | {
"total_num": 32,
"base_passed_num": 31
} |
[
"datachain.src.datachain.lib.image.convert_image",
"datachain.src.datachain.lib.image.convert_images"
] | datachain | [
"datachain/lib/image.py",
"datachain/lib/image.py"
] | [
"tests/unit/lib/test_clip.py",
"tests/unit/lib/test_image.py"
] | [
{
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"func_code": "def convert_image(\n img: Image.Image,\n mode: str = \"RGB\",\n size: Optional[tuple[int, int]] = None,\n transform: Optional[Callable] = None,\n encoder: Optional[Calla... | [
"function_empty",
"TDD"
] | [
"datachain.lib.image.convert_image",
"datachain.lib.image.convert_images"
] | Python | 1 | 2 | {
"total_num": 41,
"base_passed_num": 13
} |
[
"datachain.src.datachain.lib.file.File::get_destination_path",
"datachain.src.datachain.lib.file.File::export"
] | datachain | [
"datachain/lib/file.py",
"datachain/lib/file.py"
] | [
"tests/unit/lib/test_file.py"
] | [
{
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"func_code": " def get_destination_path(self, output: str, placement: ExportPlacement) -> str:\n \"\"\"\n Returns full destination path of a file for exporting to some output\... | [
"function_empty"
] | [
"datachain.lib.file.File.get_destination_path",
"datachain.lib.file.File.export"
] | Python | 2 | 2 | {
"total_num": 33,
"base_passed_num": 25
} |
[
"datachain.src.datachain.lib.signal_schema.SignalSchema::_get_flat_tree",
"datachain.src.datachain.lib.convert.python_to_sql.python_to_sql",
"datachain.src.datachain.lib.signal_schema.SignalSchema::to_udf_spec",
"datachain.src.datachain.lib.signal_schema.SignalSchema::db_signals"
] | datachain | [
"datachain/lib/signal_schema.py",
"datachain/lib/signal_schema.py",
"datachain/lib/convert/python_to_sql.py",
"datachain/lib/signal_schema.py",
"datachain/lib/signal_schema.py"
] | [
"tests/unit/lib/test_signal_schema.py"
] | [
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"func_code": " def _get_flat_tree(\n self, tree: dict, prefix: list[str], depth: int\n ) -> Iterator[tuple[list[str], DataType, bool, int]]:\n for name, (type_, substree) i... | [
"function_empty",
"TDD"
] | [
"datachain.lib.signal_schema.SignalSchema._get_flat_tree",
"datachain.lib.signal_schema.SignalSchema.get_flat_tree",
"datachain.lib.convert.python_to_sql.python_to_sql",
"datachain.lib.signal_schema.SignalSchema.to_udf_spec",
"datachain.lib.signal_schema.SignalSchema.db_signals"
] | Python | 1 | 4 | {
"total_num": 58,
"base_passed_num": 47
} |
[
"datachain.src.datachain.func.func.Func::get_result_type",
"datachain.src.datachain.lib.convert.python_to_sql.python_to_sql",
"datachain.src.datachain.func.func.Func::get_column"
] | datachain | [
"datachain/func/func.py",
"datachain/lib/convert/python_to_sql.py",
"datachain/func/func.py",
"datachain/sql/selectable.py"
] | [
"tests/unit/sql/test_array.py"
] | [
{
"class_start_lineno": 29,
"class_end_lineno": 422,
"func_start_lineno": 361,
"func_end_lineno": 373,
"func_code": " def get_result_type(\n self, signals_schema: Optional[\"SignalSchema\"] = None\n ) -> \"DataType\":\n if self.result_type:\n return self.result_typ... | [
"TDD"
] | [
"datachain.func.func.Func.get_result_type",
"datachain.lib.convert.python_to_sql.python_to_sql",
"datachain.func.func.Func.get_column",
"datachain.sql.selectable.process_column_expression"
] | Python | 0 | 3 | {
"total_num": 12,
"base_passed_num": 0
} |
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