language stringclasses 1
value | repo stringclasses 346
values | path stringlengths 6 201 | class_span dict | source stringlengths 21 2.38M | target stringlengths 1 96 |
|---|---|---|---|---|---|
python | apache__airflow | providers/amazon/tests/unit/amazon/aws/sensors/test_step_function.py | {
"start": 1345,
"end": 3801
} | class ____:
def test_init(self):
sensor = StepFunctionExecutionSensor(
task_id=TASK_ID,
execution_arn=EXECUTION_ARN,
aws_conn_id=AWS_CONN_ID,
region_name=REGION_NAME,
verify=True,
botocore_config={"read_timeout": 42},
)
... | TestStepFunctionExecutionSensor |
python | encode__django-rest-framework | tests/schemas/test_openapi.py | {
"start": 39907,
"end": 47853
} | class ____(TestCase):
def test_override_settings(self):
assert isinstance(views.ExampleListView.schema, AutoSchema)
def test_paths_construction(self):
"""Construction of the `paths` key."""
patterns = [
path('example/', views.ExampleListView.as_view()),
]
ge... | TestGenerator |
python | ray-project__ray | release/ray_release/exception.py | {
"start": 2800,
"end": 2900
} | class ____(EnvironmentSetupError):
exit_code = ExitCode.REMOTE_ENV_SETUP_ERROR
| RemoteEnvSetupError |
python | pytorch__pytorch | test/jit/test_list_dict.py | {
"start": 73253,
"end": 80819
} | class ____(JitTestCase):
"""
This class contains a suite of tests for torch.jit.script, a
function that returns a dictionary-like object that has reference
semantics across the Python/TorchScript boundary. That is,
it can be passed to a TorchScript function that mutates it
and those modification... | TestScriptDict |
python | wandb__wandb | wandb/apis/importers/internals/internal.py | {
"start": 1981,
"end": 12887
} | class ____:
run: ImporterRun
interface: InterfaceQueue = InterfaceQueue()
@property
def run_dir(self) -> str:
p = Path(f"{ROOT_DIR}/{self.run.run_id()}/wandb")
p.mkdir(parents=True, exist_ok=True)
return f"{ROOT_DIR}/{self.run.run_id()}"
def make_artifacts_only_records(
... | RecordMaker |
python | automl__auto-sklearn | autosklearn/pipeline/components/regression/decision_tree.py | {
"start": 566,
"end": 4904
} | class ____(AutoSklearnRegressionAlgorithm):
def __init__(
self,
criterion,
max_features,
max_depth_factor,
min_samples_split,
min_samples_leaf,
min_weight_fraction_leaf,
max_leaf_nodes,
min_impurity_decrease,
random_state=None,
):
... | DecisionTree |
python | qdrant__qdrant-client | qdrant_client/local/sparse_distances.py | {
"start": 1549,
"end": 1864
} | class ____:
def __init__(self, positive: SparseVector, negative: SparseVector):
validate_sparse_vector(positive)
validate_sparse_vector(negative)
self.positive: SparseVector = sort_sparse_vector(positive)
self.negative: SparseVector = sort_sparse_vector(negative)
| SparseContextPair |
python | modin-project__modin | asv_bench/benchmarks/benchmarks.py | {
"start": 20381,
"end": 22288
} | class ____:
param_names = ["shape", "indexer_type"]
params = [
get_benchmark_shapes("TimeIndexing"),
[
"bool_array",
"bool_series",
"scalar",
"slice",
"continuous_slice",
"numpy_array_take_all_values",
"python_li... | TimeIndexing |
python | sqlalchemy__sqlalchemy | lib/sqlalchemy/dialects/mssql/json.py | {
"start": 4182,
"end": 4431
} | class ____(_FormatTypeMixin, sqltypes.JSON.JSONIndexType):
def _format_value(self, value):
if isinstance(value, int):
value = "$[%s]" % value
else:
value = '$."%s"' % value
return value
| JSONIndexType |
python | getsentry__sentry | src/sentry/features/base.py | {
"start": 1224,
"end": 1482
} | class ____(Feature):
def __init__(self, name: str, organization: Organization) -> None:
super().__init__(name)
self.organization = organization
def get_subject(self) -> Organization:
return self.organization
| OrganizationFeature |
python | kubernetes-client__python | kubernetes/client/models/v1_replication_controller_list.py | {
"start": 383,
"end": 7334
} | class ____(object):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
"""
"""
Attributes:
openapi_types (dict): The key is attribute name
and the value is attribute type.
attri... | V1ReplicationControllerList |
python | PyCQA__pylint | tests/functional/r/regression_02/regression_5244.py | {
"start": 205,
"end": 332
} | class ____:
def some_func(self):
return lambda: 42
def __len__(self):
return len(self.some_func())
| MyClass |
python | run-llama__llama_index | llama-index-core/llama_index/core/memory/types.py | {
"start": 442,
"end": 2412
} | class ____(BaseComponent):
"""Base class for all memory types."""
@classmethod
def class_name(cls) -> str:
"""Get class name."""
return "BaseMemory"
@classmethod
@abstractmethod
def from_defaults(
cls,
**kwargs: Any,
) -> "BaseMemory":
"""Create a ch... | BaseMemory |
python | Netflix__metaflow | metaflow/plugins/argo/argo_workflows.py | {
"start": 215846,
"end": 216776
} | class ____(object):
# https://github.com/argoproj/argo-events/blob/master/api/sensor.md#argoproj.io/v1alpha1.ArgoWorkflowTrigger
def __init__(self):
tree = lambda: defaultdict(tree)
self.payload = tree()
self.payload["operation"] = "submit"
self.payload["group"] = "argoproj.io"
... | ArgoWorkflowTrigger |
python | allegroai__clearml | examples/frameworks/pytorch/pytorch_tensorboard.py | {
"start": 409,
"end": 6227
} | class ____(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.conv1 = nn.Conv2d(1, 10, kernel_size=5)
self.conv2 = nn.Conv2d(10, 20, kernel_size=5)
self.conv2_drop = nn.Dropout2d()
self.fc1 = nn.Linear(320, 50)
self.fc2 = nn.Linear(50, 10)
def forw... | Net |
python | django__django | tests/bash_completion/management/commands/test_command.py | {
"start": 54,
"end": 258
} | class ____(BaseCommand):
def add_arguments(self, parser):
parser.add_argument("--list", action="store_true", help="Print all options")
def handle(self, *args, **options):
pass
| Command |
python | sympy__sympy | sympy/stats/rv.py | {
"start": 6285,
"end": 8632
} | class ____(Expr):
"""
Random Symbols represent ProbabilitySpaces in SymPy Expressions.
In principle they can take on any value that their symbol can take on
within the associated PSpace with probability determined by the PSpace
Density.
Explanation
===========
Random Symbols contain ps... | RandomSymbol |
python | tensorflow__tensorflow | tensorflow/python/data/experimental/kernel_tests/service/cross_trainer_cache_test.py | {
"start": 1237,
"end": 19200
} | class ____(data_service_test_base.TestBase,
parameterized.TestCase):
"""Tests for sharing datasets across jobs using a cross-trainer cache."""
@combinations.generate(test_base.default_test_combinations())
def testEnableCrossTrainerCache(self):
"""Tests cross-trainer cache with `di... | CrossTrainerCacheTest |
python | mlflow__mlflow | mlflow/utils/autologging_utils/logging_and_warnings.py | {
"start": 237,
"end": 8120
} | class ____:
"""
Provides threadsafe utilities to modify warning behavior for MLflow autologging, including:
- Global disablement of MLflow warnings across all threads
- Global rerouting of MLflow warnings to an MLflow event logger (i.e. `logger.warning()`)
across all threads
- Disablement of ... | _WarningsController |
python | huggingface__transformers | src/transformers/models/nllb_moe/modeling_nllb_moe.py | {
"start": 33148,
"end": 38252
} | class ____(NllbMoePreTrainedModel):
"""
Transformer decoder consisting of *config.decoder_layers* layers. Each layer is a [`NllbMoeDecoderLayer`]
Args:
config:
NllbMoeConfig
embed_tokens (nn.Embedding):
output embedding
"""
_can_record_outputs = {
"h... | NllbMoeDecoder |
python | huggingface__transformers | src/transformers/models/funnel/modeling_funnel.py | {
"start": 22520,
"end": 23318
} | class ____(nn.Module):
def __init__(self, config: FunnelConfig) -> None:
super().__init__()
self.linear_1 = nn.Linear(config.d_model, config.d_inner)
self.activation_function = ACT2FN[config.hidden_act]
self.activation_dropout = nn.Dropout(config.activation_dropout)
self.line... | FunnelPositionwiseFFN |
python | pydata__xarray | xarray/tests/arrays.py | {
"start": 373,
"end": 901
} | class ____(utils.NDArrayMixin, ExplicitlyIndexed):
"""Disallows any loading."""
def __init__(self, array):
self.array = array
def get_duck_array(self):
raise UnexpectedDataAccess("Tried accessing data")
def __array__(
self, dtype: np.typing.DTypeLike | None = None, /, *, copy:... | InaccessibleArray |
python | ansible__ansible | lib/ansible/config/manager.py | {
"start": 11980,
"end": 32459
} | class ____:
DEPRECATED = [] # type: list[tuple[str, dict[str, str]]]
WARNINGS = set() # type: set[str]
_errors: list[tuple[str, Exception]]
def __init__(self, conf_file=None, defs_file=None):
self._get_ini_config_value = functools.cache(self._get_ini_config_value)
self._base_defs =... | ConfigManager |
python | langchain-ai__langchain | libs/core/langchain_core/language_models/base.py | {
"start": 1117,
"end": 3072
} | class ____(TypedDict, total=False):
"""LangSmith parameters for tracing."""
ls_provider: str
"""Provider of the model."""
ls_model_name: str
"""Name of the model."""
ls_model_type: Literal["chat", "llm"]
"""Type of the model. Should be 'chat' or 'llm'."""
ls_temperature: float | None
... | LangSmithParams |
python | pytorch__pytorch | test/distributed/_shard/sharding_spec/test_sharding_spec.py | {
"start": 1251,
"end": 19870
} | class ____(TestCase):
@skip_but_pass_in_sandcastle_if(not TEST_MULTIGPU, "2 CUDA GPUs are needed")
def test_device_placement(self):
# valid devices
DevicePlacementSpec("cuda:0")
DevicePlacementSpec(torch.device(0))
DevicePlacementSpec(torch.device("cuda:0"))
DevicePlaceme... | TestShardingSpec |
python | pytorch__pytorch | test/distributed/_shard/sharded_tensor/test_sharded_tensor.py | {
"start": 85361,
"end": 120165
} | class ____(ShardedTensorTestBase):
@with_comms(init_rpc=False)
@skip_if_lt_x_gpu(4)
@requires_nccl()
def test_local_shards(self):
shard_offsets = [(self.rank // 2) * 5, (self.rank % 2) * 5]
local_shard_metadata = ShardMetadata(
shard_offsets=shard_offsets,
shard_s... | TestShardedTensorFromLocalShards |
python | pytorch__pytorch | test/test_nestedtensor.py | {
"start": 154252,
"end": 345832
} | class ____(NestedTensorTestCase):
# TODO: consolidate with the below
def _get_list_for_jagged_tensor(self, nested_size, device, requires_grad=True):
Ds = nested_size[1:]
out = []
for s in nested_size[0]:
out.append(
torch.randn(
s,
... | TestNestedTensorSubclass |
python | pypa__hatch | src/hatch/config/model.py | {
"start": 13575,
"end": 14338
} | class ____(LazilyParsedConfig):
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._field_location = FIELD_TO_PARSE
@property
def location(self):
if self._field_location is FIELD_TO_PARSE:
if "location" in self.raw_data:
location... | ProjectConfig |
python | numba__numba | numba/core/withcontexts.py | {
"start": 3980,
"end": 16343
} | class ____(WithContext):
"""Creates a contextmanager to be used inside jitted functions to enter
*object-mode* for using interpreter features. The body of the with-context
is lifted into a function that is compiled in *object-mode*. This
transformation process is limited and cannot process all possibl... | _ObjModeContextType |
python | tornadoweb__tornado | tornado/test/httpserver_test.py | {
"start": 44597,
"end": 45625
} | class ____(AsyncHTTPTestCase):
def get_app(self):
return Application([("/", HelloWorldRequestHandler)])
def get_httpserver_options(self):
return dict(max_header_size=1024)
def test_small_headers(self):
response = self.fetch("/", headers={"X-Filler": "a" * 100})
response.ret... | MaxHeaderSizeTest |
python | sqlalchemy__sqlalchemy | lib/sqlalchemy/testing/fixtures/mypy.py | {
"start": 710,
"end": 8786
} | class ____(TestBase):
__requires__ = ("no_sqlalchemy2_stubs",)
@config.fixture(scope="function")
def per_func_cachedir(self):
yield from self._cachedir()
@config.fixture(scope="class")
def cachedir(self):
yield from self._cachedir()
def _cachedir(self):
# as of mypy 0.... | MypyTest |
python | tqdm__tqdm | tqdm/contrib/telegram.py | {
"start": 2815,
"end": 5008
} | class ____(tqdm_auto):
"""
Standard `tqdm.auto.tqdm` but also sends updates to a Telegram Bot.
May take a few seconds to create (`__init__`).
- create a bot <https://core.telegram.org/bots#6-botfather>
- copy its `{token}`
- add the bot to a chat and send it a message such as `/start`
- go ... | tqdm_telegram |
python | scrapy__scrapy | scrapy/utils/request.py | {
"start": 3595,
"end": 3701
} | class ____(Protocol):
def fingerprint(self, request: Request) -> bytes: ...
| RequestFingerprinterProtocol |
python | lazyprogrammer__machine_learning_examples | unsupervised_class3/autoencoder_theano.py | {
"start": 427,
"end": 2942
} | class ____:
def __init__(self, D, M):
# represents a batch of training data
self.X = T.matrix('X')
# input -> hidden
self.W = theano.shared(np.random.randn(D, M) * np.sqrt(2.0 / M))
self.b = theano.shared(np.zeros(M))
# hidden -> output
self.V = theano.shared(np.random.randn(M, D) * np.s... | Autoencoder |
python | airbytehq__airbyte | airbyte-integrations/connectors/source-appsflyer/source_appsflyer/source.py | {
"start": 11306,
"end": 11636
} | class ____(RawDataMixin, IncrementalAppsflyerStream):
cursor_field = "install_time"
def path(
self, stream_state: Mapping[str, Any] = None, stream_slice: Mapping[str, Any] = None, next_page_token: Mapping[str, Any] = None
) -> str:
return f"raw-data/export/app/{self.app_id}/installs_report/... | Installs |
python | PrefectHQ__prefect | src/prefect/logging/highlighters.py | {
"start": 86,
"end": 413
} | class ____(RegexHighlighter):
"""Apply style to log levels."""
base_style = "level."
highlights: list[str] = [
r"(?P<debug_level>DEBUG)",
r"(?P<info_level>INFO)",
r"(?P<warning_level>WARNING)",
r"(?P<error_level>ERROR)",
r"(?P<critical_level>CRITICAL)",
]
| LevelHighlighter |
python | google__jax | tests/source_mapper_test.py | {
"start": 4508,
"end": 5335
} | class ____(jtu.JaxTestCase):
def test_hlo_parser(self):
source_map = hlo._parse_hlo_new_format(HLO_EXAMPLE.split("\n"))
print(source_map)
self.assertLen(source_map.sources, 1)
self.assertEqual(source_map.sources[0], "<embedded module>")
mappings = source_map.mappings
constant_line_idx = -1
... | HLOParserTest |
python | ray-project__ray | python/ray/tests/accelerators/mock_dpctl_2.py | {
"start": 124,
"end": 271
} | class ____:
def __init__(self, info):
pass
@property
def name(self):
return "Intel(R) Data Center GPU Max 1100"
| SyclDevice |
python | paramiko__paramiko | tests/test_transport.py | {
"start": 38416,
"end": 38834
} | class ____(TransportTest):
_auth_handler_class = AuthOnlyHandler
def setUp(self):
# Copypasta (Transport init is load-bearing)
self.socks = LoopSocket()
self.sockc = LoopSocket()
self.sockc.link(self.socks)
# New class who dis
self.tc = ServiceRequestingTransport... | ServiceRequestingTransportTest |
python | PyCQA__pylint | tests/functional/r/regression_02/regression_5408.py | {
"start": 309,
"end": 360
} | class ____:
inner_class = MyInnerClass
| MySubClass |
python | pypa__pip | src/pip/_internal/distributions/base.py | {
"start": 274,
"end": 1830
} | class ____(metaclass=abc.ABCMeta):
"""A base class for handling installable artifacts.
The requirements for anything installable are as follows:
- we must be able to determine the requirement name
(or we can't correctly handle the non-upgrade case).
- for packages with setup requirements, we... | AbstractDistribution |
python | dask__dask | dask/_task_spec.py | {
"start": 10780,
"end": 15069
} | class ____:
key: KeyType
_dependencies: frozenset
__slots__ = tuple(__annotations__)
def ref(self):
return Alias(self.key)
def copy(self):
raise NotImplementedError
@property
def data_producer(self) -> bool:
return False
@property
def dependencies(self) -... | GraphNode |
python | allegroai__clearml | clearml/backend_api/services/v2_23/workers.py | {
"start": 26542,
"end": 29519
} | class ____(NonStrictDataModel):
"""
:param id: Worker ID
:type id: str
:param name: Worker name
:type name: str
:param running_time: Task running time
:type running_time: int
:param last_iteration: Last task iteration
:type last_iteration: int
"""
_schema = {
"proper... | CurrentTaskEntry |
python | marshmallow-code__marshmallow | tests/test_decorators.py | {
"start": 3917,
"end": 7876
} | class ____:
def test_pass_original_single(self):
class MySchema(Schema):
foo = fields.Raw()
@post_load(pass_original=True)
def post_load(self, data, original_data, **kwargs):
ret = data.copy()
ret["_post_load"] = original_data["sentinel"]
... | TestPassOriginal |
python | spack__spack | lib/spack/spack/vendor/jinja2/nodes.py | {
"start": 25066,
"end": 25654
} | class ____(Expr):
"""Get an attribute or item from an expression and prefer the item."""
fields = ("node", "arg", "ctx")
node: Expr
arg: Expr
ctx: str
def as_const(self, eval_ctx: t.Optional[EvalContext] = None) -> t.Any:
if self.ctx != "load":
raise Impossible()
e... | Getitem |
python | bokeh__bokeh | src/bokeh/models/glyph.py | {
"start": 3013,
"end": 3317
} | class ____(XYGlyph):
''' Base class of glyphs with `x` and `y` coordinate attributes and
a connected topology.
'''
# explicit __init__ to support Init signatures
def __init__(self, *args: Any, **kwargs: Any) -> None:
super().__init__(*args, **kwargs)
@abstract
| ConnectedXYGlyph |
python | astropy__astropy | astropy/coordinates/tests/test_representation_methods.py | {
"start": 12187,
"end": 16795
} | class ____(ShapeSetup):
def test_broadcast_to(self):
s0_broadcast = np.broadcast_to(self.s0, (3, 6, 7))
s0_diff = s0_broadcast.differentials["s"]
assert type(s0_broadcast) is type(self.s0)
assert s0_broadcast.shape == (3, 6, 7)
assert s0_diff.shape == s0_broadcast.shape
... | TestShapeFunctions |
python | Netflix__metaflow | metaflow/plugins/pypi/pip.py | {
"start": 709,
"end": 1538
} | class ____(Exception):
"Wrapper for pip package resolve errors."
def __init__(self, error):
self.error = error
try:
# Parse the package spec from error message:
# ERROR: ERROR: Could not find a version that satisfies the requirement pkg==0.0.1 (from versions: none)
... | PipPackageNotFound |
python | neetcode-gh__leetcode | python/0707-design-linked-list.py | {
"start": 119,
"end": 1863
} | class ____:
def __init__(self):
self.left = ListNode(0)
self.right = ListNode(0)
self.left.next = self.right
self.right.prev = self.left
def get(self, index: int) -> int:
cur = self.left.next
while cur and index > 0:
cur = cur.next
index ... | MyLinkedList |
python | MTrajK__coding-problems | Other/running_median.py | {
"start": 573,
"end": 2859
} | class ____:
def __init__(self, is_min=True):
self.data = []
self.is_min = is_min
def push(self, el):
if not self.is_min:
el = -el
heapq.heappush(self.data, el)
def pop(self):
el = heapq.heappop(self.data)
if not self.is_min:
el = -el
... | PriorityQueue |
python | eth-brownie__brownie | brownie/_gui/console.py | {
"start": 107,
"end": 420
} | class ____(ToggleButton):
def __init__(self, parent):
super().__init__(parent, "Console", "c")
self.console = self.root.main.console
def toggle_on(self):
self.console.config(height=3)
return True
def toggle_off(self):
self.console.config(height=1)
| ConsoleButton |
python | pytorch__pytorch | torchgen/api/types/types.py | {
"start": 4746,
"end": 5082
} | class ____(CType):
elem: CType
def cpp_type(self, *, strip_ref: bool = False) -> str:
# Do not pass `strip_ref` recursively.
return f"::std::optional<{self.elem.cpp_type()}>"
def remove_const_ref(self) -> CType:
return OptionalCType(self.elem.remove_const_ref())
@dataclass(frozen... | OptionalCType |
python | ray-project__ray | python/ray/train/examples/pytorch/torch_data_prefetch_benchmark/auto_pipeline_for_host_to_device_data_transfer.py | {
"start": 239,
"end": 621
} | class ____(nn.Module):
def __init__(self, in_d, hidden):
# output dim = 1
super(Net, self).__init__()
dims = [in_d] + hidden + [1]
self.layers = nn.ModuleList(
[nn.Linear(dims[i - 1], dims[i]) for i in range(len(dims))]
)
def forward(self, x):
for lay... | Net |
python | openai__openai-python | src/openai/types/audio/transcription.py | {
"start": 872,
"end": 1373
} | class ____(BaseModel):
input_tokens: int
"""Number of input tokens billed for this request."""
output_tokens: int
"""Number of output tokens generated."""
total_tokens: int
"""Total number of tokens used (input + output)."""
type: Literal["tokens"]
"""The type of the usage object. Alw... | UsageTokens |
python | tensorflow__tensorflow | third_party/xla/xla/backends/cpu/testlib/elemental_kernel_emitter_test.py | {
"start": 6971,
"end": 8863
} | class ____(parameterized.TestCase):
def test_elemental_comparision_kernel_emitter(self, op_def, shape, dtype):
[direction, np_op] = op_def
is_unsigned = np.issubdtype(dtype, np.unsignedinteger)
value_range = (0.0, 20.0) if is_unsigned else (-10.0, 10.0)
lhs_np = create_input(value_range, shape, dtyp... | ElementalComparisonKernelRunnerTest |
python | microsoft__pyright | packages/pyright-internal/src/tests/samples/typeVarDefaultClass3.py | {
"start": 1432,
"end": 1481
} | class ____[T1 = str, T4 = dict[T1, T2]]: ...
| ClassJ |
python | pytorch__pytorch | torch/ao/nn/quantized/modules/conv.py | {
"start": 16624,
"end": 21181
} | class ____(_ConvNd):
r"""Applies a 2D convolution over a quantized input signal composed of
several quantized input planes.
For details on input arguments, parameters, and implementation see
:class:`~torch.nn.Conv2d`.
.. note::
Only `zeros` is supported for the :attr:`padding_mode` argumen... | Conv2d |
python | html5lib__html5lib-python | html5lib/html5parser.py | {
"start": 2188,
"end": 14726
} | class ____(object):
"""HTML parser
Generates a tree structure from a stream of (possibly malformed) HTML.
"""
def __init__(self, tree=None, strict=False, namespaceHTMLElements=True, debug=False):
"""
:arg tree: a treebuilder class controlling the type of tree that will be
... | HTMLParser |
python | django__django | tests/admin_views/test_autocomplete_view.py | {
"start": 2061,
"end": 14744
} | class ____(AdminViewBasicTestCase):
as_view_args = {"admin_site": site}
opts = {
"app_label": Answer._meta.app_label,
"model_name": Answer._meta.model_name,
"field_name": "question",
}
factory = RequestFactory()
url = reverse_lazy("autocomplete_admin:autocomplete")
@clas... | AutocompleteJsonViewTests |
python | getsentry__sentry | src/flagpole/__init__.py | {
"start": 1999,
"end": 2334
} | class ____(Exception):
pass
@functools.cache
def load_json_schema() -> dict[str, Any]:
path = os.path.join(os.path.dirname(__file__), "flagpole-schema.json")
with open(path, "rb") as json_file:
data = orjson.loads(json_file.read())
return data
@dataclasses.dataclass(frozen=True)
| InvalidFeatureFlagConfiguration |
python | langchain-ai__langchain | libs/core/langchain_core/prompts/structured.py | {
"start": 715,
"end": 6005
} | class ____(ChatPromptTemplate):
"""Structured prompt template for a language model."""
schema_: dict | type
"""Schema for the structured prompt."""
structured_output_kwargs: dict[str, Any] = Field(default_factory=dict)
def __init__(
self,
messages: Sequence[MessageLikeRepresentatio... | StructuredPrompt |
python | getsentry__sentry | src/sentry/api/bases/organization.py | {
"start": 7098,
"end": 7311
} | class ____(OrganizationPermission):
scope_map = {
"GET": ["event:read", "event:write", "event:admin"],
"POST": ["event:read", "event:write", "event:admin"],
}
| OrganizationDataExportPermission |
python | dagster-io__dagster | examples/docs_projects/project_ml/src/project_ml/defs/types.py | {
"start": 395,
"end": 577
} | class ____(TypedDict):
test_accuracy: float
predictions: list[int]
labels: list[int]
classification_report: dict[str, Any]
model_info: dict[str, str]
| EvaluationResult |
python | getsentry__sentry | tests/sentry/integrations/github_enterprise/test_webhooks.py | {
"start": 697,
"end": 11263
} | class ____(APITestCase):
def setUp(self) -> None:
self.url = "/extensions/github-enterprise/webhook/"
self.metadata = {
"url": "35.232.149.196",
"id": "2",
"name": "test-app",
"webhook_secret": "b3002c3e321d4b7880360d397db2ccfd",
"private_k... | WebhookTest |
python | pytorch__pytorch | torch/_inductor/fx_passes/overlap_scheduling.py | {
"start": 6035,
"end": 6456
} | class ____:
"""Track info about a collective operation"""
start_node: fx.Node
wait_node: fx.Node
size_bytes: int
estimated_time_ms: float
exposed_time_ms: float # How much of this collective is still exposed
hiding_nodes: OrderedSet[fx.Node] = field(default_factory=OrderedSet)
@proper... | CollectiveInfo |
python | huggingface__transformers | src/transformers/models/patchtst/modeling_patchtst.py | {
"start": 12001,
"end": 14051
} | class ____(nn.Module):
"""
A class to patchify the time series sequence into different patches
Returns:
`torch.Tensor` of shape `(batch_size, num_channels, num_patches, patch_length)`
"""
def __init__(self, config: PatchTSTConfig):
super().__init__()
self.sequence_length =... | PatchTSTPatchify |
python | Textualize__textual | docs/examples/guide/css/nesting02.py | {
"start": 122,
"end": 479
} | class ____(App):
"""App with nested CSS."""
CSS_PATH = "nesting02.tcss"
def compose(self) -> ComposeResult:
with Horizontal(id="questions"):
yield Static("Yes", classes="button affirmative")
yield Static("No", classes="button negative")
if __name__ == "__main__":
app ... | NestingDemo |
python | PyCQA__pylint | tests/functional/u/unpacking/unpacking_non_sequence_py37.py | {
"start": 373,
"end": 486
} | class ____:
function: Callable[..., tuple[int, int]]
def update(self):
_, _ = self.function()
| Metric |
python | realpython__materials | thread-safety-locks/bank_deadlock.py | {
"start": 81,
"end": 1213
} | class ____:
def __init__(self):
self.balance = 0
self.lock = threading.Lock()
def deposit(self, amount):
print(
f"Thread {threading.current_thread().name} waiting "
"to acquire lock for deposit()"
)
with self.lock:
print(
... | BankAccount |
python | pytorch__pytorch | torch/distributed/algorithms/ddp_comm_hooks/mixed_precision_hooks.py | {
"start": 218,
"end": 3254
} | class ____:
"""
State to manage DDP mixed precision in backward / gradient communication.
This contains a weakref to the DDP module for access to reducer and process
group, and a stream to run parameter and gradient upcasts.
"""
ddp_weakref: Any
upcast_stream: torch.Stream
wait_for_str... | _AllreduceUpcastHookState |
python | getsentry__sentry | src/sentry/models/groupreaction.py | {
"start": 522,
"end": 3205
} | class ____(DefaultFieldsModel):
"""
This model has no affiliation with PullRequestComment.reactions.
This model represents feedback/evaluations related to a Group or an entity associated with a Group.
This model supports multiple patterns based on NULL combinations:
Suspect Commit Reactions:
- ... | GroupReaction |
python | sympy__sympy | sympy/plotting/pygletplot/plot.py | {
"start": 891,
"end": 11354
} | class ____:
"""
Plot Examples
=============
See examples/advanced/pyglet_plotting.py for many more examples.
>>> from sympy.plotting.pygletplot import PygletPlot as Plot
>>> from sympy.abc import x, y, z
>>> Plot(x*y**3-y*x**3)
[0]: -x**3*y + x*y**3, 'mode=cartesian'
>>> p = Plot... | PygletPlot |
python | mlflow__mlflow | mlflow/webhooks/types.py | {
"start": 9245,
"end": 9922
} | class ____(TypedDict):
"""Payload sent when an alias is created for a prompt version.
Example payload:
.. code-block:: python
{
"name": "example_prompt",
"alias": "example_alias",
"version": "1",
}
"""
name: str
"""The name of the prompt."... | PromptAliasCreatedPayload |
python | nryoung__algorithms | algorithms/data_structures/queue.py | {
"start": 672,
"end": 1445
} | class ____:
def __init__(self):
self._queue = deque([])
def add(self, value):
"""
Add element as the last item in the Queue.
Worst Case Complexity: O(1)
"""
self._queue.append(value)
def remove(self):
"""
Remove element from the front of t... | Queue |
python | kamyu104__LeetCode-Solutions | Python/longest-fibonacci-subarray.py | {
"start": 37,
"end": 413
} | class ____(object):
def longestSubarray(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
result = cnt = 2
for i in xrange(2, len(nums)):
if nums[i] != nums[i-1]+nums[i-2]:
cnt = 2
continue
cnt += 1
... | Solution |
python | pytorch__pytorch | test/distributed/_composable/test_replicate_with_compiler.py | {
"start": 13679,
"end": 16131
} | class ____(InductorTestCase):
def setUp(self):
# Hmm, why a specific set_device call for rank 0?
self.rank = 0
self.world_size = 4
torch.get_device_module(device_type).set_device(device_type)
store = FakeStore()
dist.init_process_group(
backend="fake",
... | DDP_TP_Test |
python | huggingface__transformers | src/transformers/models/timm_wrapper/modeling_timm_wrapper.py | {
"start": 5645,
"end": 10641
} | class ____(TimmWrapperPreTrainedModel):
"""
Wrapper class for timm models to be used in transformers.
"""
def __init__(self, config: TimmWrapperConfig):
super().__init__(config)
# using num_classes=0 to avoid creating classification head
extra_init_kwargs = config.model_args or ... | TimmWrapperModel |
python | google__pytype | pytype/pytd/pytd.py | {
"start": 15072,
"end": 15193
} | class ____(Type):
"""A type we know nothing about yet (? in pytd)."""
def __bool__(self):
return True
| AnythingType |
python | openai__openai-python | src/openai/types/evals/create_eval_completions_run_data_source.py | {
"start": 1913,
"end": 3015
} | class ____(BaseModel):
type: Literal["stored_completions"]
"""The type of source. Always `stored_completions`."""
created_after: Optional[int] = None
"""An optional Unix timestamp to filter items created after this time."""
created_before: Optional[int] = None
"""An optional Unix timestamp to ... | SourceStoredCompletions |
python | pytorch__pytorch | torch/_inductor/codegen/cpp_gemm_template.py | {
"start": 25570,
"end": 73855
} | class ____(CppTemplate):
"""
GEMM Template for Inductor CPP Backend.
"""
def __init__(
self,
input_nodes,
layout: ir.Layout,
num_threads: int,
register_blocking: GemmBlocking,
beta=1,
alpha=1,
has_bias=False,
epilogue_creator: Opti... | CppGemmTemplate |
python | getsentry__sentry | src/sentry/conduit/auth.py | {
"start": 194,
"end": 2436
} | class ____(NamedTuple):
token: str
channel_id: str
url: str
def generate_channel_id() -> str:
"""Generate a unique channel ID for a Conduit stream."""
return str(uuid.uuid4())
def generate_conduit_token(
org_id: int,
channel_id: str,
issuer: str | None = None,
audience: str | Non... | ConduitCredentials |
python | walkccc__LeetCode | solutions/3393. Count Paths With the Given XOR Value/3393.py | {
"start": 0,
"end": 613
} | class ____:
def countPathsWithXorValue(self, grid: list[list[int]], k: int) -> int:
MOD = 1_000_000_007
m = len(grid)
n = len(grid[0])
@functools.lru_cache(None)
def count(i: int, j: int, xors: int) -> int:
"""
Return the number of paths from (i, j) to (m - 1, n - 1) with XOR value
... | Solution |
python | getsentry__sentry | tests/sentry/monitors/endpoints/test_organization_monitor_details.py | {
"start": 301,
"end": 430
} | class ____(BaseUpdateMonitorTest):
endpoint = "sentry-api-0-organization-monitor-details"
__test__ = True
| UpdateMonitorTest |
python | mozilla__bleach | bleach/_vendor/html5lib/serializer.py | {
"start": 15682,
"end": 15759
} | class ____(Exception):
"""Error in serialized tree"""
pass
| SerializeError |
python | django-extensions__django-extensions | tests/test_autoslug_fields.py | {
"start": 740,
"end": 8185
} | class ____(TestCase):
def tearDown(self):
super().tearDown()
SluggedTestModel.objects.all().delete()
CustomFuncSluggedTestModel.objects.all().delete()
CustomFuncPrecedenceSluggedTestModel.objects.all().delete()
def test_auto_create_slug(self):
m = SluggedTestModel(title... | AutoSlugFieldTest |
python | pennersr__django-allauth | allauth/socialaccount/providers/openid/migrations/0001_initial.py | {
"start": 43,
"end": 1643
} | class ____(migrations.Migration):
dependencies = []
operations = [
migrations.CreateModel(
name="OpenIDNonce",
fields=[
(
"id",
models.AutoField(
verbose_name="ID",
serialize=... | Migration |
python | scipy__scipy | scipy/sparse/linalg/_eigen/arpack/arpack.py | {
"start": 12741,
"end": 13029
} | class ____(RuntimeError):
"""
ARPACK error
"""
def __init__(self, info, infodict=None):
if infodict is None:
infodict = _NAUPD_ERRORS
msg = infodict.get(info, "Unknown error")
super().__init__(f"ARPACK error {info}: {msg}")
| ArpackError |
python | getsentry__sentry | src/sentry/notifications/notifications/organization_request/invite_request.py | {
"start": 373,
"end": 1447
} | class ____(AbstractInviteRequestNotification):
metrics_key = "invite_request"
template_path = "sentry/emails/organization-invite-request"
def get_specific_analytics_event(self, provider: ExternalProviders) -> analytics.Event | None:
"""
Returns the specific analytics event for the provider.... | InviteRequestNotification |
python | cherrypy__cherrypy | cherrypy/lib/sessions.py | {
"start": 16221,
"end": 22261
} | class ____(Session):
"""Implementation of the file backend for sessions.
storage_path
The folder where session data will be saved. Each session
will be saved as pickle.dump(data, expiration_time) in its own file;
the filename will be self.SESSION_PREFIX + self.id.
lock_timeout
... | FileSession |
python | wandb__wandb | tests/unit_tests/test_step_prepare.py | {
"start": 7170,
"end": 10537
} | class ____:
@staticmethod
def _bg_prepare(
step_prepare: StepPrepare, *args, **kwargs
) -> "concurrent.futures.Future[ResponsePrepare]":
"""Starts prepare running in the background."""
enqueued = threading.Event()
future = concurrent.futures.Future()
def prepare_and_... | TestStepPrepare |
python | huggingface__transformers | src/transformers/models/x_clip/modeling_x_clip.py | {
"start": 2100,
"end": 4250
} | class ____(ModelOutput):
r"""
loss (`torch.FloatTensor` of shape `(1,)`, *optional*, returned when `return_loss` is `True`):
Contrastive loss for video-text similarity.
logits_per_video (`torch.FloatTensor` of shape `(video_batch_size, text_batch_size)`):
The scaled dot product scores betwee... | XCLIPOutput |
python | astropy__astropy | astropy/nddata/__init__.py | {
"start": 838,
"end": 1551
} | class ____(_config.ConfigNamespace):
"""
Configuration parameters for `astropy.nddata`.
"""
warn_unsupported_correlated = _config.ConfigItem(
True,
"Whether to issue a warning if `~astropy.nddata.NDData` arithmetic "
"is performed with uncertainties and the uncertainties do not ... | Conf |
python | sanic-org__sanic | sanic/http/tls/creators.py | {
"start": 7907,
"end": 9542
} | class ____(CertCreator):
def check_supported(self) -> None:
if not TRUSTME_INSTALLED:
raise SanicException(
"Sanic is attempting to use trustme to generate local TLS "
"certificates since you did not supply a certificate, but "
"one is required. Sa... | TrustmeCreator |
python | apache__airflow | providers/google/src/airflow/providers/google/cloud/operators/vertex_ai/auto_ml.py | {
"start": 26661,
"end": 28896
} | class ____(GoogleCloudBaseOperator):
"""
List an AutoML training job.
Can be used with AutoMLForecastingTrainingJob, AutoMLImageTrainingJob, AutoMLTabularTrainingJob,
AutoMLTextTrainingJob, or AutoMLVideoTrainingJob in a Location.
"""
template_fields = (
"region",
"project_id",... | ListAutoMLTrainingJobOperator |
python | doocs__leetcode | solution/0000-0099/0078.Subsets/Solution.py | {
"start": 0,
"end": 350
} | class ____:
def subsets(self, nums: List[int]) -> List[List[int]]:
def dfs(i: int):
if i == len(nums):
ans.append(t[:])
return
dfs(i + 1)
t.append(nums[i])
dfs(i + 1)
t.pop()
ans = []
t = []
... | Solution |
python | getsentry__sentry | src/sentry/plugins/bases/issue2.py | {
"start": 3030,
"end": 17351
} | class ____(Plugin):
auth_provider: str | None = None
allowed_actions = ("create", "link", "unlink")
# we default this to None to support legacy integrations, but newer style
# should explicitly call out what is stored
issue_fields: frozenset[str] | None = None
# issue_fields = frozenset(['id',... | IssueTrackingPlugin2 |
python | jazzband__pip-tools | piptools/resolver.py | {
"start": 19485,
"end": 32056
} | class ____(BaseResolver):
"""A wrapper for the backtracking (or 2020) resolver."""
def __init__(
self,
constraints: Iterable[InstallRequirement],
existing_constraints: dict[str, InstallRequirement],
repository: BaseRepository,
allow_unsafe: bool = False,
unsafe_p... | BacktrackingResolver |
python | urllib3__urllib3 | src/urllib3/contrib/emscripten/response.py | {
"start": 694,
"end": 9507
} | class ____(BaseHTTPResponse):
def __init__(
self,
internal_response: EmscriptenResponse,
url: str | None = None,
connection: BaseHTTPConnection | BaseHTTPSConnection | None = None,
):
self._pool = None # set by pool class
self._body = None
self._response ... | EmscriptenHttpResponseWrapper |
python | numpy__numpy | numpy/_core/tests/test_multiarray.py | {
"start": 245009,
"end": 247841
} | class ____:
def _create_arrays(self):
a = np.arange(20.0).reshape(4, 5)
a.flags.writeable = False
b = a[::2, ::2]
return a, b
def test_contiguous(self):
testpassed = False
a, _ = self._create_arrays()
try:
a.flat[12] = 100.0
except Val... | TestFlat |
python | kamyu104__LeetCode-Solutions | Python/maximum-and-sum-of-array.py | {
"start": 72,
"end": 2199
} | class ____(object):
def maximumANDSum(self, nums, numSlots):
"""
:type nums: List[int]
:type numSlots: int
:rtype: int
"""
# Template translated from:
# https://github.com/kth-competitive-programming/kactl/blob/main/content/graph/WeightedMatching.h
def... | Solution |
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