repo_id stringclasses 409
values | prefix large_stringlengths 34 36.3k | target large_stringlengths 1 498 | assertion_type stringclasses 31
values | difficulty stringclasses 8
values | test_file stringlengths 10 121 | test_function stringlengths 1 104 | test_class stringlengths 0 51 | lineno int32 2 11.3k | commit_idx int32 |
|---|---|---|---|---|---|---|---|---|---|
worldcoin/open-iris | import numpy as np
import pytest
from iris.io.dataclasses import EyeOrientation, GeometryPolygons
from iris.nodes.eye_properties_estimation.moment_of_area import MomentOfArea
from tests.unit_tests.utils import rotated_elliptical_contour
@pytest.mark.parametrize(
"input_contour,expected_eye_orientation",
[(rot... | 1 / 360 | assert | complex_expr | tests/e2e_tests/nodes/eye_properties_estimation/test_e2e_moment_of_area.py | test_first_order_area | 21 | null | |
worldcoin/open-iris | import json
import os
import random
from typing import List
from unittest.mock import Mock
import cv2
import numpy as np
import pytest
from iris.callbacks.pipeline_trace import PipelineCallTraceStorage
from iris.io.dataclasses import IRImage, IrisTemplate
from iris.orchestration.environment import Environment
from ir... | "right" | assert | string_literal | tests/e2e_tests/pipelines/test_e2e_multiframe_iris_pipeline.py | test_iris_pipeline_with_aggregation_single_image | TestMultiframeIrisPipeline | 95 | null |
worldcoin/open-iris | import os
from contextlib import nullcontext as does_not_raise
from typing import Any, Dict, List, Optional
from unittest.mock import MagicMock, Mock, patch
import cv2
import numpy as np
import onnxruntime as ort
import pytest
import yaml
from _pytest.fixtures import FixtureRequest
import iris
from iris import __vers... | input_version | assert | variable | tests/unit_tests/pipelines/test_iris_pipeline.py | test_version_validation_behavior | 994 | null | |
worldcoin/open-iris | import numpy as np
import pytest
from iris.io.dataclasses import IrisTemplate, IrisTemplateWithId
from iris.nodes.templates_alignment.hamming_distance_based import (
HammingDistanceBasedAlignment,
ReferenceSelectionMethod,
)
class TestE2EHammingDistanceBasedAlignment:
def sample_templates(self):
... | (16, 256, 2) | assert | collection | tests/e2e_tests/nodes/templates_alignment/test_e2e_hamming_distance_based.py | test_e2e_alignment_default_parameters | TestE2EHammingDistanceBasedAlignment | 149 | null |
worldcoin/open-iris | from numbers import Number
from typing import Tuple
import numpy as np
import pytest
from pydantic import ValidationError
from iris.io.dataclasses import GeometryPolygons, IRImage
from iris.io.errors import BoundingBoxEstimationError
from iris.nodes.eye_properties_estimation.iris_bbox_calculator import IrisBBoxCalcul... | expected_result[0] | assert | complex_expr | tests/unit_tests/nodes/eye_properties_estimation/test_iris_bbox_calculator.py | test_iris_bbox_calculator | 60 | null | |
worldcoin/open-iris | import copy
from typing import Any, Dict, List
import pytest
from _pytest.fixtures import FixtureRequest
from iris.callbacks.pipeline_trace import NodeResultsWriter, PipelineCallTraceStorage
from iris.io.class_configs import Algorithm
from iris.nodes.eye_properties_estimation.occlusion_calculator import OcclusionCalc... | mock_result | assert | variable | tests/unit_tests/callbacks/test_pipeline_trace.py | test_write_get_input | 117 | null | |
worldcoin/open-iris | import pytest
from iris.io.errors import IRISPipelineError
from iris.orchestration.validators import pipeline_config_duplicate_node_name_check, pipeline_metadata_version_check
class TestPipelineConfigDuplicateNodeNameCheck:
def test_unique_node_names_passes(self):
"""Test that unique node names pass vali... | nodes | assert | variable | tests/unit_tests/orchestration/test_orchestration_validators.py | test_unique_node_names_passes | TestPipelineConfigDuplicateNodeNameCheck | 35 | null |
worldcoin/open-iris | import numpy as np
import pytest
from iris.io.dataclasses import IrisTemplate, IrisTemplateWithId
from iris.nodes.templates_alignment.hamming_distance_based import (
HammingDistanceBasedAlignment,
ReferenceSelectionMethod,
)
class TestE2EHammingDistanceBasedAlignment:
def sample_templates(self):
... | (8, 32, 2) | assert | collection | tests/e2e_tests/nodes/templates_alignment/test_e2e_hamming_distance_based.py | test_e2e_different_rotation_shifts | TestE2EHammingDistanceBasedAlignment | 286 | null |
worldcoin/open-iris | from typing import Tuple
import numpy as np
import pytest
from iris.io.errors import GeometryRefinementError
from iris.nodes.geometry_refinement.smoothing import Smoothing
from tests.unit_tests.utils import generate_arc
def algorithm() -> Smoothing:
return Smoothing(dphi=1, kernel_size=10)
def test_sort_two_arr... | second_array) | assert_* | variable | tests/unit_tests/nodes/geometry_refinement/test_smoothing.py | test_sort_two_arrays | 111 | null | |
worldcoin/open-iris | from typing import Tuple
import numpy as np
import pytest
from iris.nodes.normalization.utils import correct_orientation, interpolate_pixel_intensity, to_uint8
from tests.unit_tests.utils import generate_arc
@pytest.mark.parametrize(
"input_img",
[
(np.ones(shape=(10, 10), dtype=np.uint8)),
(... | np.uint8 | assert | complex_expr | tests/unit_tests/nodes/normalization/test_normalization_utils.py | test_to_uint8 | 97 | null | |
worldcoin/open-iris | import numpy as np
import pytest
from pydantic import ValidationError
from iris.nodes.geometry_refinement.contour_interpolation import ContourInterpolation
def algorithm() -> ContourInterpolation:
return ContourInterpolation(max_distance_between_boundary_points=0.01)
@pytest.mark.parametrize(
"max_distance_b... | ValidationError) | pytest.raises | variable | tests/unit_tests/nodes/geometry_refinement/test_contour_interpolation.py | test_constructor_raises_an_exception | 28 | null | |
worldcoin/open-iris | import json
from typing import Any, List, Literal
import numpy as np
import pytest
from pydantic import ValidationError
import iris.io.dataclasses as dc
from iris.io.dataclasses import DistanceMatrix
from iris.io.errors import IRISPipelineError
class TestAlignedTemplates:
def sample_iris_templates(self, request... | 1 | assert | numeric_literal | tests/unit_tests/io/test_dataclasses.py | test_initialization | TestAlignedTemplates | 814 | null |
worldcoin/open-iris | import json
from typing import Any, List, Literal
import numpy as np
import pytest
from pydantic import ValidationError
import iris.io.dataclasses as dc
from iris.io.dataclasses import DistanceMatrix
from iris.io.errors import IRISPipelineError
class TestAlignedTemplates:
def sample_iris_templates(self, request... | 0 | assert | numeric_literal | tests/unit_tests/io/test_dataclasses.py | test_serialize | TestAlignedTemplates | 855 | null |
worldcoin/open-iris | from unittest.mock import Mock, patch
import numpy as np
import pytest
from iris.callbacks.pipeline_trace import PipelineCallTraceStorage
from iris.io.dataclasses import IrisTemplate, IrisTemplateWithId
from iris.orchestration.environment import Environment
from iris.orchestration.error_managers import store_error_ma... | "test" | assert | string_literal | tests/unit_tests/pipelines/test_multiframe_aggregation_pipeline.py | test_parameters_class | TestTemplatesAggregationPipeline | 293 | null |
worldcoin/open-iris | import json
import os
import random
from typing import List
from unittest.mock import Mock
import cv2
import numpy as np
import pytest
from iris.callbacks.pipeline_trace import PipelineCallTraceStorage
from iris.io.dataclasses import IRImage, IrisTemplate
from iris.orchestration.environment import Environment
from ir... | len(ir_images) | assert | func_call | tests/e2e_tests/pipelines/test_e2e_multiframe_iris_pipeline.py | test_iris_pipeline_with_aggregation_multiple_images | TestMultiframeIrisPipeline | 180 | null |
worldcoin/open-iris | from typing import Any, Dict, List
import cv2
import numpy as np
def generate_arc(
radius: float, center_x: float, center_y: float, from_angle: float, to_angle: float, num_points: int = 1000
) -> np.ndarray:
angles = np.linspace(from_angle, to_angle, num_points, endpoint=not (from_angle == 0.0 and to_angle ==... | error_dict_2["traceback"] | assert | complex_expr | tests/unit_tests/utils.py | compare_iris_pipeline_error_output | 222 | null | |
worldcoin/open-iris | from typing import Any, Dict, List
import cv2
import numpy as np
def generate_arc(
radius: float, center_x: float, center_y: float, from_angle: float, to_angle: float, num_points: int = 1000
) -> np.ndarray:
angles = np.linspace(from_angle, to_angle, num_points, endpoint=not (from_angle == 0.0 and to_angle ==... | error_dict_2 is None | assert | complex_expr | tests/unit_tests/utils.py | compare_iris_pipeline_error_output | 219 | null | |
worldcoin/open-iris | import os
import pickle
from typing import Any
import numpy as np
from iris.nodes.encoder.iris_encoder import IrisEncoder
def load_mock_pickle(name: str) -> Any:
testdir = os.path.join(os.path.dirname(__file__), "mocks", "iris_encoder")
mock_path = os.path.join(testdir, f"{name}.pickle")
return pickle.... | len(expected_result.mask_codes) | assert | func_call | tests/e2e_tests/nodes/encoder/test_e2e_iris_encoder.py | test_iris_encoder_constructor | 26 | null | |
worldcoin/open-iris | import json
import os
import random
from typing import List
from unittest.mock import Mock
import cv2
import numpy as np
import pytest
from iris.callbacks.pipeline_trace import PipelineCallTraceStorage
from iris.io.dataclasses import IRImage, IrisTemplate
from iris.orchestration.environment import Environment
from ir... | expected | assert | variable | tests/e2e_tests/pipelines/test_e2e_multiframe_iris_pipeline.py | test_iris_pipeline_image_id_assignments | TestMultiframeIrisPipeline | 279 | null |
lightly-ai/lightly | import unittest
from copy import deepcopy
from random import randint, random, seed
from lightly.api.bitmask import BitMask
N = 10
class TestBitMask(unittest.TestCase):
def setup(self, psuccess=1.0):
pass
def assert_difference(self, bistring_1: str, bitstring_2: str, target: str):
mask_a = Bi... | "1") | self.assertEqual | string_literal | tests/api/test_BitMask.py | test_invert | TestBitMask | 179 | null |
lightly-ai/lightly | from PIL import Image
from lightly.transforms import DenseCLTransform
from .. import helpers
def test_multi_view_on_pil_image() -> None:
multi_view_transform = DenseCLTransform(input_size=32)
sample = Image.new("RGB", (100, 100))
output = helpers.assert_list_tensor(multi_view_transform(sample))
asse... | 2 | assert | numeric_literal | tests/transforms/test_densecl_transform.py | test_multi_view_on_pil_image | 12 | null | |
lightly-ai/lightly | from typing import Optional
import pytest
import torch
from pytest_mock import MockerFixture
from torch.nn import Parameter
from lightly.utils import dependency
from torchvision.models import VisionTransformer
from lightly.models.modules import masked_vision_transformer_torchvision
from lightly.models.modules.maske... | 0 | assert | numeric_literal | tests/models/modules/test_masked_vision_transformer_torchvision.py | get_masked_vit | TestMaskedVisionTransformerTorchvision | 42 | null |
lightly-ai/lightly | from typing import List, Optional
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient
from lightly.api.api_workflow_tags import TagDoesNotExistError
from lightly.openapi_generated.swagger_client.models import TagCreator, TagData
from tests.api_workflow import utils
def _get_... | ["file1"] | assert | collection | tests/api_workflow/test_api_workflow_tags.py | test_get_filenames_in_tag__exclude_parent_tag | 149 | null | |
lightly-ai/lightly | import re
import unittest
import pytest
import torch
from lightly.models.modules.memory_bank import MemoryBankModule
class TestMemoryBank:
def test_forward(self) -> None:
torch.manual_seed(0)
memory_bank = MemoryBankModule(size=(5, 2), feature_dim_first=False)
x0 = torch.randn(3, 2)
... | (5, 2) | assert | collection | tests/models/modules/test_memory_bank.py | test_forward | TestMemoryBank | 104 | null |
lightly-ai/lightly | import os
import shutil
import tempfile
import unittest
from typing import List, Tuple
import numpy as np
import torchvision
from PIL.Image import Image
from lightly.data import LightlyDataset
from lightly.data._utils import check_images
from lightly.transforms.torchvision_v2_compatibility import torchvision_transfor... | n_tot) | self.assertEqual | variable | tests/data/test_LightlyDataset.py | test_create_lightly_dataset_from_folder_nosubdir | TestLightlyDataset | 129 | null |
lightly-ai/lightly | import os
import random
import re
import sys
import tempfile
import hydra
import torchvision
import yaml
from hydra.experimental import compose
import lightly
from lightly.data import LightlyDataset
from lightly.utils.bounding_box import BoundingBox
from lightly.utils.cropping.crop_image_by_bounding_boxes import (
... | 0 | assert | numeric_literal | tests/cli/test_cli_crop.py | parse_cli_string | TestCLICrop | 91 | null |
lightly-ai/lightly | from __future__ import annotations
import copy
import random
import unittest
from typing import Optional
import pytest
import torch
import torch.nn as nn
from pytest_mock import MockerFixture
from torch import Tensor
from torch.nn import Identity, Parameter
from lightly.models import utils
from lightly.models.utils ... | 4 | assert | numeric_literal | tests/models/test_ModelUtils.py | test_get_weight_decay_parameters__batch_norm | 823 | null | |
lightly-ai/lightly | import os
import time
import pytest
from pytest_mock import MockerFixture
from urllib3.exceptions import MaxRetryError
from lightly.api import _version_checking
from lightly.openapi_generated.swagger_client.api import VersioningApi
def mock_versioning_api():
return
def test_get_latest_version(mocker: MockerFixt... | "1.2.8" | assert | string_literal | tests/api/test_version_checking.py | test_get_latest_version | 46 | null | |
lightly-ai/lightly | from typing import List, Optional
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient
from lightly.api.api_workflow_tags import TagDoesNotExistError
from lightly.openapi_generated.swagger_client.models import TagCreator, TagData
from tests.api_workflow import utils
def _get_... | tags[0].id) | assert_* | complex_expr | tests/api_workflow/test_api_workflow_tags.py | test_get_tag_name | 190 | null | |
lightly-ai/lightly | import os
import sys
import tempfile
import warnings
import hydra
import pytest
import torchvision
from hydra.experimental import compose
import lightly
from tests.api_workflow.mocked_api_workflow_client import (
MockedApiWorkflowClient,
MockedApiWorkflowSetup,
)
_DATASET_ID = "b2a40959eacd1c9a142ba57b"
cla... | "XYZ" | assert | string_literal | tests/cli/test_cli_download.py | test_parse_cli_string | TestCLIDownload | 65 | null |
lightly-ai/lightly | import csv
import json
import tempfile
import unittest
from pathlib import Path
import numpy as np
from lightly.utils import io
from tests.api_workflow.mocked_api_workflow_client import MockedApiWorkflowSetup
class TestEmbeddingsIO(unittest.TestCase):
def setUp(self) -> None:
# correct embedding file as ... | sorted(loaded)) | self.assertListEqual | func_call | tests/utils/test_io.py | test_save_schema | TestEmbeddingsIO | 133 | null |
lightly-ai/lightly | import unittest
from typing import Optional
import pytest
import torch
from torch import nn
from torch.nn import Linear
from torch.optim import SGD
from lightly.utils import scheduler
from lightly.utils.scheduler import CosineWarmupScheduler
@pytest.mark.parametrize(
"step, max_steps, start_value, end_value, per... | pytest.approx(expected) | assert | func_call | tests/utils/test_scheduler.py | test_cosine_schedule | 44 | null | |
lightly-ai/lightly | import os
import unittest
from unittest import mock
import pytest
from PIL import Image
from lightly.api.utils import (
DatasourceType,
PIL_to_bytes,
get_lightly_server_location_from_env,
get_signed_url_destination,
getenv,
paginate_endpoint,
)
class TestUtils(unittest.TestCase):
def tes... | some_list) | self.assertEqual | variable | tests/api/test_utils.py | test_paginate_endpoint | TestUtils | 94 | null |
lightly-ai/lightly | from lightly.cli.config.get_config import get_lightly_config
def test_get_lightly_config() -> None:
conf = get_lightly_config()
# Assert some default values
assert conf.checkpoint == | "" | assert | string_literal | tests/cli/test_cli_get_lighty_config.py | test_get_lightly_config | 7 | null | |
lightly-ai/lightly | import os
import unittest
from unittest import mock
import pytest
from PIL import Image
from lightly.api.utils import (
DatasourceType,
PIL_to_bytes,
get_lightly_server_location_from_env,
get_signed_url_destination,
getenv,
paginate_endpoint,
)
class TestUtils(unittest.TestCase):
def tes... | []) | self.assertEqual | collection | tests/api/test_utils.py | test_paginate_endpoint_empty | TestUtils | 135 | null |
lightly-ai/lightly | import unittest
import torch
import torch.nn as nn
import torchvision
import lightly
from lightly.models import BYOL, ResNetGenerator
def get_backbone(resnet, num_ftrs=64):
last_conv_channels = list(resnet.children())[-1].in_features
backbone = nn.Sequential(
lightly.models.batchnorm.get_norm_layer(3... | out_dim) | self.assertEqual | variable | tests/models/test_ModelsBYOL.py | test_feature_dim_configurable | TestModelsBYOL | 63 | null |
lightly-ai/lightly | from __future__ import annotations
import contextlib
import io
import os
import shutil
import tempfile
import unittest
from fractions import Fraction
from typing import Any
from unittest import mock
import PIL
import torch
import torchvision
from lightly.data import LightlyDataset, NonIncreasingTimestampError
from l... | PIL.Image.Image) | self.assertIsInstance | complex_expr | tests/data/test_VideoDataset.py | _test_video_dataset_from_folder | TestVideoDataset | 194 | null |
lightly-ai/lightly | import unittest
import torch
import torch.nn as nn
import torchvision
import lightly
from lightly.models import BYOL, ResNetGenerator
def get_backbone(resnet, num_ftrs=64):
last_conv_channels = list(resnet.children())[-1].in_features
backbone = nn.Sequential(
lightly.models.batchnorm.get_norm_layer(3... | out) | self.assertIsNotNone | variable | tests/models/test_ModelsBYOL.py | test_variations_input_dimension | TestModelsBYOL | 80 | null |
lightly-ai/lightly | import pytest
import torch
import torch.nn.functional as F
from pytest_mock import MockerFixture
from torch import distributed as dist
from torch import nn
from torch.optim import SGD
from lightly.loss import msn_loss
from lightly.loss.msn_loss import MSNLoss
from lightly.models.modules.heads import MSNProjectionHead
... | (8, 4) | assert | collection | tests/loss/test_msn_loss.py | test_prototype_probabilitiy | TestMSNLoss | 51 | null |
lightly-ai/lightly | from abc import ABC, abstractmethod
from typing import Optional, Tuple
import pytest
import torch
from pytest_mock import MockerFixture
from torch import Tensor
from torch.nn import Parameter
from lightly.models import utils
from lightly.models.modules.masked_vision_transformer import MaskedVisionTransformer
class M... | tokens.shape[1] | assert | complex_expr | tests/models/modules/masked_vision_transformer_test.py | test_encode | MaskedVisionTransformerTest | 216 | null |
lightly-ai/lightly | import typing
from typing import List
import numpy as np
import pytest
import torch
import torch.nn.functional as F
from torch import Tensor
from lightly.loss import VICRegLLoss
def off_diagonal(x: Tensor) -> Tensor:
n, m = x.shape
assert n == | m | assert | variable | tests/loss/test_vicregl_loss.py | off_diagonal | 161 | null | |
lightly-ai/lightly | import unittest
import torch
import torch.nn as nn
import torchvision
import lightly
from lightly.models import ResNetGenerator, SimCLR
def get_backbone(resnet, num_ftrs=64):
last_conv_channels = list(resnet.children())[-1].in_features
backbone = nn.Sequential(
lightly.models.batchnorm.get_norm_layer... | model) | self.assertIsNotNone | variable | tests/models/test_ModelsSimCLR.py | test_create_variations_cpu | TestModelsSimCLR | 32 | null |
lightly-ai/lightly | import json
import random
import re
from typing import Any, List
from unittest import mock
from unittest.mock import MagicMock
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_compute_worker
from lightly.api.api_workflow_compute_worker import (
STATE_SCH... | tag_0 | assert | variable | tests/api_workflow/test_api_workflow_compute_worker.py | test_get_compute_worker_run_tags__multiple_tags | 898 | null | |
lightly-ai/lightly | from __future__ import annotations
import contextlib
import io
import os
import shutil
import tempfile
import unittest
from fractions import Fraction
from typing import Any
from unittest import mock
import PIL
import torch
import torchvision
from lightly.data import LightlyDataset, NonIncreasingTimestampError
from l... | []) | self.assertListEqual | collection | tests/data/test_VideoDataset.py | test_find_non_increasing_timestamps | TestVideoDataset | 321 | null |
lightly-ai/lightly | import unittest
import torch
import torch.nn as nn
import torchvision
import lightly
from lightly.models import MoCo, ResNetGenerator
def get_backbone(resnet, num_ftrs=64):
last_conv_channels = list(resnet.children())[-1].in_features
backbone = nn.Sequential(
lightly.models.batchnorm.get_norm_layer(3... | out) | self.assertIsNotNone | variable | tests/models/test_ModelsMoCo.py | test_variations_input_dimension | TestModelsMoCo | 80 | null |
lightly-ai/lightly | from typing import Tuple
import pytest
import torch
from pytest_mock import MockerFixture
from pytorch_lightning import Trainer
from torch import Tensor, nn
from torch.utils.data import DataLoader, Dataset
from lightly.utils.benchmarking import KNNClassifier
from lightly.utils.benchmarking.knn_classifier import F
cl... | 2 / 3) | pytest.approx | complex_expr | tests/utils/benchmarking/test_knn_classifier.py | test | TestKNNClassifier | 64 | null |
lightly-ai/lightly | from typing import List, Optional
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient
from lightly.api.api_workflow_tags import TagDoesNotExistError
from lightly.openapi_generated.swagger_client.models import TagCreator, TagData
from tests.api_workflow import utils
def _get_... | tags[0].id | assert | complex_expr | tests/api_workflow/test_api_workflow_tags.py | test_create_tag_from_filenames | 48 | null | |
lightly-ai/lightly | import numpy as np
import pytest
import torch
from torch import Tensor
from lightly.loss import DirectCLRLoss
class TestDirectCLRLoss:
temperature = 0.5
@pytest.mark.parametrize("n_samples", [1, 2, 4])
@pytest.mark.parametrize("dimension", [1, 2, 8])
@pytest.mark.parametrize("loss_dim", [1, 2, 4])
... | l2, abs=1e-5) | pytest.approx | complex_expr | tests/loss/test_directclr_loss.py | test_with_values | TestDirectCLRLoss | 39 | null |
lightly-ai/lightly | import numpy as np
import pytest
import torch
import torch.nn.functional as F
from torch import Tensor
from lightly.loss import MACLLoss
def _cal_macl_loss_original(
pos: Tensor, neg: Tensor, tau_0: float, alpha: float, A0: float
) -> Tensor:
"""The original implementation of the MACL loss.
See: https://... | 0.0, abs=1e-10) | pytest.approx | complex_expr | tests/loss/test_macl_loss.py | test_forward_pass | TestMACLLoss | 102 | null |
lightly-ai/lightly | import json
import random
import re
from typing import Any, List
from unittest import mock
from unittest.mock import MagicMock
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_compute_worker
from lightly.api.api_workflow_compute_worker import (
STATE_SCH... | tag_1 | assert | variable | tests/api_workflow/test_api_workflow_compute_worker.py | test_get_compute_worker_run_tags__multiple_tags | 897 | null | |
lightly-ai/lightly | from typing import List
import pytest
from pytest_mock import MockerFixture
from lightly.active_learning.config.selection_config import SelectionConfig
from lightly.api import ApiWorkflowClient, api_workflow_selection
from lightly.openapi_generated.swagger_client.models import (
JobResultType,
JobState,
J... | "surprise!" | assert | string_literal | tests/api_workflow/test_api_workflow_selection.py | test_selection__too_many_errors | 198 | null | |
lightly-ai/lightly | from abc import ABC, abstractmethod
from typing import Optional, Tuple
import pytest
import torch
from pytest_mock import MockerFixture
from torch import Tensor
from torch.nn import Parameter
from lightly.models import utils
from lightly.models.modules.masked_vision_transformer import MaskedVisionTransformer
class M... | 3 | assert | numeric_literal | tests/models/modules/masked_vision_transformer_test.py | test_encode | MaskedVisionTransformerTest | 213 | null |
lightly-ai/lightly | import numpy as np
import pytest
import torch
from pytest_mock import MockerFixture
from torch import Tensor
from torch import distributed as dist
from lightly.loss import NTXentLoss
class TestNTXentLoss:
def test_forward_pass(self) -> None:
loss = NTXentLoss(memory_bank_size=0)
for bsz in range(... | pytest.approx(0.0) | assert | func_call | tests/loss/test_ntx_ent_loss.py | test_forward_pass | TestNTXentLoss | 99 | null |
lightly-ai/lightly | from abc import ABC, abstractmethod
from typing import Optional, Tuple
import pytest
import torch
from pytest_mock import MockerFixture
from torch import Tensor
from torch.nn import Parameter
from lightly.models import utils
from lightly.models.modules.masked_vision_transformer import MaskedVisionTransformer
class M... | n_masked | assert | variable | tests/models/modules/masked_vision_transformer_test.py | get_masks | MaskedVisionTransformerTest | 405 | null |
lightly-ai/lightly | import unittest
from copy import deepcopy
from random import randint, random, seed
from lightly.api.bitmask import BitMask
N = 10
class TestBitMask(unittest.TestCase):
def setup(self, psuccess=1.0):
pass
def assert_difference(self, bistring_1: str, bitstring_2: str, target: str):
mask_a = Bi... | [1, 3, 4]) | self.assertListEqual | collection | tests/api/test_BitMask.py | test_masked_select_from_list_example | TestBitMask | 162 | null |
lightly-ai/lightly | import pytest
import torch
from pytest_mock import MockerFixture
from torch import distributed as dist
from lightly.loss.dcl_loss import DCLLoss, DCLWLoss, negative_mises_fisher_weights
class TestDCLLoss:
@pytest.mark.parametrize("batch_size", [2, 3])
@pytest.mark.parametrize("dim", [1, 3])
@pytest.mark.... | 0 | assert | numeric_literal | tests/loss/test_dcl_loss.py | test_dclloss_forward | TestDCLLoss | 54 | null |
lightly-ai/lightly | import os
import sys
import tempfile
import warnings
import hydra
import pytest
import torchvision
from hydra.experimental import compose
import lightly
from tests.api_workflow.mocked_api_workflow_client import (
MockedApiWorkflowClient,
MockedApiWorkflowSetup,
)
_DATASET_ID = "b2a40959eacd1c9a142ba57b"
cla... | "123" | assert | string_literal | tests/cli/test_cli_download.py | test_parse_cli_string | TestCLIDownload | 64 | null |
lightly-ai/lightly | import unittest
import torch
import torch.nn as nn
import torchvision
import lightly
from lightly.models import MoCo, ResNetGenerator
def get_backbone(resnet, num_ftrs=64):
last_conv_channels = list(resnet.children())[-1].in_features
backbone = nn.Sequential(
lightly.models.batchnorm.get_norm_layer(3... | num_ftrs) | self.assertEqual | variable | tests/models/test_ModelsMoCo.py | test_feature_dim_configurable | TestModelsMoCo | 58 | null |
lightly-ai/lightly | import json
import random
import re
from typing import Any, List
from unittest import mock
from unittest.mock import MagicMock
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_compute_worker
from lightly.api.api_workflow_compute_worker import (
STATE_SCH... | 1 | assert | numeric_literal | tests/api_workflow/test_api_workflow_compute_worker.py | test_selection_config_from_dict | 319 | null | |
lightly-ai/lightly | import torch
from pytorch_lightning import LightningModule, Trainer
from torch.utils.data import DataLoader
from torchvision.datasets import FakeData
from lightly.transforms.torchvision_v2_compatibility import torchvision_transforms as T
from lightly.utils.benchmarking import MetricCallback
class TestMetricCallback:
... | [0, 1, 2] | assert | collection | tests/utils/benchmarking/test_metric_callback.py | test | TestMetricCallback | 24 | null |
lightly-ai/lightly | from lightly.cli.config.get_config import get_lightly_config
def test_get_lightly_config() -> None:
conf = get_lightly_config()
# Assert some default values
assert conf.checkpoint == ""
assert conf.loader.batch_size == 16
assert conf.trainer.weights_summary is None
assert conf.summary_callback... | 1 | assert | numeric_literal | tests/cli/test_cli_get_lighty_config.py | test_get_lightly_config | 10 | null | |
lightly-ai/lightly | import os
from unittest import mock
import numpy as np
import lightly
from tests.api_workflow import utils
from tests.api_workflow.mocked_api_workflow_client import (
MockedApiWorkflowClient,
MockedApiWorkflowSetup,
)
class TestApiWorkflow(MockedApiWorkflowSetup):
def setUp(self) -> None:
lightly... | id | assert | variable | tests/api_workflow/test_api_workflow.py | test_dataset_id_existing | TestApiWorkflow | 49 | null |
lightly-ai/lightly | from __future__ import annotations
import contextlib
import io
import os
import shutil
import tempfile
import unittest
from fractions import Fraction
from typing import Any
from unittest import mock
import PIL
import torch
import torchvision
from lightly.data import LightlyDataset, NonIncreasingTimestampError
from l... | offsets[0]) | self.assertEqual | complex_expr | tests/data/test_VideoDataset.py | test_video_similar_timestamps_for_different_backends | TestVideoDataset | 129 | null |
lightly-ai/lightly | from typing import List
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_datasets
from lightly.openapi_generated.swagger_client.api import DatasetsApi
from lightly.openapi_generated.swagger_client.models import (
Creator,
DatasetCreateRequest,
Dat... | len(datasets) | assert | func_call | tests/api_workflow/test_api_workflow_datasets.py | test_get_datasets__shared | 244 | null | |
lightly-ai/lightly | import json
import random
import re
from typing import Any, List
from unittest import mock
from unittest.mock import MagicMock
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_compute_worker
from lightly.api.api_workflow_compute_worker import (
STATE_SCH... | message | assert | variable | tests/api_workflow/test_api_workflow_compute_worker.py | test_get_compute_worker_state_and_message_docker_state | 671 | null | |
lightly-ai/lightly | import unittest
import torch
import torch.nn as nn
import torchvision
import lightly
from lightly.models import MoCo, ResNetGenerator
def get_backbone(resnet, num_ftrs=64):
last_conv_channels = list(resnet.children())[-1].in_features
backbone = nn.Sequential(
lightly.models.batchnorm.get_norm_layer(3... | out_dim) | self.assertEqual | variable | tests/models/test_ModelsMoCo.py | test_feature_dim_configurable | TestModelsMoCo | 63 | null |
lightly-ai/lightly | from PIL import Image
from lightly.transforms import DenseCLTransform
from .. import helpers
def test_multi_view_on_pil_image() -> None:
multi_view_transform = DenseCLTransform(input_size=32)
sample = Image.new("RGB", (100, 100))
output = helpers.assert_list_tensor(multi_view_transform(sample))
asser... | (3, 32, 32) | assert | collection | tests/transforms/test_densecl_transform.py | test_multi_view_on_pil_image | 13 | null | |
lightly-ai/lightly | import json
import logging
import time
import pytest
import requests
from pytest_mock import MockerFixture
from requests import Session
from requests.exceptions import RequestException
from urllib3.exceptions import ProtocolError
from urllib3.response import HTTPResponse
from lightly.api import retry_utils
from light... | None | assert | none_literal | tests/api/test_retry_utils.py | test__get_error_code_from_api_exception__body_empty | 235 | null | |
lightly-ai/lightly | import torch
from lightly.transforms import GaussianMixtureMask
def test() -> None:
transform = GaussianMixtureMask(20, (10, 15))
image = torch.rand(3, 32, 17)
output = transform(image)
assert output.shape == | image.shape | assert | complex_expr | tests/transforms/test_gaussian_mixture_masks.py | test | 10 | null | |
lightly-ai/lightly | import pytest
import tqdm
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_datasource_listing
from lightly.openapi_generated.swagger_client.models import DatasourceRawSamplesDataRow
from lightly.openapi_generated.swagger_client.models.datasource_processed_until_timestamp_re... | 4 | assert | numeric_literal | tests/api_workflow/test_api_workflow_datasource_listing.py | test__download_raw_files_divide_and_conquer_iter | TestListingMixin | 635 | null |
lightly-ai/lightly | from typing import Tuple
import pytest
import torch
from pytest_mock import MockerFixture
from pytorch_lightning import Trainer
from torch import Tensor, nn
from torch.utils.data import DataLoader, Dataset
from lightly.utils.benchmarking import KNNClassifier
from lightly.utils.benchmarking.knn_classifier import F
cl... | [] | assert | collection | tests/utils/benchmarking/test_knn_classifier.py | _test__accelerator | TestKNNClassifier | 106 | null |
lightly-ai/lightly | from __future__ import annotations
import copy
import random
import unittest
from typing import Optional
import pytest
import torch
import torch.nn as nn
from pytest_mock import MockerFixture
from torch import Tensor
from torch.nn import Identity, Parameter
from lightly.models import utils
from lightly.models.utils ... | 0 | assert | numeric_literal | tests/models/test_ModelUtils.py | test_random_block_mask_image__aspect_ratio | 604 | null | |
lightly-ai/lightly | import numpy as np
import torch
from PIL import Image
from torch import Tensor
from lightly.transforms import ToTensor
def test_ToTensor() -> None:
img_np = np.random.randint(0, 255, (20, 30, 3), dtype=np.uint8)
img_pil = Image.fromarray(img_np)
img_tens = ToTensor()(img_pil)
assert isinstance(img_ten... | torch.float32 | assert | complex_expr | tests/transforms/test_torchvision_v2compatibility.py | test_ToTensor | 15 | null | |
lightly-ai/lightly | import unittest
from typing import Optional
import pytest
import torch
from torch import nn
from torch.nn import Linear
from torch.optim import SGD
from lightly.utils import scheduler
from lightly.utils.scheduler import CosineWarmupScheduler
@pytest.mark.parametrize(
"step, max_steps, start_value, end_value, per... | expected) | pytest.approx | variable | tests/utils/test_scheduler.py | test_cosine_schedule | 50 | null | |
lightly-ai/lightly | import torch
from lightly.transforms import IRFFT2DTransform
def test() -> None:
transform = IRFFT2DTransform((32, 32))
image = torch.rand(3, 32, 17)
output = transform(image)
assert output.shape == | (3, 32, 32) | assert | collection | tests/transforms/test_irfft2d_transform.py | test | 10 | null | |
lightly-ai/lightly | import torch
from lightly.transforms import RandomFrequencyMaskTransform, RFFT2DTransform
def test() -> None:
rfm_transform = RandomFrequencyMaskTransform()
rfft2d_transform = RFFT2DTransform()
image = torch.randn(3, 64, 64)
fft_image = rfft2d_transform(image)
transformed_image = rfm_transform(fft... | fft_image.shape | assert | complex_expr | tests/transforms/test_random_frequency_mask_transform.py | test | 13 | null | |
lightly-ai/lightly | from typing import TYPE_CHECKING
import numpy as np
import pytest
from numpy.testing import assert_allclose
from sklearn.decomposition import PCA as SKPCA
from lightly.utils.embeddings_2d import PCA, fit_pca
def test_pca_fit_transform_shapes_and_dtype() -> None:
# Create dummy data: 100 samples, 10 features
... | (100, 2) | assert | collection | tests/utils/test_embeddings_2d.py | test_pca_fit_transform_shapes_and_dtype | 31 | null | |
lightly-ai/lightly | import re
import unittest
import pytest
import torch
from lightly.models.modules.memory_bank import MemoryBankModule
class TestNTXentLoss(unittest.TestCase):
def test_forward_easy(self) -> None:
bsz = 3
dim, size = 2, 9
n = 33 * bsz
memory_bank = MemoryBankModule(size=size)
... | next_diff.norm()) | self.assertGreater | func_call | tests/models/modules/test_memory_bank.py | test_forward_easy | TestNTXentLoss | 36 | null |
lightly-ai/lightly | import unittest
from copy import deepcopy
from random import randint, random, seed
from lightly.api.bitmask import BitMask
N = 10
class TestBitMask(unittest.TestCase):
def setup(self, psuccess=1.0):
pass
def assert_difference(self, bistring_1: str, bitstring_2: str, target: str):
mask_a = Bi... | j) | self.assertEqual | variable | tests/api/test_BitMask.py | test_nonzero_bits | TestBitMask | 195 | null |
lightly-ai/lightly | import os
import re
import sys
import tempfile
import hydra
import torchvision
from hydra.experimental import compose
from lightly import cli
from tests.api_workflow.mocked_api_workflow_client import (
N_FILES_ON_SERVER,
MockedApiWorkflowClient,
MockedApiWorkflowSetup,
)
class TestCLIMagic(MockedApiWorkf... | 0 | assert | numeric_literal | tests/cli/test_cli_magic.py | parse_cli_string | TestCLIMagic | 53 | null |
lightly-ai/lightly | from PIL import Image
from lightly.transforms.byol_transform import (
BYOLTransform,
BYOLView1Transform,
BYOLView2Transform,
)
from .. import helpers
def test_view_on_pil_image() -> None:
single_view_transform = BYOLView1Transform(input_size=32)
sample = Image.new("RGB", (100, 100))
output = ... | (3, 32, 32) | assert | collection | tests/transforms/test_byol_transform.py | test_view_on_pil_image | 16 | null | |
lightly-ai/lightly | from typing import TYPE_CHECKING
import numpy as np
import pytest
from numpy.testing import assert_allclose
from sklearn.decomposition import PCA as SKPCA
from lightly.utils.embeddings_2d import PCA, fit_pca
def test_fit_pca_invalid_fraction_raises_value_error() -> None:
X = np.random.randn(20, 4).astype(np.flo... | str(excinfo2.value) | assert | func_call | tests/utils/test_embeddings_2d.py | test_fit_pca_invalid_fraction_raises_value_error | 69 | null | |
lightly-ai/lightly | import numpy as np
import pytest
import torch
from torch import Tensor
from lightly.loss import DirectCLRLoss
class TestDirectCLRLoss:
temperature = 0.5
@pytest.mark.parametrize("batch_size", [1, 8])
def test_forward_pass(self, batch_size: int) -> None:
loss = DirectCLRLoss(loss_dim=32)
b... | pytest.approx(0.0) | assert | func_call | tests/loss/test_directclr_loss.py | test_forward_pass | TestDirectCLRLoss | 52 | null |
lightly-ai/lightly | import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_download_dataset
from lightly.openapi_generated.swagger_client.models import (
DatasetData,
DatasetEmbeddingData,
DatasetType,
ImageType,
TagData,
)
from tests.api_workflow import utils
def ... | 2 | assert | numeric_literal | tests/api_workflow/test_api_workflow_download_dataset.py | test_download_dataset__ok | 142 | null | |
lightly-ai/lightly | from typing import TYPE_CHECKING
import numpy as np
import pytest
from numpy.testing import assert_allclose
from sklearn.decomposition import PCA as SKPCA
from lightly.utils.embeddings_2d import PCA, fit_pca
def test_pca_aligns_with_sklearn(
n: int = 100, noise: float = 1e-6, seed: int = 0
) -> None:
# make... | np.abs(sk_comp)) | assert_* | func_call | tests/utils/test_embeddings_2d.py | test_pca_aligns_with_sklearn | 116 | null | |
lightly-ai/lightly | from typing import List
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_datasets
from lightly.openapi_generated.swagger_client.api import DatasetsApi
from lightly.openapi_generated.swagger_client.models import (
Creator,
DatasetCreateRequest,
Dat... | 1 | assert | numeric_literal | tests/api_workflow/test_api_workflow_datasets.py | test_get_datasets_by_name__own_existing | TestApiWorkflowDatasets | 92 | null |
lightly-ai/lightly | from __future__ import annotations
import contextlib
import io
import os
import shutil
import tempfile
import unittest
from fractions import Fraction
from typing import Any
from unittest import mock
import PIL
import torch
import torchvision
from lightly.data import LightlyDataset, NonIncreasingTimestampError
from l... | backends[1]) | self.assertNotEqual | complex_expr | tests/data/test_VideoDataset.py | test_video_similar_timestamps_for_different_backends | TestVideoDataset | 118 | null |
lightly-ai/lightly | import typing
from typing import List
import numpy as np
import pytest
import torch
import torch.nn.functional as F
from torch import Tensor
from lightly.loss import VICRegLLoss
class TestVICRegLLoss:
def test_forward(self) -> None:
torch.manual_seed(0)
criterion = VICRegLLoss()
global_vi... | 0 | assert | numeric_literal | tests/loss/test_vicregl_loss.py | test_forward | TestVICRegLLoss | 31 | null |
lightly-ai/lightly | import pickle
from pytest_mock import MockerFixture
from urllib3 import PoolManager, Timeout
from lightly.api.swagger_rest_client import LightlySwaggerRESTClientObject
from lightly.openapi_generated.swagger_client.configuration import Configuration
class TestLightlySwaggerRESTClientObject:
def test_request__con... | 1 | assert | numeric_literal | tests/api/test_swagger_rest_client.py | test_request__connection_read_timeout | TestLightlySwaggerRESTClientObject | 71 | null |
lightly-ai/lightly | import csv
import io
import json
import tempfile
import unittest
from collections import defaultdict
from io import IOBase
from typing import *
import numpy as np
import requests
from requests import Response
import lightly
from lightly.api.api_workflow_client import ApiWorkflowClient
from lightly.openapi_generated.s... | None | assert | none_literal | tests/api_workflow/mocked_api_workflow_client.py | get_list_of_raw_samples_from_datasource_by_dataset_id | MockedDatasourcesApi | 721 | null |
lightly-ai/lightly | import unittest
from copy import deepcopy
from random import randint, random, seed
from lightly.api.bitmask import BitMask
N = 10
class TestBitMask(unittest.TestCase):
def setup(self, psuccess=1.0):
pass
def assert_difference(self, bistring_1: str, bitstring_2: str, target: str):
mask_a = Bi... | target) | assert_* | variable | tests/api/test_BitMask.py | test_difference_random | TestBitMask | 122 | null |
lightly-ai/lightly | from typing import Tuple
import pytest
import torch
from pytest_mock import MockerFixture
from pytorch_lightning import Trainer
from torch import Tensor, nn
from torch.utils.data import DataLoader, Dataset
from lightly.utils.benchmarking import KNNClassifier
from lightly.utils.benchmarking.knn_classifier import F
cl... | 1 / 3) | pytest.approx | complex_expr | tests/utils/benchmarking/test_knn_classifier.py | test | TestKNNClassifier | 58 | null |
lightly-ai/lightly | import pytest
import torch
from PIL import Image as PILImageModule
from PIL.Image import Image as PILImage
from torch.testing import assert_close
from lightly.utils.dependency import torchvision_transforms_v2_available
from torchvision.tv_tensors import BoundingBoxes, Mask
from lightly.transforms import AddGridTrans... | img_orig | assert | variable | tests/transforms/test_add_grid_transform.py | test_AddGridTransform_as_dict | 84 | null | |
lightly-ai/lightly | from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_export
from lightly.api import utils as api_utils
from lightly.openapi_generated.swagger_client.models import FileNameFormat, TagData
from tests.api_workflow import utils
def _get_tag(dataset_id: str, tag_name: str) -> TagDa... | tag.id) | assert_* | complex_expr | tests/api_workflow/test_api_workflow_export.py | test_export_label_box_data_rows_by_tag_name | 251 | null | |
lightly-ai/lightly | from __future__ import annotations
import contextlib
import io
import os
import shutil
import tempfile
import unittest
from fractions import Fraction
from typing import Any
from unittest import mock
import PIL
import torch
import torchvision
from lightly.data import LightlyDataset, NonIncreasingTimestampError
from l... | len(dataset)) | self.assertEqual | func_call | tests/data/test_VideoDataset.py | _test_video_dataset_non_increasing_timestamps | TestVideoDataset | 293 | null |
lightly-ai/lightly | import random
import unittest
import torch
import torchvision
from lightly.data import (
BaseCollateFunction,
ImageCollateFunction,
MultiCropCollateFunction,
PIRLCollateFunction,
SimCLRCollateFunction,
SwaVCollateFunction,
)
from lightly.data.collate import (
DINOCollateFunction,
MAECo... | 2 + 10) | self.assertEqual | complex_expr | tests/data/test_data_collate.py | test_msn_collate_forward | TestDataCollate | 218 | null |
lightly-ai/lightly | from __future__ import annotations
import contextlib
import io
import os
import shutil
import tempfile
import unittest
from fractions import Fraction
from typing import Any
from unittest import mock
import PIL
import torch
import torchvision
from lightly.data import LightlyDataset, NonIncreasingTimestampError
from l... | offsets[1]) | self.assertEqual | complex_expr | tests/data/test_VideoDataset.py | test_video_similar_timestamps_for_different_backends | TestVideoDataset | 122 | null |
lightly-ai/lightly | from typing import List
import pytest
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_datasets
from lightly.openapi_generated.swagger_client.api import DatasetsApi
from lightly.openapi_generated.swagger_client.models import (
Creator,
DatasetCreateRequest,
Dat... | 2 | assert | numeric_literal | tests/api_workflow/test_api_workflow_datasets.py | test_get_datasets__shared | 246 | null | |
lightly-ai/lightly | import pytest
import tqdm
from pytest_mock import MockerFixture
from lightly.api import ApiWorkflowClient, api_workflow_datasource_listing
from lightly.openapi_generated.swagger_client.models import DatasourceRawSamplesDataRow
from lightly.openapi_generated.swagger_client.models.datasource_processed_until_timestamp_re... | "read-url" | assert | string_literal | tests/api_workflow/test_api_workflow_datasource_listing.py | test_get_prediction_read_url | TestListingMixin | 523 | null |
lightly-ai/lightly | from PIL import Image
from lightly.transforms.mae_transform import MAETransform
def test_multi_view_on_pil_image() -> None:
multi_view_transform = MAETransform(input_size=32)
sample = Image.new("RGB", (100, 100))
output = multi_view_transform(sample)
assert len(output) == 1
assert output[0].shape... | (3, 32, 32) | assert | collection | tests/transforms/test_mae_transform.py | test_multi_view_on_pil_image | 11 | null |
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