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 |
|---|---|---|---|---|---|---|---|---|---|
nonebot/nonebot2 | from collections.abc import Callable
from dataclasses import asdict
from functools import wraps
from pathlib import Path
import sys
from typing import TypeVar
from typing_extensions import ParamSpec
import pytest
import nonebot
from nonebot.plugin import (
Plugin,
PluginManager,
_managers,
_plugins,
... | {sub_plugin, sub_plugin2} | assert | collection | tests/test_plugin/test_load.py | test_load_nested_plugin | 84 | null | |
nonebot/nonebot2 | from http.cookies import SimpleCookie
import json
from typing import Any
from aiohttp import ClientSession, ClientWebSocketResponse, WSMessage, WSMsgType
import anyio
from nonebug import App
import pytest
from nonebot.adapters import Bot
from nonebot.dependencies import Dependent
from nonebot.drivers import (
URL... | None | assert | none_literal | tests/test_driver.py | background_task | 184 | null | |
nonebot/nonebot2 | import json
from typing import ClassVar, Dict, List, Literal, TypeVar, Union # noqa: UP035
from nonebot.utils import (
DataclassEncoder,
escape_tag,
generic_check_issubclass,
is_async_gen_callable,
is_coroutine_callable,
is_gen_callable,
)
from utils import FakeMessage, FakeMessageSegment
def... | "{" '"type": "node", ' '"data": {"content": [{"type": "text", "data": {"text": "text"}}]}' "}" | assert | string_literal | tests/test_utils.py | test_dataclass_encoder | 119 | null | |
nonebot/nonebot2 | from collections.abc import Callable
import pytest
import nonebot
from nonebot.adapters import Event
from nonebot.matcher import Matcher, matchers
from nonebot.rule import (
CommandRule,
EndswithRule,
FullmatchRule,
IsTypeRule,
KeywordsRule,
RegexRule,
ShellCommandRule,
StartswithRule,... | "plugin" | assert | string_literal | tests/test_plugin/test_on.py | test_runtime_on | 165 | null | |
nonebot/nonebot2 | import pytest
from nonebot.adapters import MessageTemplate
from utils import FakeMessage, FakeMessageSegment, escape_text
def test_template_message():
template = FakeMessage.template("{a:custom}{b:text}{c:image}/{d}")
@template.add_format_spec
def custom(input: str) -> str:
return f"{input}-custo... | "custom-custom!text/114" | assert | string_literal | tests/test_adapters/test_template.py | test_template_message | 32 | null | |
nonebot/nonebot2 | from typing import TYPE_CHECKING
from pydantic import BaseModel, Field
import pytest
from nonebot.compat import PYDANTIC_V2, LegacyUnionField
from nonebot.config import DOTENV_TYPE, BaseSettings, SettingsConfig, SettingsError
def test_config_without_delimiter():
config = ExampleWithoutDelimiter()
assert conf... | 0 | assert | numeric_literal | tests/test_config.py | test_config_without_delimiter | 120 | null | |
nonebot/nonebot2 | from pydantic import ValidationError
import pytest
from nonebot.adapters import Message, MessageSegment
from nonebot.compat import type_validate_python
from utils import FakeMessage, FakeMessageSegment
def test_message_contains():
message = FakeMessage(
[
FakeMessageSegment.text("test"),
... | False | assert | bool_literal | tests/test_adapters/test_message.py | test_message_contains | 190 | null | |
nonebot/nonebot2 | from collections.abc import Callable
from dataclasses import asdict
from functools import wraps
from pathlib import Path
import sys
from typing import TypeVar
from typing_extensions import ParamSpec
import pytest
import nonebot
from nonebot.plugin import (
Plugin,
PluginManager,
_managers,
_plugins,
... | num_managers + 1 | assert | complex_expr | tests/test_plugin/test_load.py | test_require_not_declared | 160 | null | |
nonebot/nonebot2 | from dataclasses import dataclass
from typing import Annotated, Any
from pydantic import BaseModel, ValidationError
import pytest
from nonebot.compat import (
DEFAULT_CONFIG,
FieldInfo,
PydanticUndefined,
Required,
TypeAdapter,
custom_validation,
field_validator,
model_dump,
model_... | 1 | assert | numeric_literal | tests/test_compat.py | test_field_validator | 54 | null | |
fudan-zvg/SETR | import torch
from mmseg.models import FPN
def test_fpn():
in_channels = [256, 512, 1024, 2048]
inputs = [
torch.randn(1, c, 56 // 2**i, 56 // 2**i)
for i, c in enumerate(in_channels)
]
fpn = FPN(in_channels, 256, len(in_channels))
outputs = fpn(inputs)
assert outputs[0].shape ... | torch.Size([1, 256, 28, 28]) | assert | func_call | tests/test_models/test_necks.py | test_fpn | 16 | null | |
fudan-zvg/SETR | import glob
import os
from os.path import dirname, exists, isdir, join, relpath
from mmcv import Config
from torch import nn
from mmseg.models import build_segmentor
def _get_config_directory():
"""Find the predefined segmentor config directory."""
try:
# Assume we are running in the source mmsegment... | len(decode_head) | assert | func_call | tests/test_config.py | _check_decode_head | 135 | null | |
fudan-zvg/SETR | import numpy as np
from mmseg.core.evaluation import mean_iou
def get_confusion_matrix(pred_label, label, num_classes, ignore_index):
"""Intersection over Union
Args:
pred_label (np.ndarray): 2D predict map
label (np.ndarray): label 2D label map
num_classes (int): number of... | num_imgs | assert | variable | tests/test_mean_iou.py | legacy_mean_iou | 30 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_utils():
loss = torch.rand(1, 3, 4, 4)
weight = torch.zeros(1, 3, 4, 4)
weight[:, :, :2, :2] = 1
# test reduce_loss()
reduced = reduce_loss(loss, 'none')
assert re... | loss | assert | variable | tests/test_models/test_losses.py | test_utils | 15 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | classes | assert | variable | tests/test_data/test_dataset.py | test_custom_classes_override_default | 201 | null | |
fudan-zvg/SETR | import glob
import os
from os.path import dirname, exists, isdir, join, relpath
from mmcv import Config
from torch import nn
from mmseg.models import build_segmentor
def _get_config_directory():
"""Find the predefined segmentor config directory."""
try:
# Assume we are running in the source mmsegment... | len(decode_head.in_index) | assert | func_call | tests/test_config.py | _check_decode_head | 151 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 2 | assert | numeric_literal | tests/test_models/test_heads.py | test_fcn_head | 133 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 0 | assert | numeric_literal | tests/test_models/test_heads.py | test_fcn_head | 168 | null | |
fudan-zvg/SETR | import numpy as np
from mmseg.core.evaluation import mean_iou
def get_confusion_matrix(pred_label, label, num_classes, ignore_index):
"""Intersection over Union
Args:
pred_label (np.ndarray): 2D predict map
label (np.ndarray): label 2D label map
num_classes (int): number of... | all_acc_l | assert | variable | tests/test_mean_iou.py | test_mean_iou | 54 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_accuracy():
# test for empty pred
pred = torch.empty(0, 4)
label = torch.empty(0)
accuracy = Accuracy(topk=1)
acc = accuracy(pred, label)
assert acc.item() == 0
... | 40 | assert | numeric_literal | tests/test_models/test_losses.py | test_accuracy | 100 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | list(classes) | assert | func_call | tests/test_data/test_dataset.py | test_custom_classes_override_default | 212 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | 2 | assert | numeric_literal | tests/test_data/test_dataset.py | test_custom_dataset_random_palette_is_generated | 246 | null | |
fudan-zvg/SETR | import math
import os.path as osp
import pytest
from torch.utils.data import (DistributedSampler, RandomSampler,
SequentialSampler)
from mmseg.datasets import (DATASETS, ConcatDataset, build_dataloader,
build_dataset)
def test_build_dataloader():
dataset ... | 16 | assert | numeric_literal | tests/test_data/test_dataset_builder.py | test_build_dataloader | 192 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmseg.models.utils import InvertedResidual
def test_inv_residual():
with pytest.raises(AssertionError):
# test stride assertion.
InvertedResidual(32, 32, 3, 4)
# test default config with res connection.
# set expand_ratio = 4, stride = 1 and inp=oup.
in... | 0 | assert | numeric_literal | tests/test_utils/test_inverted_residual_module.py | test_inv_residual | 17 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_resize():
# test assertion if img_scale is a list
with pytest.raises(AssertionError):
transform = dict(type=... | 1333 * 1.1 | assert | complex_expr | tests/test_data/test_transform.py | test_resize | 93 | null | |
fudan-zvg/SETR | import torch
from mmseg.models import FPN
def test_fpn():
in_channels = [256, 512, 1024, 2048]
inputs = [
torch.randn(1, c, 56 // 2**i, 56 // 2**i)
for i, c in enumerate(in_channels)
]
fpn = FPN(in_channels, 256, len(in_channels))
outputs = fpn(inputs)
assert outputs[0].shape... | torch.Size([1, 256, 56, 56]) | assert | func_call | tests/test_models/test_necks.py | test_fpn | 15 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | original_classes | assert | variable | tests/test_data/test_dataset.py | test_custom_classes_override_default | 200 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 1 | assert | numeric_literal | tests/test_models/test_heads.py | test_fcn_head | 177 | null | |
fudan-zvg/SETR | import glob
import os
from os.path import dirname, exists, isdir, join, relpath
from mmcv import Config
from torch import nn
from mmseg.models import build_segmentor
def _get_config_directory():
"""Find the predefined segmentor config directory."""
try:
# Assume we are running in the source mmsegment... | decode_head.in_channels | assert | complex_expr | tests/test_config.py | _check_decode_head | 153 | null | |
fudan-zvg/SETR | import logging
import tempfile
from unittest.mock import MagicMock, patch
import mmcv.runner
import pytest
import torch
import torch.nn as nn
from mmcv.runner import obj_from_dict
from torch.utils.data import DataLoader, Dataset
from mmseg.apis import single_gpu_test
from mmseg.core import DistEvalHook, EvalHook
def... | [torch.tensor([1])]) | assert_* | collection | tests/test_eval_hook.py | test_eval_hook | 74 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_seg_rescale():
results = dict()
seg = np.array(
Image.open(osp.join(osp.dirname(__file__), '../data/seg.png'... | (h // 2, w // 2) | assert | collection | tests/test_data/test_transform.py | test_seg_rescale | 237 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmcv.ops import DeformConv2dPack
from mmcv.utils.parrots_wrapper import _BatchNorm
from torch.nn.modules import AvgPool2d, GroupNorm
from mmseg.models.backbones import (FastSCNN, ResNeSt, ResNet, ResNetV1d,
ResNeXt)
from mmseg.models.backbones.resnest... | 16 | assert | numeric_literal | tests/test_models/test_backbone.py | test_resnet_bottleneck | 183 | null | |
fudan-zvg/SETR | import torch
from mmseg.models import FPN
def test_fpn():
in_channels = [256, 512, 1024, 2048]
inputs = [
torch.randn(1, c, 56 // 2**i, 56 // 2**i)
for i, c in enumerate(in_channels)
]
fpn = FPN(in_channels, 256, len(in_channels))
outputs = fpn(inputs)
assert outputs[0].shape ... | torch.Size([1, 256, 14, 14]) | assert | func_call | tests/test_models/test_necks.py | test_fpn | 17 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_resize():
# test assertion if img_scale is a list
with pytest.raises(AssertionError):
transform = dict(type=... | 400 | assert | numeric_literal | tests/test_data/test_transform.py | test_resize | 72 | null | |
fudan-zvg/SETR | import glob
import os
from os.path import dirname, exists, isdir, join, relpath
from mmcv import Config
from torch import nn
from mmseg.models import build_segmentor
def _get_config_directory():
"""Find the predefined segmentor config directory."""
try:
# Assume we are running in the source mmsegment... | None | assert | none_literal | tests/test_config.py | test_config_build_segmentor | 61 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 0.05 | assert | numeric_literal | tests/test_models/test_heads.py | test_dnl_head | 584 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_utils():
loss = torch.rand(1, 3, 4, 4)
weight = torch.zeros(1, 3, 4, 4)
weight[:, :, :2, :2] = 1
# test reduce_loss()
reduced = reduce_loss(loss, 'none')
assert red... | target) | assert_* | variable | tests/test_models/test_losses.py | test_utils | 29 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmcv.ops import DeformConv2dPack
from mmcv.utils.parrots_wrapper import _BatchNorm
from torch.nn.modules import AvgPool2d, GroupNorm
from mmseg.models.backbones import (FastSCNN, ResNeSt, ResNet, ResNetV1d,
ResNeXt)
from mmseg.models.backbones.resnest... | 3 | assert | numeric_literal | tests/test_models/test_backbone.py | test_resnet_res_layer | 237 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_random_crop():
# test assertion for invalid random crop
with pytest.raises( | AssertionError) | pytest.raises | variable | tests/test_data/test_transform.py | test_random_crop | 137 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | ValueError) | pytest.raises | variable | tests/test_data/test_dataset.py | test_classes | 20 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 48 | assert | numeric_literal | tests/test_models/test_heads.py | test_decode_head | 99 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmseg.models.utils import InvertedResidual
def test_inv_residual():
with pytest.raises(AssertionError):
# test stride assertion.
InvertedResidual(32, 32, 3, 4)
# test default config with res connection.
# set expand_ratio = 4, stride = 1 and inp=oup.
in... | 1 | assert | numeric_literal | tests/test_utils/test_inverted_residual_module.py | test_inv_residual | 19 | null | |
fudan-zvg/SETR | import math
import os.path as osp
import pytest
from torch.utils.data import (DistributedSampler, RandomSampler,
SequentialSampler)
from mmseg.datasets import (DATASETS, ConcatDataset, build_dataloader,
build_dataset)
def test_build_dataset():
cfg = dict(... | 5 | assert | numeric_literal | tests/test_data/test_dataset_builder.py | test_build_dataset | 60 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | None | assert | none_literal | tests/test_models/test_heads.py | test_decode_head | 86 | null | |
fudan-zvg/SETR | import os.path as osp
import pickle
import shutil
import tempfile
import time
import mmcv
import torch
import torch.distributed as dist
from mmcv.image import tensor2imgs
from mmcv.runner import get_dist_info
from mmdet.core import encode_mask_results
def single_gpu_test(model,
data_loader,
... | len(img_metas) | assert | func_call | hlg-detection/mmdet/apis/test.py | single_gpu_test | 39 | null | |
fudan-zvg/SETR | import math
import os.path as osp
import pytest
from torch.utils.data import (DistributedSampler, RandomSampler,
SequentialSampler)
from mmseg.datasets import (DATASETS, ConcatDataset, build_dataloader,
build_dataset)
def test_build_dataset():
cfg = dict(... | 1 | assert | numeric_literal | tests/test_data/test_dataset_builder.py | test_build_dataset | 32 | null | |
fudan-zvg/SETR | import torch
from mmseg.models import FPN
def test_fpn():
in_channels = [256, 512, 1024, 2048]
inputs = [
torch.randn(1, c, 56 // 2**i, 56 // 2**i)
for i, c in enumerate(in_channels)
]
fpn = FPN(in_channels, 256, len(in_channels))
outputs = fpn(inputs)
assert outputs[0].shape ... | torch.Size([1, 256, 7, 7]) | assert | func_call | tests/test_models/test_necks.py | test_fpn | 18 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_seg_rescale():
results = dict()
seg = np.array(
Image.open(osp.join(osp.dirname(__file__), '../data/seg.png'... | (h, w) | assert | collection | tests/test_data/test_transform.py | test_seg_rescale | 242 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_utils():
loss = torch.rand(1, 3, 4, 4)
weight = torch.zeros(1, 3, 4, 4)
weight[:, :, :2, :2] = 1
# test reduce_loss()
reduced = reduce_loss(loss, 'none')
assert red... | loss.sum()) | assert_* | func_call | tests/test_models/test_losses.py | test_utils | 21 | null | |
fudan-zvg/SETR | import logging
import tempfile
from unittest.mock import MagicMock, patch
import mmcv.runner
import pytest
import torch
import torch.nn as nn
from mmcv.runner import obj_from_dict
from torch.utils.data import DataLoader, Dataset
from mmseg.apis import single_gpu_test
from mmseg.core import DistEvalHook, EvalHook
def... | TypeError) | pytest.raises | variable | tests/test_eval_hook.py | test_eval_hook | 42 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_accuracy():
# test for empty pred
pred = torch.empty(0, 4)
label = torch.empty(0)
accuracy = Accuracy(topk=1)
acc = accuracy(pred, label)
assert acc.item() == 0
... | 100 | assert | numeric_literal | tests/test_models/test_losses.py | test_accuracy | 94 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | 4 | assert | numeric_literal | tests/test_data/test_dataset.py | test_custom_dataset | 114 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmcv.ops import DeformConv2dPack
from mmcv.utils.parrots_wrapper import _BatchNorm
from torch.nn.modules import AvgPool2d, GroupNorm
from mmseg.models.backbones import (FastSCNN, ResNeSt, ResNet, ResNetV1d,
ResNeXt)
from mmseg.models.backbones.resnest... | 9 | assert | numeric_literal | tests/test_models/test_backbone.py | test_resnet_backbone | 379 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_ce_loss():
from mmseg.models import build_loss
# use_mask and use_sigmoid cannot be true at the same time
with pytest.raises( | AssertionError) | pytest.raises | variable | tests/test_models/test_losses.py | test_ce_loss | 47 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmseg.core import OHEMPixelSampler
from mmseg.models.decode_heads import FCNHead
def _context_for_ohem():
return FCNHead(in_channels=32, channels=16, num_classes=19)
def test_ohem_sampler():
with pytest.raises(AssertionError):
# seg_logit and seg_label must be of the ... | seg_logit.shape[0] | assert | complex_expr | tests/test_sampler.py | test_ohem_sampler | 27 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 32 | assert | numeric_literal | tests/test_models/test_heads.py | test_decode_head | 85 | null | |
fudan-zvg/SETR | import numpy as np
from mmseg.core.evaluation import mean_iou
def get_confusion_matrix(pred_label, label, num_classes, ignore_index):
"""Intersection over Union
Args:
pred_label (np.ndarray): 2D predict map
label (np.ndarray): label 2D label map
num_classes (int): number of... | -1 | assert | numeric_literal | tests/test_mean_iou.py | test_mean_iou | 62 | null | |
fudan-zvg/SETR | import numpy as np
import pytest
import torch
from mmseg.models.losses import Accuracy, reduce_loss, weight_reduce_loss
def test_utils():
loss = torch.rand(1, 3, 4, 4)
weight = torch.zeros(1, 3, 4, 4)
weight[:, :, :2, :2] = 1
# test reduce_loss()
reduced = reduce_loss(loss, 'none')
assert red... | loss.mean()) | assert_* | func_call | tests/test_models/test_losses.py | test_utils | 18 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmseg.models.utils import InvertedResidual
def test_inv_residual():
with pytest.raises(AssertionError):
# test stride assertion.
InvertedResidual(32, 32, 3, 4)
# test default config with res connection.
# set expand_ratio = 4, stride = 1 and inp=oup.
in... | (1, 1) | assert | collection | tests/test_utils/test_inverted_residual_module.py | test_inv_residual | 16 | null | |
fudan-zvg/SETR | import os.path as osp
import pickle
import shutil
import tempfile
import mmcv
import torch
import torch.distributed as dist
from mmcv.image import tensor2imgs
from mmcv.runner import get_dist_info
def single_gpu_test(model, data_loader, show=False, out_dir=None):
"""Test with single GPU.
Args:
model ... | len(img_metas) | assert | func_call | mmseg/apis/test.py | single_gpu_test | 43 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import tempfile
import mmcv
import numpy as np
from mmseg.datasets.pipelines import LoadAnnotations, LoadImageFromFile
class TestLoading(object):
def setup_class(cls):
cls.data_prefix = osp.join(osp.dirname(__file__), '../data')
def test_load_img(self):
res... | np.uint8 | assert | complex_expr | tests/test_data/test_loading.py | test_load_img | TestLoading | 25 | null |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | 7 | assert | numeric_literal | tests/test_data/test_dataset.py | test_dataset_wrapper | 57 | null | |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 3 | assert | numeric_literal | tests/test_models/test_heads.py | test_psp_head | 207 | null | |
fudan-zvg/SETR | import argparse
import copy
import os
import os.path as osp
import mmcv
import torch
from mmcv import DictAction
from mmcv.parallel import MMDataParallel, MMDistributedDataParallel
from mmcv.runner import (get_dist_info, init_dist, load_checkpoint,
wrap_fp16_model)
from pycocotools.coco import... | ['proposal', 'bbox', 'segm', 'keypoints'] | assert | collection | hlg-detection/tools/analysis_tools/test_robustness.py | coco_eval_with_return | 29 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | 15 | assert | numeric_literal | tests/test_data/test_dataset.py | test_dataset_wrapper | 51 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmseg.core import OHEMPixelSampler
from mmseg.models.decode_heads import FCNHead
def _context_for_ohem():
return FCNHead(in_channels=32, channels=16, num_classes=19)
def test_ohem_sampler():
with pytest.raises( | AssertionError) | pytest.raises | variable | tests/test_sampler.py | test_ohem_sampler | 14 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_resize():
# test assertion if img_scale is a list
with pytest.raises(AssertionError):
transform = dict(type=... | 1333 | assert | numeric_literal | tests/test_data/test_transform.py | test_resize | 71 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import tempfile
import mmcv
import numpy as np
from mmseg.datasets.pipelines import LoadAnnotations, LoadImageFromFile
class TestLoading(object):
def setup_class(cls):
cls.data_prefix = osp.join(osp.dirname(__file__), '../data')
def test_load_img(self):
res... | np.float32 | assert | complex_expr | tests/test_data/test_loading.py | test_load_img | TestLoading | 47 | null |
fudan-zvg/SETR | from unittest.mock import patch
import pytest
import torch
from mmcv.cnn import ConvModule, DepthwiseSeparableConvModule
from mmcv.utils import ConfigDict
from mmcv.utils.parrots_wrapper import SyncBatchNorm
from mmseg.models.decode_heads import (ANNHead, ASPPHead, CCHead, DAHead,
... | 8 | assert | numeric_literal | tests/test_models/test_heads.py | test_dw_aspp_head | 538 | null | |
fudan-zvg/SETR | import pytest
import torch
from mmseg.models.utils import InvertedResidual
def test_inv_residual():
with pytest.raises(AssertionError):
# test stride assertion.
InvertedResidual(32, 32, 3, 4)
# test default config with res connection.
# set expand_ratio = 4, stride = 1 and inp=oup.
in... | (3, 3) | assert | collection | tests/test_utils/test_inverted_residual_module.py | test_inv_residual | 18 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import mmcv
import numpy as np
import pytest
from mmcv.utils import build_from_cfg
from PIL import Image
from mmseg.datasets.builder import PIPELINES
def test_random_crop():
# test assertion for invalid random crop
with pytest.raises(AssertionError):
transform = dict... | (h - 20, w - 20) | assert | collection | tests/test_data/test_transform.py | test_random_crop | 159 | null | |
fudan-zvg/SETR | import copy
import os.path as osp
import tempfile
import mmcv
import numpy as np
from mmseg.datasets.pipelines import LoadAnnotations, LoadImageFromFile
class TestLoading(object):
def setup_class(cls):
cls.data_prefix = osp.join(osp.dirname(__file__), '../data')
def test_load_seg_custom_classes(sel... | (10, 10) | assert | collection | tests/test_data/test_loading.py | test_load_seg_custom_classes | TestLoading | 145 | null |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | 3 | assert | numeric_literal | tests/test_data/test_dataset.py | test_custom_dataset_random_palette_is_generated | 248 | null | |
fudan-zvg/SETR | import os.path as osp
from unittest.mock import MagicMock, patch
import numpy as np
import pytest
from mmseg.core.evaluation import get_classes, get_palette
from mmseg.datasets import (DATASETS, ADE20KDataset, CityscapesDataset,
ConcatDataset, CustomDataset, PascalVOCDataset,
... | [classes[0]] | assert | collection | tests/test_data/test_dataset.py | test_custom_classes_override_default | 223 | null | |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import mock_open, patch
from hackingBuddyGPT.usecases.web_api_testing.documentation.parsing.openapi_converter import (
OpenAPISpecificationConverter,
)
class TestOpenAPISpecificationConverter(unittest.TestCase):
def setUp(self):
self.converter = OpenAPISpec... | result) | self.assertIsNone | variable | tests/test_openapi_converter.py | test_convert_file_yaml_to_json_error | TestOpenAPISpecificationConverter | 70 | null |
ipa-lab/hackingBuddyGPT | import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer_with_llm import ResponseAnalyzerWithLLM
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
class TestResponseAnalyzerWithLLM(unittest.TestCase):
def se... | "text/html") | self.assertEqual | string_literal | tests/test_response_analyzer_with_llm.py | test_parse_http_response_html | TestResponseAnalyzerWithLLM | 46 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.documentation import OpenAPISpecificationHandler
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptStrategy, PromptC... | self.openapi_handler.is_partial_match("/admin", ["/users/{id}", "/posts"])) | self.assertFalse | func_call | tests/test_openAPI_specification_manager.py | test_is_partial_match_false | TestOpenAPISpecificationHandler | 168 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptContext
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_handler import (
R... | updated_spec["components"]["schemas"]["Test"]["properties"]) | self.assertIn | complex_expr | tests/test_response_handler.py | test_parse_http_response_to_schema | TestResponseHandler | 105 | null |
ipa-lab/hackingBuddyGPT | import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer_with_llm import ResponseAnalyzerWithLLM
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
class TestResponseAnalyzerWithLLM(unittest.TestCase):
def se... | "200") | self.assertEqual | string_literal | tests/test_response_analyzer_with_llm.py | test_parse_http_response_success | TestResponseAnalyzerWithLLM | 31 | null |
ipa-lab/hackingBuddyGPT | import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer_with_llm import ResponseAnalyzerWithLLM
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
class TestResponseAnalyzerWithLLM(unittest.TestCase):
def se... | full_response) | self.assertIn | variable | tests/test_response_analyzer_with_llm.py | test_get_addition_context | TestResponseAnalyzerWithLLM | 82 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.documentation import OpenAPISpecificationHandler
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptStrategy, PromptC... | "200") | self.assertEqual | string_literal | tests/test_openAPI_specification_manager.py | test_extract_status_code_and_message_valid | TestOpenAPISpecificationHandler | 122 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.logging import LocalLogger
from hackingBuddyGPT.usecases.web_api_testing.simple_openapi_documentation import (
SimpleWebAPIDocumentation,
SimpleWebAPIDocumentationUseCase,
)
from hackingBuddyGPT.utils import Console... | self.agent._prompt_history[0]["content"]) | self.assertIn | complex_expr | tests/test_web_api_documentation.py | test_initial_prompt | TestSimpleWebAPIDocumentationTest | 41 | null |
ipa-lab/hackingBuddyGPT | import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer_with_llm import ResponseAnalyzerWithLLM
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
class TestResponseAnalyzerWithLLM(unittest.TestCase):
def se... | additional_context) | self.assertIn | variable | tests/test_response_analyzer_with_llm.py | test_get_addition_context | TestResponseAnalyzerWithLLM | 81 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptContext
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_handler import (
R... | {"type": "str", "example": "test"}) | self.assertEqual | collection | tests/test_response_handler.py | test_extract_keys | TestResponseHandler | 131 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import mock_open, patch
from hackingBuddyGPT.usecases.web_api_testing.documentation.parsing.openapi_converter import (
OpenAPISpecificationConverter,
)
class TestOpenAPISpecificationConverter(unittest.TestCase):
def setUp(self):
self.converter = OpenAPISpec... | "r") | assert_* | string_literal | tests/test_openapi_converter.py | test_convert_file_yaml_to_json | TestOpenAPISpecificationConverter | 27 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.documentation import OpenAPISpecificationHandler
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptStrategy, PromptC... | "double") | self.assertEqual | string_literal | tests/test_openAPI_specification_manager.py | test_get_type_double | TestOpenAPISpecificationHandler | 135 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptContext
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_handler import (
R... | "#/components/schemas/Test") | self.assertEqual | string_literal | tests/test_response_handler.py | test_parse_http_response_to_schema | TestResponseHandler | 102 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | printed) | self.assertIn | variable | tests/test_response_analyzer.py | test_print_analysis_output_structure | TestResponseAnalyzer | 94 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | msg) | self.assertEqual | variable | tests/test_response_analyzer.py | test_parse_http_response_success | TestResponseAnalyzer | 41 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
class TestPromptGenerationHelper(unittest.TestCase):
def setUp(self):
self.host = "https://reqres.in"
self.description = "Fake API"
self.prompt_helper = PromptGenerationHelper(self.host, self.descript... | "") | self.assertEqual | string_literal | tests/test_prompt_generation_helper.py | test_get_user_from_prompt | TestPromptGenerationHelper | 24 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | "Valid") | self.assertEqual | string_literal | tests/test_response_analyzer.py | test_is_valid_input_response | TestResponseAnalyzer | 72 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.usecases.web_api_testing.simple_web_api_testing import (
SimpleWebAPITestingUseCase, SimpleWebAPITesting,
)
from hackingBuddyGPT.utils import Console, DbStorage
from hackingBuddyGPT.utils.logging import LocalLogger
class Tes... | contents) | self.assertIn | variable | tests/test_web_api_testing.py | test_initial_prompt | TestSimpleWebAPITestingTest | 40 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | 200) | self.assertEqual | numeric_literal | tests/test_response_analyzer.py | test_analyze_authentication | TestResponseAnalyzer | 57 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptContext
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_handler import (
R... | openapi_spec) | self.assertEqual | variable | tests/test_response_handler.py | test_parse_http_response_to_openapi_example | TestResponseHandler | 70 | null |
ipa-lab/hackingBuddyGPT | import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.utils import LLMHandler
class TestLLMHandler(unittest.TestCase):
def setUp(self):
self.llm_mock = MagicMock()
self.capabilities = {"cap1": MagicMock(), "cap2": MagicMock()}
self.llm_handler = ... | self.llm_handler.created_objects) | self.assertIn | complex_expr | tests/test_llm_handler.py | test_add_created_object | TestLLMHandler | 38 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | "Authenticated") | self.assertEqual | string_literal | tests/test_response_analyzer.py | test_analyze_authentication | TestResponseAnalyzer | 58 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | "Error") | self.assertEqual | string_literal | tests/test_response_analyzer.py | test_is_valid_input_response | TestResponseAnalyzer | 74 | null |
ipa-lab/hackingBuddyGPT | import unittest
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer import ResponseAnalyzer
class TestResponseAnalyzer(unittest.TestCase):
def setUp(self):
self.auth_headers = (
"HTTP/... | "Unexpected") | self.assertEqual | string_literal | tests/test_response_analyzer.py | test_is_valid_input_response | TestResponseAnalyzer | 75 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.prompt_generation import PromptGenerationHelper
from hackingBuddyGPT.utils.prompt_generation.information import PromptContext
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_handler import (
R... | entry_dict) | self.assertIn | variable | tests/test_response_handler.py | test_parse_http_response_to_openapi_example | TestResponseHandler | 71 | null |
ipa-lab/hackingBuddyGPT | import unittest
from unittest.mock import MagicMock
from hackingBuddyGPT.usecases.web_api_testing.response_processing.response_analyzer_with_llm import ResponseAnalyzerWithLLM
from hackingBuddyGPT.utils.prompt_generation.information import PromptPurpose
class TestResponseAnalyzerWithLLM(unittest.TestCase):
def se... | "Execution Result") | self.assertEqual | string_literal | tests/test_response_analyzer_with_llm.py | test_process_step_calls_llm_handler | TestResponseAnalyzerWithLLM | 65 | null |
ipa-lab/hackingBuddyGPT | import os
import unittest
from unittest.mock import MagicMock, patch
from hackingBuddyGPT.utils.logging import LocalLogger
from hackingBuddyGPT.usecases.web_api_testing.simple_openapi_documentation import (
SimpleWebAPIDocumentation,
SimpleWebAPIDocumentationUseCase,
)
from hackingBuddyGPT.utils import Console... | result) | self.assertFalse | variable | tests/test_web_api_documentation.py | test_perform_round | TestSimpleWebAPIDocumentationTest | 89 | null |
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