code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from numpy import exp, pi, sqrt
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase = 0.0 , UpperCAmelCase = 1.0 ):
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 152 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_snake_case : Optional[int] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[Any] , ... | 81 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
... | 326 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 81 | 0 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingT... | 155 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_snake_case : List[str] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : List[str] , *lowe... | 81 | 0 |
def lowerCAmelCase_ (lowercase__ : Tuple , lowercase__ : List[str] ) -> Dict:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
lowerCAmelCase__ = str(bin(__lowerCamel... | 668 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case : Union[str, Any] = {
"configuration_owlvit": ... | 81 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
... | 26 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case : int = logging.get_logger(__name__)
_snake_case : str = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/con... | 81 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
... | 119 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_snake_case : Union[str, Any] = logging.getLogger(__name__)
def lowerCAmelCase_ ( ):
__snake_case : int = argparse.ArgumentParser(
... | 81 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ : Optional[int] = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig",
... | 298 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
g... | 81 | 0 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_p... | 425 |
_snake_case : Optional[int] = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
_snake_case : Dict = ["a", "b", "c", "d", "e"]
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
__snake_case ... | 81 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'''files''', [
['''full:README.md''', '''dataset_infos.json'''],
['''empty:RE... | 212 |
def lowerCAmelCase_ ( ):
return [
a * b * (1_0_0_0 - a - b)
for a in range(1 , 9_9_9 )
for b in range(__lowerCamelCase , 9_9_9 )
if (a * a + b * b == (1_0_0_0 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'''{so... | 81 | 0 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('''>=''', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.default... | 454 |
from math import sqrt
def lowerCAmelCase_ ( __lowerCamelCase = 1_0_0_0_0_0_0 ):
__snake_case : int = 0
__snake_case : int = 0
__snake_case : int
while num_cuboids <= limit:
max_cuboid_size += 1
... | 81 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _UpperCamelCase ( _lowerCAmelCase):
def __init__(self , lowerCamelCase__ , lowerCamelCase__ ):
"""simple d... | 574 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test... | 81 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
__a: int = {
... | 152 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
_snake_case : int = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[int] , ... | 81 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
"tokenization_m2m_100": ["M2M100T... | 326 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_... | 81 | 0 |
"""simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils impo... | 155 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : Any = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
],
}
... | 81 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_dete... | 668 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
f... | 81 | 0 |
'''simple docstring'''
import requests
__UpperCamelCase = "YOUR API KEY"
def _a ( _lowerCamelCase , _lowerCamelCase = giphy_api_key ) -> Optional[int]:
"""simple docstring"""
__snake_case : Optional[int] = ... | 26 |
class a :
"""simple docstring"""
def __init__( self : Tuple , lowerCamelCase : list ) -> None:
__snake_case : str = set_counts
__snake_case : Union[str, Any] = max(lowerCamelCase ... | 81 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/confi... | 119 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 81 | 0 |
SCREAMING_SNAKE_CASE__ : Optional[int] = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
SCREAMING_SNAKE_CASE__ : Dict = ["a", "b", "c", "d", "e"]
def __magic_name__ ( __lowerCAmelCase : Optional[int] , __lowerCAmelCase : Union[str, Any]... | 298 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrings_... | 81 | 0 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ... | 425 |
from __future__ import annotations
def lowerCAmelCase_ ( __lowerCamelCase ):
if not nums:
return 0
__snake_case : Any = nums[0]
__snake_case : str = 0
for num in nums[1:]:
__snake_case , __snake_c... | 81 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case_ : Any = {
"configuration_roformer": ["ROF... | 212 |
from __future__ import annotations
from typing import Any
def lowerCAmelCase_ ( __lowerCamelCase ):
create_state_space_tree(__lowerCamelCase , [] , 0 )
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase )... | 81 | 0 |
import os
from collections.abc import Iterator
def __snake_case ( _lowerCAmelCase : List[str] = "." ) -> int:
for dir_path, dir_names, filenames in os.walk(__lowerCamelCase ):
A_ : Tuple = [d for d in dir_names if d != "scripts" and d[0] not in "._"]
... | 454 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteSc... | 81 | 0 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class _UpperCamelCase :
def __init__(self ):
"""simple docstring"""
A__ = [2, 1, 2, -1]
A__ = [1, 2, 3, 4]
... | 574 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.tes... | 81 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a: Optional[Any] = logging.get_logger(__name__)
__a: Optional[int] = {
"xlm-mlm-en-2048": "ht... | 152 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_snake_case : Optional[int] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[Any] , ... | 81 | 0 |
class A :
def __init__( self , lowercase_ ) -> None:
'''simple docstring'''
_snake_case : str = set_counts
_snake_case : Union[str, Any] = max(lowercase_ )
_snake_case : List[Any] ... | 326 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 81 | 0 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_imag... | 155 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_snake_case : List[str] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : List[str] , *lowe... | 81 | 0 |
from importlib import import_module
from .logging import get_logger
_UpperCAmelCase : Tuple = get_logger(__name__)
class lowerCAmelCase_ :
def __init__( self : str , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : Dict=None ):
lowerCAmelCas... | 668 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case : Union[str, Any] = {
"configuration_owlvit": ... | 81 | 0 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from dif... | 26 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case : int = logging.get_logger(__name__)
_snake_case : str = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/con... | 81 | 0 |
'''simple docstring'''
from __future__ import annotations
UpperCAmelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
class lowerCAmelCase :
def __init__( self : Tuple ... | 119 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_snake_case : Union[str, Any] = logging.getLogger(__name__)
def lowerCAmelCase_ ( ):
__snake_case : int = argparse.ArgumentParser(
... | 81 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrings_to... | 298 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
g... | 81 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE =logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE ={
"huggingface/informer-tourism-monthly": (
"https:... | 425 |
_snake_case : Optional[int] = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
_snake_case : Dict = ["a", "b", "c", "d", "e"]
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
__snake_case ... | 81 | 0 |
'''simple docstring'''
from __future__ import annotations
def __snake_case ( _UpperCAmelCase : int):
if len(__lowerCamelCase) == 0:
return array
UpperCamelCase = min(__lowerCamelCase), max(__lowerCamelCase)
# Compute the variables
UpperCamelCase = _max - ... | 212 |
def lowerCAmelCase_ ( ):
return [
a * b * (1_0_0_0 - a - b)
for a in range(1 , 9_9_9 )
for b in range(__lowerCamelCase , 9_9_9 )
if (a * a + b * b == (1_0_0_0 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'''{so... | 81 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
_lowerCAmelCase : Union[str, Any] = TypeVar('''T''')
class __magic_name__ ( Generic[T] ):
"""simple docstring"""
def __init__( self :Tu... | 454 |
from math import sqrt
def lowerCAmelCase_ ( __lowerCamelCase = 1_0_0_0_0_0_0 ):
__snake_case : int = 0
__snake_case : int = 0
__snake_case : int
while num_cuboids <= limit:
max_cuboid_size += 1
... | 81 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase__ = {
"configuration_bridgetower": [
"BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"B... | 574 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test... | 81 | 0 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .d... | 152 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
_snake_case : int = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[int] , ... | 81 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMA... | 326 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_... | 81 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( ):
__SCREAMING_SNAKE_CASE = []
__SCREAMING_SNAKE_CASE = 1
while len(__lowerCamelCase ) < 1e6:
constant.append(str(__lowerCamelCase ) )
i += 1
__SCREAMING_SNAKE_CASE = "".join(__lowerCamelCase ... | 155 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : Any = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
],
}
... | 81 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 668 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
f... | 81 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transforme... | 26 |
class a :
"""simple docstring"""
def __init__( self : Tuple , lowerCamelCase : list ) -> None:
__snake_case : str = set_counts
__snake_case : Union[str, Any] = max(lowerCamelCase ... | 81 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
UpperCAmelCase = logging.get_logger(__name__)
def __UpperCamelCase ( lowercase__ : Dict ):
'''simple docstring'''
if isinstance(__lowe... | 119 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 81 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
SCREAMING_SNAKE_CASE__ : Tuple = False
class lowerCAmelCase__ ( unittest.... | 298 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrings_... | 81 | 0 |
"""simple docstring"""
def lowercase__( __SCREAMING_SNAKE_CASE : Dict = 10 ):
if not isinstance(__lowerCamelCase , __lowerCamelCase ) or n < 0:
raise ValueError('Invalid input' )
lowercase_ : List[str] = 10**n
lowercase_ : Optional[int] ... | 425 |
from __future__ import annotations
def lowerCAmelCase_ ( __lowerCamelCase ):
if not nums:
return 0
__snake_case : Any = nums[0]
__snake_case : str = 0
for num in nums[1:]:
__snake_case , __snake_c... | 81 | 0 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_availab... | 212 |
from __future__ import annotations
from typing import Any
def lowerCAmelCase_ ( __lowerCamelCase ):
create_state_space_tree(__lowerCamelCase , [] , 0 )
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase )... | 81 | 0 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class __magic_name__ ( _lowerCAmelCase ):
... | 454 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteSc... | 81 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowerCamelCase__ = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
... | 574 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.tes... | 81 | 0 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class UpperCAmelCase ( pl.LightningModule ):
'''simple docstring'''
def __init__( self , __lowerC... | 152 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_snake_case : Optional[int] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[Any] , ... | 81 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer
... | 326 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 81 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
class SCREAMING_SNAKE_CASE_ ( ... | 155 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_snake_case : List[str] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : List[str] , *lowe... | 81 | 0 |
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 668 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case : Union[str, Any] = {
"configuration_owlvit": ... | 81 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_u... | 26 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case : int = logging.get_logger(__name__)
_snake_case : str = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/con... | 81 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_config... | 119 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_snake_case : Union[str, Any] = logging.getLogger(__name__)
def lowerCAmelCase_ ( ):
__snake_case : int = argparse.ArgumentParser(
... | 81 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __magic_name__ ( __lowerCAmelCase : Union[str, Any] , __lowerCAmelCase : str ) -> Tuple:
__lowerCamelCase = f'''{sampling_rate}'''
__lowerC... | 298 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
g... | 81 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
__SCREAMING_SNAKE_CASE =logging.get_l... | 425 |
_snake_case : Optional[int] = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
_snake_case : Dict = ["a", "b", "c", "d", "e"]
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
__snake_case ... | 81 | 0 |
'''simple docstring'''
def __snake_case ( _UpperCAmelCase : Dict):
UpperCamelCase = len(__lowerCamelCase)
while cur > 1:
# Find the maximum number in arr
UpperCamelCase = arr.index(max(arr[0:cur]))
# Reverse from 0 to mi
UpperCamelCase = arr[mi::-1] +... | 212 |
def lowerCAmelCase_ ( ):
return [
a * b * (1_0_0_0 - a - b)
for a in range(1 , 9_9_9 )
for b in range(__lowerCamelCase , 9_9_9 )
if (a * a + b * b == (1_0_0_0 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'''{so... | 81 | 0 |
def __snake_case ( _lowerCAmelCase : List[str] ) -> List[Any]:
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
A_ : str = sum(__lowerCamelCase ) / len(__lowerCamelCase ) # Calculate the average
... | 454 |
from math import sqrt
def lowerCAmelCase_ ( __lowerCamelCase = 1_0_0_0_0_0_0 ):
__snake_case : int = 0
__snake_case : int = 0
__snake_case : int
while num_cuboids <= limit:
max_cuboid_size += 1
... | 81 | 0 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.... | 574 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test... | 81 | 0 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __Uppe... | 152 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
_snake_case : int = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[int] , ... | 81 | 0 |
import string
def A_ ( lowercase_ ) -> int:
for key in range(len(string.ascii_uppercase ) ):
_snake_case : Optional[int] = ""
for symbol in message:
if symbol in string.ascii_uppercase:
_snake_ca... | 326 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_... | 81 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
f... | 155 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : Any = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
],
}
... | 81 | 0 |
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...test... | 668 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
f... | 81 | 0 |
'''simple docstring'''
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hpara... | 26 |
class a :
"""simple docstring"""
def __init__( self : Tuple , lowerCamelCase : list ) -> None:
__snake_case : str = set_counts
__snake_case : Union[str, Any] = max(lowerCamelCase ... | 81 | 0 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def __UpperCamelCase ( lowercase__ : str, lowercase__ : Union[str, Any], lowercase__ : str, lowercase__ : int, lowercase__ : Union[str, Any], lowercase__ : U... | 119 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 81 | 0 |
def __magic_name__ ( __lowerCAmelCase : Optional[int] , __lowerCAmelCase : Optional[Any] ) -> str:
while second != 0:
__lowerCamelCase = first & second
first ^= second
__lowerCamelCase = c << 1
return first
if __name__ ... | 298 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add_start_docstrings_... | 81 | 0 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE ="Tobias Carryer"
from time import time
class UpperCamelCase :
def __init__( self ,__UpperCamelCase ,__UpperCamelCase ,__UpperCamelCase ,__UpperCamelCase=int(time() ) ) -> Optional[Any]: # noqa: B008
'''simpl... | 425 |
from __future__ import annotations
def lowerCAmelCase_ ( __lowerCamelCase ):
if not nums:
return 0
__snake_case : Any = nums[0]
__snake_case : str = 0
for num in nums[1:]:
__snake_case , __snake_c... | 81 | 0 |
'''simple docstring'''
from __future__ import annotations
def __snake_case ( _UpperCAmelCase : Optional[Any]):
return len(set(__lowerCamelCase)) == len(__lowerCamelCase)
if __name__ == "__main__":
import doctest
doctest.testmod()
| 212 |
from __future__ import annotations
from typing import Any
def lowerCAmelCase_ ( __lowerCamelCase ):
create_state_space_tree(__lowerCamelCase , [] , 0 )
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase )... | 81 | 0 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
_lowerCAmelCase : Dict = logging.getLogger(__name__)
if __name__ =... | 454 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteSc... | 81 | 0 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ =... | 574 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.tes... | 81 | 0 |
'''simple docstring'''
class UpperCAmelCase :
'''simple docstring'''
def __init__( self , __lowerCAmelCase = "" , __lowerCAmelCase = False ) -> None:
# Mapping from the first character of the prefix of the node
lowercase__ : dict[str, Rad... | 152 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_snake_case : Optional[int] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[Any] , ... | 81 | 0 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
lowerCAmelCase_ = logging.get_logger(__name__)
class A (_lowerCAmelCase ):
def __init__( self , *lowercase_ , **lowercase_ ) -> None:
'''simple docstrin... | 326 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 81 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 155 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_snake_case : List[str] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : List[str] , *lowe... | 81 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : str = {
"configuration_whisper": ["WHISPER_PRETRAINED_CONFIG_ARCH... | 668 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case : Union[str, Any] = {
"configuration_owlvit": ... | 81 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
"tiiuae/falcon-40b": "https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json",
... | 26 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case : int = logging.get_logger(__name__)
_snake_case : str = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/con... | 81 | 0 |
'''simple docstring'''
import numpy as np
UpperCAmelCase = [
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class lowerCAmelCase :
def __init__( self : Optional[int] ):
... | 119 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_snake_case : Union[str, Any] = logging.getLogger(__name__)
def lowerCAmelCase_ ( ):
__snake_case : int = argparse.ArgumentParser(
... | 81 | 0 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Optional[Any] = {
"... | 298 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
g... | 81 | 0 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_availab... | 425 |
_snake_case : Optional[int] = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
_snake_case : Dict = ["a", "b", "c", "d", "e"]
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
__snake_case ... | 81 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_... | 212 |
def lowerCAmelCase_ ( ):
return [
a * b * (1_0_0_0 - a - b)
for a in range(1 , 9_9_9 )
for b in range(__lowerCamelCase , 9_9_9 )
if (a * a + b * b == (1_0_0_0 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(f'''{so... | 81 | 0 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects import *... | 454 |
from math import sqrt
def lowerCAmelCase_ ( __lowerCamelCase = 1_0_0_0_0_0_0 ):
__snake_case : int = 0
__snake_case : int = 0
__snake_case : int
while num_cuboids <= limit:
max_cuboid_size += 1
... | 81 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
def _SCREAMING_SNAKE_CASE ( UpperCamelCase : Union[str, Any] , UpperCamelCase : str , UpperCamelCase : Optional[int] ):
A__ = named... | 574 |
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test... | 81 | 0 |
'''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from tra... | 152 |
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
_snake_case : int = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[int] , ... | 81 | 0 |
def A_ ( lowercase_ , lowercase_ , lowercase_ ) -> List[Any]:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowerCamelCase ) )
def A_ ( lowercase_ , lowercase_ , lowercase_ , lowercase_ ) ... | 326 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_... | 81 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCamelCase_ ):
__SCREAMING_SNAKE_CASE = abs(__lowerCamelCase )
__SCREAMING_SNAKE_CASE = 0
while n > 0:
res += n % 10
n //= 10
return res
def _lowerCAmelCase ( UpperCamelCase_ ):
__SCRE... | 155 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_snake_case : Any = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
],
}
... | 81 | 0 |
"""simple docstring"""
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pe... | 82 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 | 1 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCamelCase = input("""Enter image url: """).strip()
print(F"Downloading image from {url} ...")
lowerCamelCase = BeautifulSoup(requests.get(url).c... | 82 |
"""simple docstring"""
lowerCamelCase = """Alexander Joslin"""
import operator as op
from .stack import Stack
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
UpperCAmelCase_ = Stack()
... | 82 | 1 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def a__ ( lowerCAmelCase__ , lowerCAmelCase__=None ):
UpperCAmelCase_ = None
if tok... | 82 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = int(number**0.5 )
return number == sq * sq
def a__ ( lowerCAmelCase__ , lowerCAmel... | 82 | 1 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
lowerCamelCase = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_ver... | 82 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise... | 82 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowercase__... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lower... | 82 | 1 |
"""simple docstring"""
class lowercase__ :
'''simple docstring'''
def __init__( self : str ) -> Optional[Any]:
'''simple docstring'''
UpperCAmelCase_ = ""
UpperCAmelCase_ ... | 82 |
"""simple docstring"""
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 82 | 1 |
"""simple docstring"""
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,... | 82 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create... | 82 | 1 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docs... | 82 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = sorted(zip(lowerCAmelCase__ , lowerCAmelCase__ ) ... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = len(lowerCAmelCase__ )
UpperCAmelCase_ = sum(lowerCAmelCase__ )
UpperCAmelCase_ = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 ... | 82 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
lowerCamelCase = """\
@inproceedings{popovic-2015-chrf,
title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",
author = \"Popovi{\'c}, ... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float(moles / volume ) * nfactor )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
return round(float((moles * 0... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 82 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCamelCase = 6_378_137.0
lowerCamelCase = 6_356_752.314_245
lowerCamelCase = 6_378_137
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ... | 82 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""ksstev... | 82 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids... | 82 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransforme... | 82 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase = 50_000
lowerCamelCase = 5_000
lowerCamelCase , lowerCamelCase = os.path.split(__file__)
lowerCamelCase = os.pat... | 82 | 1 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
lowerCamelCase = logging.getLogger(__name__)
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowercase__ ( SCREAMING_SNAKE_CASE ):
... | 82 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if edge <= 0 or not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def a__ ( lowe... | 82 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
lowerCamelCase = False
class lowercase_... | 82 | 1 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 | 1 |
"""simple docstring"""
from __future__ import annotations
class lowercase__ :
'''simple docstring'''
def __init__( self : List[str] , _UpperCAmelCase : int ) -> None:
'''simple docstring'''
... | 82 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
... | 82 | 1 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
lowerCamelCase = pd.read_csv("""sample_data.csv""", hea... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = 0
UpperCAmelCase_ = len(lowerCAmelCase__ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase__ ):
if arr[i] > arr[j]:
... | 82 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a__ ( lowerCAmelCase__ ):
UpperCAmelCase_ = args.pruning_method
UpperCAmelCase_ = args... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ ):
if number > 0:
raise ValueError("input must be a negative integer" )
UpperCAmelCase_ = len(bin(lowerCAmelCase__ )[3:] )
UpperCAmelCase_ = bin(abs(lowerCAmelCase__ ) - (1 << binary_num... | 82 | 1 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def... | 82 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..imag... | 82 | 1 |
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