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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__A = {
'''configuration_perceiver''': ['''PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Pe... | 646 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcesso... | 646 | """simple docstring"""
# Copyright 2023 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.org/licenses/LICENSE-2.0... | 646 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _snake_case :
snake_case__ = None
snake_case__ = False
snake_case__ = False
snake_case__ = ... | 646 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 1 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
snake_case__ = ""
snake_case__ = (
None # protocol passed i... | 646 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 1 |
"""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 ModelT... | 646 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: dict ) -> set:
'''simple docstring'''
__lowerCamelCase : Union[str, Any] = set()
# edges = list of graph's edges
__lowerCamelCase : Any = get_edges(_lowerCamelCase )
# While there are ... | 646 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__A = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__A = _LazyModule(__name__, globals()['''__file__'''], _im... | 646 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 1 |
"""simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__A = logging.getLogger(__name__)
... | 646 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transforme... | 646 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 1 |
"""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
__A = logging.get_logger(__name__)
__A = {... | 646 | """simple docstring"""
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... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetConfig''', '... | 646 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.n... | 646 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def lowercase_ ( _lowerCamelCase: Sequence[float] , _lowerCamelCase: bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
__lowerCamelCase : int = 0 if allow_empty_sub... | 646 | """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 ImageProcessingSavingTe... | 646 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''kssteven/ibert-roberta-base''': '''https://huggingface.... | 646 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 1 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures,... | 646 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FIL... | 646 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 1 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,... | 646 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto im... | 646 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: Tuple ) -> List[Any]:
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__lowerCamelCase : Optional[int] = len(_lowerCamelCase )
__l... | 646 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod() | 646 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: int , _lowerCamelCase: int ) -> list[list[int]]:
'''simple docstring'''
__lowerCamelCase : list[list[int]] = []
create_all_state(1 , _lowerCamelCase , _lowerCam... | 646 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 1 |
"""simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowercase_ ( _lowerCamelCase: dict , _lowerCamelCase: str , _lowerCamelCase: set , _lowerCamelCase: set , _lowerCamelCase: dict , _lowerCamelCase: dict , _lowerCa... | 646 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''facebook/xmod-base''': '''https://huggingface.co/facebo... | 646 | """simple docstring"""
# Copyright 2023 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.org/licenses/LICENSE-2.0... | 646 | 1 |
"""simple docstring"""
from math import log
from scipy.constants import Boltzmann, physical_constants
__A = 300 # TEMPERATURE (unit = K)
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float , _lowerCamelCase: float , ) -> float:
'''simple docstring'''
... | 646 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 1 |
"""simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
__A = 8.9_8_8e9 # units = N * m^s * C^-2
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float , _lowerCamelCase: float , _lowerCamelCase: float ) -> dict[str, float]:
'''simple docstring'''
... | 646 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 1 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowercase_ ( _lowerCamelCase: str = "isbn/0140328726" ) -> dict:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = olid.strip().strip(... | 646 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 646 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module ):
snake_case__ = 42
snake_case__ = 42
... | 646 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 1 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
snake_case__ = "li... | 646 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 1 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. 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.org/licenses/LICENSE-2.0... | 646 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 1 |
"""simple docstring"""
__A = {str(digit): digit**5 for digit in range(10)}
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_lowerCamelCase ) )
def lowercase_ ( ) -> int:
'''simple d... | 646 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import i... | 646 | """simple docstring"""
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... | 646 | 1 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
__A = logging.get_logger(__name__)
def lowercase_ ( _lowerCamelCase: int , _lowerCamelCase: Tup... | 646 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: str ) -> bool:
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError("String must only contain alphabetic characters." )
__lowerCamelCase : Dict = sorted(string.low... | 646 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 1 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class _snake_case :
def __init__( self : List[Any] , UpperCAmelCase : Tuple , UpperCAmelCase : List[Any] , UpperCAmelCase : List[Any] , ... | 646 | """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 ImageProcessingSavingTe... | 646 | 1 |
"""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
__A = logging.get_logger(__name__)
__A = {
'''google/mobilenet_v2_1.4_... | 646 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 1 |
"""simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''EncodecConfig''',
],
'''feature_ext... | 646 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 1 |
"""simple docstring"""
from math import ceil, sqrt
def lowercase_ ( _lowerCamelCase: int = 1000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : Dict = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
... | 646 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigT... | 646 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, sl... | 646 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 1 |
"""simple docstring"""
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
... | 646 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 1 |
"""simple docstring"""
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _snake_case ( yaml.SafeLoader ):
def lowerCamelCase__ ( self : Dict , UpperCAmelCase : Optional[int] ):
__lo... | 646 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {
'''configuration_upernet''': ['''UperNetConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Optional... | 646 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import YolosConfig
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 Conf... | 646 | """simple docstring"""
# Copyright 2023 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.org/licenses/LICENSE-2.0... | 646 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int ) -> int:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("multiplicative_persistence() only accepts integral values" )
if num < 0:
rai... | 646 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowerCamelCase: list[int | str] ) -> None:
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowercase_ ( _lowerCame... | 646 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 1 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
__A = logging.getLogger(__name__)
@dataclass
class... | 646 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 1 |
"""simple docstring"""
import re
def lowercase_ ( _lowerCamelCase: str ) -> bool:
'''simple docstring'''
__lowerCamelCase : List[Any] = re.compile(r"^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$" )
if match := re.search(_lowerCamelCase , _lowerCamelCase ):
... | 646 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 646 | 1 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 646 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sen... | 646 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_transfo_xl''': ['''TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TransfoXLConfig'''],
'''tokenization_transfo_xl'''... | 646 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 1 |
"""simple docstring"""
import random
from .binary_exp_mod import bin_exp_mod
def lowercase_ ( _lowerCamelCase: Tuple , _lowerCamelCase: str=1000 ) -> Dict:
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
... | 646 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
tr... | 646 | """simple docstring"""
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... | 646 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils i... | 646 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 1 |
"""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:README.md", "dataset_infos.jso... | 646 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowercase_ ( _lowerCamelCase: str ) -> Dict:
''... | 646 | """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 ImageProcessingSavingTe... | 646 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Optional[int] , _lowerCamelCase... | 646 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 1 |
"""simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_... | 646 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 1 |
"""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_convbert import ConvBertTokenizer
__A = logging.get_logger(__name__)
__A = {'''v... | 646 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 1 |
"""simple docstring"""
import argparse
import struct
import unittest
class _snake_case :
def __init__( self : Optional[int] , UpperCAmelCase : bytes ):
__lowerCamelCase : Dict = data
# Initialize hash values
__lowerC... | 646 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__A = {
'''configuration_blenderbot''': [
'''BLENDERBOT_PRETRAINE... | 646 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 1 |
"""simple docstring"""
__A = 65521
def lowercase_ ( _lowerCamelCase: str ) -> int:
'''simple docstring'''
__lowerCamelCase : Dict = 1
__lowerCamelCase : Union[str, Any] = 0
for plain_chr in plain_text:
__lowerCamelCase : Tup... | 646 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 1 |
"""simple docstring"""
from cva import destroyAllWindows, imread, imshow, waitKey
def lowercase_ ( _lowerCamelCase: Any ) -> Optional[Any]:
'''simple docstring'''
__lowerCamelCase , __lowerCamelCase : int = img.shape[0], img.shape[1]
# converting each pixel's color... | 646 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor... | 646 | """simple docstring"""
# Copyright 2023 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.org/licenses/LICENSE-2.0... | 646 | 1 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def lowercase_ ( _lowerCamelCase: np.ndarray , _lowerCamelCase: float ) -> np.ndarray:
'''simple docstring'''
__lowerCamelCase : int = math.sqrt(_lowerCamelCase )
__lowerCamelCase... | 646 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokeni... | 646 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, 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, ids_tensor, random_attention_mask
fr... | 646 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A = get_tests_dir('''fixtures/test_sentencepiece_with_bytefall... | 646 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 646 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 646 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 1 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_atten... | 646 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _snake_case ( unittest.TestCase ):
snake_case__ = ... | 646 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__A = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ConditionalDetrConfig... | 646 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 1 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_... | 646 | """simple docstring"""
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... | 646 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__A = logging.getLogger(__name__)
def lowercase_ ( ) -> str:
'''simple docstring'''
__lowerCamelCase : Tuple = argparse.ArgumentP... | 646 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 1 |
"""simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int = 100 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[Any] = sum(i * i for i in range(1 , n + 1 ) )
__lowerCamelCase : Optional[Any] = int(math.pow(sum(range(1 ... | 646 | """simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
snake_case__ = [("... | 646 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
# See all GPTNeoX models at https://hug... | 646 | """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 ImageProcessingSavingTe... | 646 | 1 |
"""simple docstring"""
from string import ascii_uppercase
__A = {char: i for i, char in enumerate(ascii_uppercase)}
__A = dict(enumerate(ascii_uppercase))
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str ) -> str:
'''simple docstring'''
__lowerCamelCase ... | 646 | """simple docstring"""
def lowercase_ ( _lowerCamelCase: float , _lowerCamelCase: float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F"""{price_plus_tax(100, 0.25) = }""")
print(F"""{price_plus_tax(1_25.50, 0.05) =... | 646 | 1 |
"""simple docstring"""
import enum
import shutil
import sys
__A, __A = shutil.get_terminal_size()
__A = {'''UP''': '''A''', '''DOWN''': '''B''', '''RIGHT''': '''C''', '''LEFT''': '''D'''}
class _snake_case ( enum.Enum ):
snake_case__ = 0
snake_case__ = 1
d... | 646 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_ima... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def lowercase_ ( _lowerCamelCase: Callable[[int | float], int | float] , _lowerCamelCase: int | float , _lowerCamelCase: int | float , _lowerCamelCase: int = 100 , ) -> float:
... | 646 | """simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require... | 646 | 1 |
"""simple docstring"""
from math import factorial
def lowercase_ ( _lowerCamelCase: int = 20 ) -> int:
'''simple docstring'''
__lowerCamelCase : Optional[int] = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
__lowerC... | 646 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 | 1 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__A = '''\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
title = {BLEU: a Method for Au... | 646 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 1 |
"""simple docstring"""
from math import sqrt
def lowercase_ ( _lowerCamelCase: int = 1000000 ) -> int:
'''simple docstring'''
__lowerCamelCase : int = 0
__lowerCamelCase : int = 0
__lowerCamelCase : int
while num_cuboids <= limit:
... | 646 | """simple docstring"""
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: int , _lowerCamelCase: Union[str, Any] ) ... | 646 | 1 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def lowercase_ ( _lowerCamelCase: int ) -> str:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("Undefined for non-integer... | 646 | """simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowercase_ ( _lowerCamelCase: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or n... | 646 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
__A = TypeVar('''T''')
__A = TypeVar('''U''')
class _snake_case ( Generic[T, U] ):
def __init__( self : Any , UpperCAmelCase : ... | 646 | """simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__A = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of t... | 646 | 1 |
"""simple docstring"""
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
__A = True
... | 646 | """simple docstring"""
from manim import *
class _snake_case ( a__ ):
def lowerCamelCase__ ( self : str ):
__lowerCamelCase : Tuple = Rectangle(height=0.5 , width=0.5 )
__lowerCamelCase : Dict = Rectangle(height=... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__A = {'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except Opt... | 646 | """simple docstring"""
# Copyright 2023 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.org/licenses/LICENSE-2.0... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A = {'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeiTConfig''', '''DeiTOnn... | 646 | """simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
__A = 0b101100111110110010010000011110111011000110011110
# bin(x)... | 646 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _snake_case ( a__ ):
snake_case__ ... | 646 | """simple docstring"""
# Imports
import numpy as np
class _snake_case :
def __init__( self : Union[str, Any] , UpperCAmelCase : Dict=None , UpperCAmelCase : Any=None , UpperCAmelCase : Optional[int]=None , UpperCAmelCase : ... | 646 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
__A = '''\
@inproceedings{popovic-2015-chrf,
title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",
author = "Popovi{\'c}, Maja",
booktitle = "Proceedings ... | 646 | """simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...te... | 646 | 1 |
"""simple docstring"""
class _snake_case :
def __init__( self : int , UpperCAmelCase : list[int] ):
__lowerCamelCase : Optional[int] = len(UpperCAmelCase )
__lowerCamelCase : int = [0] * len_array
if le... | 646 | """simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 646 | 1 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__A = logging.get_logger('''transformers.models.speecht5''')
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: ... | 646 | """simple docstring"""
import math
def lowercase_ ( _lowerCamelCase: int ) -> list[int]:
'''simple docstring'''
__lowerCamelCase : Optional[int] = []
__lowerCamelCase : Tuple = 2
__lowerCamelCase : str = int(math.sqrt(_lowerCamelCase ) ... | 646 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioConfig'''],
'''configuration_... | 646 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers i... | 646 | 1 |
"""simple docstring"""
def lowercase_ ( _lowerCamelCase: int , _lowerCamelCase: int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(0 ) == 0 )
def lowercase_ ( ) -> None:
'''simple docstring'''
assert and_gate(0 , 0 ) == 0... | 646 | """simple docstring"""
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
__A = log... | 646 | 1 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
__A = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.0... | 646 | """simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self : Optional[Any] , *UpperCAmelCase : int , **... | 646 | 1 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_pa... | 646 | """simple docstring"""
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... | 646 | 1 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib... | 646 | """simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parame... | 646 | 1 |
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