code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
SCREAMING_SNAKE_CASE : str = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.jso... | 21 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
class A_ ( lowerCAmelCase_ ):
def __init__( self : Tuple , *snake_cas... | 22 |
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.parametrize('revision' ... | 329 | 0 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
UpperCamelCase__: Tuple = logging.getLogge... | 23 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
def lowerCamelCase__ ( snake_case_ : int = 1 , snake_case_ : int = 1000 ) -> int:
__snake_case = 1
__snake_case = 0
for divide_by_number in range(snake_case_ , digit + 1 ):
__snake_case = [... | 24 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase__ : str = logging.get_logger(__name__)
UpperCAmelCase__ : int = {
'CarlCochet/trajectory-transformer-halfcheetah-medium-v2': (
'h... | 25 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 0 |
def lowerCAmelCase_ ( snake_case_ ):
assert column_title.isupper()
_A : Any = 0
_A : List[str] = len(snake_case_ ) - 1
_A : Optional[Any] = 0
while index >= 0:
_A : Optional[int] = (ord(co... | 26 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase (_SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : str ):
__a : List[str] = list(_SCREAMING_SNAKE_CASE )... | 27 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
'''simple docstring'''
def __lowerCamelCase ( A__ = 50 ) -> int:
"""simple docstring"""
UpperCamelCase = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for b... | 28 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 0 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..model... | 29 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__a = logging.get_logger(__name__)
class lowercase__( UpperCAmelCase ):
"""simple docstring"""
a :Union[str, Any] =... | 30 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def UpperCamelCase_ ( _UpperCA... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class SCREAMING_SNAKE_CASE__ ( lowercase__ ):
def __init__( self : ... | 32 |
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... | 329 | 0 |
"""simple docstring"""
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
__A : Tuple = {
'''User-Agent''': '''Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'''
''' (KHTML, like Gecko) Chrome... | 33 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDep... | 34 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm": ["XLMTokenizer... | 35 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 0 |
from math import pow
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
'''simple docstring'''
if current_sum == needed_sum:
# If the sum of the powers is equal to needed_sum, then we have a soluti... | 36 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
if bit_count < 0:
raise ValueError("""The given input must be positive""" )
# get the generated string sequence
lowerCAmelCase__ : List[str] = gray_code_se... | 37 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 0 |
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 import FlaxAutoModel
from tr... | 38 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 0 |
def __A ( __lowerCAmelCase , __lowerCAmelCase )-> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = (boundary[1] - boundary[0]) / steps
_UpperCAmelCase = boundary[0]
_UpperCAmelCase = boundary[1]
_UpperCAmel... | 39 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 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 transformers.u... | 40 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ (UpperCamelCase ) -> bool:
if not isinstance(UpperCamelCase , UpperCamelCase ):
lowerCamelCase__ : int = f'''Input value of [number={number}] must be an integer'''
... | 41 |
import unittest
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 ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A = 1_000_000 ) -> int:
_snake_case = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , __A ):
phi[j] -= phi[j] // i
return sum(phi[2 : ... | 42 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__lowercase = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__lowercase = [file for file in filepaths if file != file... | 43 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 0 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests
... | 44 |
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.parametrize('revision' ... | 329 | 0 |
"""simple docstring"""
import torch
from torch import nn
class __lowerCAmelCase ( nn.Module ):
'''simple docstring'''
def __init__( self , _a , _a , _a , _a , _a=1 , _a=False ):
super().__init__()
__a = n... | 45 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
... | 46 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 0 |
'''simple docstring'''
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("ignore", category=UserWarning, module="torch.optim.lr_scheduler")
class A__ ... | 47 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 0 |
def A ( _SCREAMING_SNAKE_CASE ) -> Any:
lowerCamelCase : Optional[Any] = []
lowerCamelCase : str = set({"(", "[", "{"} )
lowerCamelCase : int = set({")", "]", "}"} )
lowerCamelCase : Union[str, Any] = ... | 48 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 0 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__snake_case :Any = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__snake_case :str = _LazyModule(__name__, globals()['... | 49 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCAmelCase ( __UpperCamelCase ):
def __init__( self : List[Any] ... | 50 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 0 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weig... | 51 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 0 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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
#
# Unless required by appl... | 52 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
'''simple docstring'''
import torch
from transformers import AutoModel
class snake_case ( torch.nn.Module ):
"""simple docstring"""
def __init__( self : Optional[int] , __A : List[Any]="sayef/fsner-bert-base-uncased" ):
super(__A , sel... | 53 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 0 |
"""simple docstring"""
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
a__ : Dict = '''src/transformers'''
a__ ... | 54 |
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... | 329 | 0 |
'''simple docstring'''
from math import factorial
def __snake_case ( UpperCAmelCase_ : int = 100 ):
return sum(int(UpperCAmelCase_ ) for x in str(factorial(UpperCAmelCase_ ) ) )
if __name__ == "__main__":
print(solution(int(input("""Enter the Number: """).strip()... | 55 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 0 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow ... | 56 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 0 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def _lowerCamelCase ( _UpperCamelCase ):
'''sim... | 57 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpos... | 58 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase ( A_ ):
A__ : Optional[Any] = ["image_processor", "tokenizer"]
A__ : Tuple = "AutoImageProcessor"
A__ : Optional[int] ... | 59 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : List[Any] = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggin... | 60 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 0 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_a = False
class A_ (unittest.TestCase ):
... | 61 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 0 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : str = "" ):
__UpperCamelCase =url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
__UpperCamelCase =BeautifulSoup(request... | 62 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 50 ) -> int:
_a = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 63 |
import unittest
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 ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
A_ = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''LongT5OnnxConfig'''],... | 64 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 0 |
def lowerCAmelCase_ ( __A, __A ) -> float:
'''simple docstring'''
def get_matched_characters(__A, __A ) -> str:
UpperCAmelCase__ = []
UpperCAmelCase__ = min(len(_stra ), len(_stra ) ) // 2
... | 65 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
l... | 66 |
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.parametrize('revision' ... | 329 | 0 |
'''simple docstring'''
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
__UpperCAmelCase =TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("", "|", ... | 67 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
lowerCAmelCase__ ... | 68 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase ( lowerCAmelCase__ ):
def __init__( self, *lowerCAmelCase__, **l... | 69 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffuser... | 70 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 0 |
def A ( a_ ) -> int:
if not isinstance(a_ ,a_ ) or number < 0:
raise ValueError('Input must be a non-negative integer' )
__UpperCamelCase : List[Any] =0
while number:
# This way we arrive at next set bit... | 71 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
"""simple docstring"""
from typing import Any
def snake_case_ ( A_ : list ):
'''simple docstring'''
if not input_list:
return []
_lowerCamelCase : Dict = [input_list.count(A_ ) for value in input_list]
_lowerCamel... | 72 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 0 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a =logging.get_logger(__name__)
a ="""▁"""
a ={"""vocab_file""": """vocab.txt""", """sente... | 73 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 0 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCAmelCase_ :
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : int ,A_ : str ) -> ... | 74 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class __UpperCamelCase :
def __init__( self, lowerCAmelCase ):
"""simple docstring"""
lowerCamelCase_ =list_of_points
... | 75 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 0 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from ... import PreT... | 76 |
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... | 329 | 0 |
"""simple docstring"""
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def a_ ( _lowerCAmelCase : np.ndarray ):
'''simple docstring'''
return input_array.reshape((input_array.siz... | 77 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 0 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_confi... | 78 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase_ = {
'''configuration_jukebox''': [
'''JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''JukeboxConfig''',
'''Ju... | 79 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIP... | 80 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 0 |
"""simple docstring"""
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,
... | 81 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 0 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class __lowerCAmelCase :
__lowerCamelCase = field(
metadata={'''help''': '''The output dir... | 82 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase__ ( lowercase ):
lowercase__ = ["""image_processor""", """tokenizer"""]
lowercase__ = """ViTImageProcessor"""
lowercase__ ... | 83 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 0 |
"""simple docstring"""
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__UpperCAmelCase = 2_99_79_24_58
# Symbols
__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase = symbols('ct x y z')
... | 84 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 85 |
import unittest
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 ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 0 |
"""simple docstring"""
from __future__ import annotations
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
__lowerCAmelCase : List[Any] = []
__lowerCAmelCase , __lowerCAmelCase : Tuple = inpu... | 86 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
... | 87 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 0 |
def a__ ( A_, A_ ):
'''simple docstring'''
return 1 if input_a == input_a else 0
def a__ ( ):
'''simple docstring'''
assert xnor_gate(0, 0 ) == 1
assert xnor_gate(0, 1 ) == 0
assert xnor_gate(1, 0 ) == 0... | 88 |
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.parametrize('revision' ... | 329 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
'''caidas/swin2sr-classicalsr-x2-64''': (
'''https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolv... | 89 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : List[Any] ) -> Optional[int]:
"""simple docstring"""
__lowerCamelCase = []
__lowerCamelCase = []
__lowerCamelCase = {
'^': 3,
'*': 2,
'/': 2,
... | 90 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, fl... | 91 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 0 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE_ : int | float | str , SCREAMING_SNAKE_CASE_ : int | float | str ):
if nth_term == "":
return [""]
__lowerCAmelCase = int(SCREAMING_SNAKE_CASE_ )
__lowerCAmelC... | 92 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowerCAmelCase__ ( unittest.TestCase ):... | 93 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
snake_case : int = loggin... | 94 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 0 |
def _A ( SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
a__ : Optional[int] =[int(SCREAMING_SNAKE_CASE ) for i in ip_va_address.split("." ) if i.isdigit()]
return len(SCREAMING_SNAKE_CASE ) == 4 and all(0 <= int(SCREAMING_SNAK... | 95 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/googl... | 96 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowercase :
"""simple docstring"""
def __init__( self , UpperCamelCase_ ... | 97 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultiste... | 98 |
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... | 329 | 0 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
lowercase : Dict = {
"""t5-small""": """https://huggingface.co/t5... | 99 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 0 |
"""simple docstring"""
from PIL import Image
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ ):
def brightness(UpperCamelCase_ ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise ValueError("""level must be between -255.0 (black) and 255... | 100 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
im... | 101 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 0 |
"""simple docstring"""
def lowercase ( ) ->int:
"""simple docstring"""
return 1
def lowercase ( _snake_case : int ) ->int:
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def lowercase ( _snake_case ... | 102 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 0 |
import math
def UpperCamelCase( __UpperCamelCase : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in for... | 103 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 0 |
'''simple docstring'''
import random
def _A ( A__ , A__ , A__ ):
"""simple docstring"""
__lowercase = a[left_index]
__lowercase = left_index + 1
for j in range(left_index + 1 , A__ ):
if a[j] < pivot:
__lowercase , __lowercase ... | 104 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 0 |
"""simple docstring"""
import math
import sys
def _SCREAMING_SNAKE_CASE ( _lowercase : int ) ->int:
'''simple docstring'''
if number != int(_lowercase ):
raise ValueError("the value of input must be a natural number" )
if num... | 105 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 0 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
while second != 0:
lowerCAmelCase__ : Tuple = first & second
first ^= second
lowerCAmelCase__ : Union[str, Any] = c << 1
return first
if __name__ == "__main__":
import doctest
doctest.test... | 106 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __magic_name__ ( A : NDArray[floataa], A : NDArray[floataa], A : list[int], A : int, ):
'''simple docstring'''
a , a = coefficient_matr... | 107 |
import unittest
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 ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 0 |
"""simple docstring"""
import re
def a__ ( SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
lowerCAmelCase : Tuple = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.search(SCREAMING_SNAKE_CASE ... | 108 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 0 |
"""simple docstring"""
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _snake... | 109 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 0 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import ... | 227 |
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.parametrize('revision' ... | 329 | 0 |
'''simple docstring'''
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
lowercase__ : Union[str, Any] = {
'''User-Agent''': '''Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'''
''' (KHTML, like Gecko) Chrome/70.... | 324 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
from __future__ import annotations
from typing import Any
class _A( snake_case__ ):
"""simple docstring"""
pass
class _A:
"""simple docstring"""
def __init__( self , _A ):
__A : Dict = data
__A : Optional[Any] ... | 280 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 0 |
'''simple docstring'''
def a_ ( _lowerCAmelCase ) -> list:
if any(not isinstance(a__ ,a__ ) or x < 0 for x in sequence ):
raise TypeError('Sequence must be list of non-negative integers' )
for _ in range(len(a__ ) ... | 208 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 0 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
f... | 6 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 0 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils imp... | 36 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
'''simple docstring'''
UpperCAmelCase : Optional[int] = '''Alexander Joslin'''
import operator as op
from .stack import Stack
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {"""*""": op.mul, """/""": op.truediv, """+""": op.add, """-... | 267 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
... | 117 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 0 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase__ ( unittest.TestCase):
def lowercase_ ( self :List[str] ) -> Union[str, Any]:
... | 161 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[Any] = {
'''configuration_longformer''': [
'''LONGFORMER_PRETRAI... | 187 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 0 |
import itertools
import math
def _a ( a :int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All... | 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 is_t... | 329 | 0 |
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