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 |
|---|---|---|---|---|
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
f... | 271 |
from importlib import import_module
from .logging import get_logger
A__ = get_logger(__name__)
class a :
def __init__( self :Optional[int] ,__lowercase :List[str] ,__lowercase :Any=None ):
snake_case__ : List[str] = attrs or []... | 230 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase : Any = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"shi-labs/dina... | 316 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
A__ = logging.get_logger(__name__)
... | 230 | 0 |
"""simple docstring"""
from math import ceil, sqrt
def lowerCAmelCase__ ( _UpperCamelCase : Any = 1_0_0_0_0_0_0 ) -> int:
"""simple docstring"""
snake_case = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_wi... | 150 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ... | 230 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class a__ ( __lowerCamelCase ):
_SCREAMING_SNAKE_CASE : int = """WhisperFeatureExtractor"""
_SCREAMING_SNAKE_CASE : Optional[int] = """WhisperTokenizer"""
def __init__( self , _Up... | 250 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class a ( unittest.TestCase ... | 230 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
f... | 183 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
A__ = datasets.logging.get_logger(__name__)
A__ = '''\
@InProceedings{moosavi2019minimum,
author = { Naf... | 230 | 0 |
def lowerCamelCase_ ( _a : int , _a : Tuple ):
'''simple docstring'''
UpperCAmelCase_ : Union[str, Any] = len(__lowerCAmelCase )
UpperCAmelCase_ : Union[str, Any] = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr va... | 345 |
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def _lowerCAmelCase ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ... | 230 | 0 |
'''simple docstring'''
import baseaa
def __lowerCamelCase ( _lowercase ) -> bytes:
return baseaa.aaaencode(string.encode("""utf-8""" ) )
def __lowerCamelCase ( _lowercase ) -> str:
return baseaa.aaadecode(__lowerCAmelCase ).decode("""utf-8""" )
if ... | 265 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching b... | 230 | 0 |
import mpmath # for roots of unity
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self , SCREAMING_SNAKE_CASE__=None , SCREAMING_SNAKE_CASE__=None ):
# Input as list
lowercase : List[str] = list(poly_a or [0] ... | 337 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner im... | 230 | 0 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple do... | 294 |
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 _lowerCAmelCase ( __lowe... | 230 | 0 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenc... | 189 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
A__ = '''http://www.mocksite.com/file1.tx... | 230 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
_a : int = logging.... | 44 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_... | 230 | 0 |
'''simple docstring'''
def UpperCAmelCase_ (__a : Optional[Any] ):
"""simple docstring"""
try:
_a : int = float(__lowerCAmelCase )
except ValueError:
raise ValueError('Please enter a valid number' )
_a : List[Any] = decimal - int(__lowerCAmelCase )
i... | 271 |
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__ = {
'''distilbert-base-uncased''': '''https://huggingfa... | 230 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def A ( snake_case :int , snake_case :Dict , snake_case :Optional[int] , snake_case :Tuple = 1_0_0 , ) -> float:
__UpperCamelCase = x_st... | 316 |
from torch import nn
class a ( nn.Module ):
def __init__( self :Tuple ,__lowercase :Optional[int] ,__lowercase :int ):
super().__init__()
snake_case__ : Optional[Any] = class_size
snake_case__ : Dict = embed_size
... | 230 | 0 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...tes... | 150 |
from math import ceil, sqrt
def _lowerCAmelCase ( __lowerCAmelCase = 1000000 ) -> int:
"""simple docstring"""
snake_case__ : Dict = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
snake_ca... | 230 | 0 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def _A ( snake_case ) -> str:
return "".join(sorted(__lowerCAmelCase ) )
def _A ( snake_case ) -> list[str]:
return word_by_signature[signature(__low... | 250 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_v... | 230 | 0 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase : Any ) -> int:
lowerCamelCase_ = len(__lowerCAmelCase )
lowerCamelCase_ = len(matrix[0] )
lowerCamelCase_ = min(__lowerCAmelCase , __lowerCAmelCase ... | 183 |
import random
from .binary_exp_mod import bin_exp_mod
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase=1000 ) -> str:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
... | 230 | 0 |
from __future__ import annotations
UpperCamelCase_ = '''#'''
class _snake_case :
'''simple docstring'''
def __init__( self: List[Any] ) -> Dict:
UpperCAmelCase_ : dict = {}
def A__ ( self: Union[str, Any] ,lowerCamelCase_: str... | 345 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
... | 230 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a : int = logging.get_logger(__name__)
a : str = {
"""distilbert-base-uncased"""... | 265 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import Iterab... | 230 | 0 |
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->Optional[Any]:
"""simple docstring"""
assert x is not None
assert y is not None
lowercase : List[Any] = len(__lowerCAmelCase )
lowercase : Optional[Any] = len(__lowerCAmelCas... | 337 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A__ = {
'''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
'''tokenization_ctrl''': ['''CTRLTokenizer'''],
}
... | 230 | 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 ... | 294 |
import math
import sys
def _lowerCAmelCase ( __lowerCAmelCase ) -> str:
"""simple docstring"""
snake_case__ : Optional[Any] = ''''''
try:
with open(__lowerCAmelCase , '''rb''' ) as binary_file:
snake_case__ : int ... | 230 | 0 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaT... | 189 |
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
... | 230 | 0 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __A ( __low... | 44 |
A__ = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__ = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__ = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
5: '''Friday''',
6: '''Saturday''',
}
def _... | 230 | 0 |
'''simple docstring'''
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
__lower... | 271 |
from importlib import import_module
from .logging import get_logger
A__ = get_logger(__name__)
class a :
def __init__( self :Optional[int] ,__lowercase :List[str] ,__lowercase :Any=None ):
snake_case__ : List[str] = attrs or []... | 230 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : Any = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Mobil... | 316 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
A__ = logging.get_logger(__name__)
... | 230 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {
"configuration_ernie": ["ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP", "ErnieConfig", "ErnieOnnxConfig"],
... | 150 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ... | 230 | 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 OptionalDependencyNotA... | 250 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class a ( unittest.TestCase ... | 230 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
_SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : Union[str, Any] = ... | 183 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
A__ = datasets.logging.get_logger(__name__)
A__ = '''\
@InProceedings{moosavi2019minimum,
author = { Naf... | 230 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'... | 345 |
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def _lowerCAmelCase ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ... | 230 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : Optional[int] = logging.get_logger(__name__)
a : Dict = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
"""google/fne... | 265 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching b... | 230 | 0 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__a = logging.get_logger(__name__)
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->Tuple:
"""simple docstring"""
lowercase : ... | 337 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner im... | 230 | 0 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 294 |
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 _lowerCAmelCase ( __lowe... | 230 | 0 |
lowerCamelCase : str =[
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
low... | 189 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
A__ = '''http://www.mocksite.com/file1.tx... | 230 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.sc... | 44 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_... | 230 | 0 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
"""The `image_to_image.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionImg2ImgPipeline` instead."""
)
| 271 |
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__ = {
'''distilbert-base-uncased''': '''https://huggingfa... | 230 | 0 |
"""simple docstring"""
import string
from math import logaa
def A ( snake_case :List[str] , snake_case :Union[str, Any] ) -> int:
__UpperCamelCase = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , '' ... | 316 |
from torch import nn
class a ( nn.Module ):
def __init__( self :Tuple ,__lowercase :Optional[int] ,__lowercase :int ):
super().__init__()
snake_case__ : Optional[Any] = class_size
snake_case__ : Dict = embed_size
... | 230 | 0 |
"""simple docstring"""
class lowerCAmelCase_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase ):
"""simple docstring"""
snake_case = size
snake_case = [0] * size
snake_case = [0] * size
@staticmet... | 150 |
from math import ceil, sqrt
def _lowerCAmelCase ( __lowerCAmelCase = 1000000 ) -> int:
"""simple docstring"""
snake_case__ : Dict = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
snake_ca... | 230 | 0 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_... | 250 |
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_available, is_v... | 230 | 0 |
"""simple docstring"""
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIF... | 183 |
import random
from .binary_exp_mod import bin_exp_mod
def _lowerCAmelCase ( __lowerCAmelCase , __lowerCAmelCase=1000 ) -> str:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
... | 230 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( _a : Dict ):
'''simple docstring'''
if len(__lowerCAmelCase ) == 0:
return array
UpperCAmelCase_ : Dict = min(__lowerCAmelCase ), max(__lowerCAmelCase )
# Compute the variables
UpperCAmelCas... | 345 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
... | 230 | 0 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
_A = input("Enter image url: ").strip()
print(f"""Downloading image from {url} ...""")
_A = BeautifulSoup(requests.get(url).content, "html.parser")
# The image URL is in the content field of... | 231 |
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=__a ):
_lowercase =['''torch''']
def __init__( self , *_UpperCamelCase , **_UpperCamelCase ) -> Dict:
requires_backends(self , ["torch"] )
@classmeth... | 231 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
# See all TrOCR models at https://hugg... | 231 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fro... | 231 | 1 |
_A = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-",
"V": "...-", "W": ".--", "X": "-..-", ... | 231 |
import math
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = 0
lowerCAmelCase_ = 0
while num > 0:
lowerCAmelCase_ = num % 8
lowerCAmelCase_ = octal + (remainder * math.floor(math.pow(10 , __lowerCAme... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
def get_matched_characters(__lowerCAmelCase : str , __lowerCAmelCase : str ) -> str:
lowerCAmelCase_ = []
lowerCAmelCase_ = min(len(_stra ) ,... | 231 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=2 , _UpperCamelCase=3 , _UpperCamelCase=64 , _UpperCamelCase=None ) -> ... | 231 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_A = {"configuration_plbart": ["PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP", "PLBartConfig"]}
try:
if not is_sentenc... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {
"configuration_distilbert": [
"DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"... | 231 | 1 |
from __future__ import annotations
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase , _UpperCamelCase ) -> Any:
lowerCAmelCase_ , lowerCAmelCase_ = text, pattern
lowerCAmelCase_ , lowerCAmelCase_ = len(_UpperCamelCase ), len(_Upper... | 231 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See all SEW models at https://huggingface.co... | 231 | 1 |
from pathlib import Path
import fire
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str , __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = Path(__lowerCAmelCase )
lowerCAmelCase_ = Path(__lowerCAmelCase )
... | 231 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that will be used ... | 231 | 1 |
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 = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/config.js... | 231 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interl... | 231 | 1 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _lowerCAmelCase ( pl.LightningModule ):
def __init__( self , _UpperCamelCase ) -> List[str]:
super().__i... | 231 |
from pathlib import Path
import fire
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str , __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = Path(__lowerCAmelCase )
lowerCAmelCase_ = Path(__lowerCAmelCase )
... | 231 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _lowerCAmelCase ( unittest.TestCase ):
... | 231 |
import functools
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase )
lowerCAmelCase_ = len(__lowerCAmelCase )
@functools.cache
def min_distance(__lowerCAmelCase : ... | 231 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
from ... | 231 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytesserac... | 231 | 1 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase ( __a , unittest.TestCase ):
_lowercase =CTRLTokenizer
_lowercase =... | 231 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .... | 231 | 1 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase ( __a , unittest.TestCase ):
_lowercase =PhobertTokenizer
_lowercase =... | 231 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( __lowerCAmelCase : str = "" ):
"""simple docstring"""
lowerCAmelCase_ = url or "https://www.imdb.com/chart/top/?ref_=nv_mv_250"
lowerCAmelCase_ = BeautifulSo... | 231 | 1 |
import functools
def lowerCamelCase__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : list[int] ):
"""simple docstring"""
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or not all(isinstance(__lowerCAmelCase , __lowerCAmelCase ) for day in... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XG... | 231 | 1 |
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 OptionalDependencyNotAvailable:
pass
... | 231 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowerCAmelCase ( __a , unittest.TestCase ):
_lo... | 231 | 1 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from tra... | 231 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _lowerCAmelCase ( pl.LightningModule ):
def __init__( self , _UpperCamelCase ) -> List[str]:
super().__i... | 231 | 1 |
import pytest
_A = "__dummy_dataset1__"
_A = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": REPO_URL + \"wikiann-bn-validation.jsonl\... | 231 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
"""simple docstring"""
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(__lowerCAmelCase , ... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
_A = {
"configuration_speech_to_text": ["SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Spee... | 231 | 1 |
from __future__ import annotations
def lowerCamelCase__ ( __lowerCAmelCase : dict , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ , lowerCAmelCase_ = set(__lowerCAmelCase ), [start]
while stack:
lowerCAmelCase_ = stack.pop()
ex... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_A = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 231 | 1 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 231 |
import requests
_A = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def lowerCamelCase__ ( __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = requests.get(_NEWS_API + bbc_news_api_key ).json()
# each article in the list is a dict
... | 231 | 1 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"huggingface/autoformer-tourism-monthly": "https://huggingface.co/huggingface/autoformer-tourism-monthly/resolve/main/config.json",
}
clas... | 231 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 231 | 1 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytesserac... | 231 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class _lowerCAmelCase ( __a ):
_lowercase ='''megatron-bert'''
def _... | 231 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XG... | 231 |
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=__a ):
_lowercase =['''torch''']
def __init__( self , *_UpperCamelCase , **_UpperCamelCase ) -> Dict:
requires_backends(self , ["torch"] )
@classmeth... | 231 | 1 |
import math
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = 0
lowerCAmelCase_ = 0
while num > 0:
lowerCAmelCase_ = num % 8
lowerCAmelCase_ = octal + (remainder * math.floor(math.pow(10 , __lowerCAme... | 231 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fro... | 231 | 1 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _... | 231 |
import math
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = 0
lowerCAmelCase_ = 0
while num > 0:
lowerCAmelCase_ = num % 8
lowerCAmelCase_ = octal + (remainder * math.floor(math.pow(10 , __lowerCAme... | 231 | 1 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowerCAmelCase ( __a , unittest.TestCase ):
_lo... | 231 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=2 , _UpperCamelCase=3 , _UpperCamelCase=64 , _UpperCamelCase=None ) -> ... | 231 | 1 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils im... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {
"configuration_distilbert": [
"DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"... | 231 | 1 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def lowerCamelCase__ ( __lowerCAmelCase : NDArray[floataa] , __lowerCAmelCase : NDArray[floataa] , __lowerCAmelCase : list[int] , __lowerCAmelCase : int ... | 231 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See all SEW models at https://huggingface.co... | 231 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import Tokeniz... | 231 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that will be used ... | 231 | 1 |
from typing import Any
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase ) -> List[str]:
lowerCAmelCase_ = data
lowerCAmelCase_ = None
class _lowerCAmelCase :
def __init__( self ) -> Optional[Any]:
lower... | 231 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interl... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase )
lowerCAmelCase_ = []
for i in range(len(__lowerCAmelCase ) - pat_len + 1 ):
lowerCAmelCase_ = True
for... | 231 |
from pathlib import Path
import fire
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str , __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = Path(__lowerCAmelCase )
lowerCAmelCase_ = Path(__lowerCAmelCase )
... | 231 | 1 |
from __future__ import annotations
from math import pow, sqrt
def lowerCamelCase__ ( __lowerCAmelCase : float , __lowerCAmelCase : float , __lowerCAmelCase : float ):
"""simple docstring"""
if (resistance, reactance, impedance).count(0 ) != 1:
raise Value... | 231 |
import functools
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase )
lowerCAmelCase_ = len(__lowerCAmelCase )
@functools.cache
def min_distance(__lowerCAmelCase : ... | 231 | 1 |
from __future__ import annotations
from typing import Any
def lowerCamelCase__ ( __lowerCAmelCase : list[Any] ):
"""simple docstring"""
create_state_space_tree(__lowerCAmelCase , [] , 0 )
def lowerCamelCase__ ( __lowerCAmelCase : list[Any] , ... | 231 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytesserac... | 231 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"vocab_file": "vocab.json",
"tokenizer_config_file": "tokenizer_config.json",
"merges_file": "mer... | 231 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .... | 231 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils... | 231 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( __lowerCAmelCase : str = "" ):
"""simple docstring"""
lowerCAmelCase_ = url or "https://www.imdb.com/chart/top/?ref_=nv_mv_250"
lowerCAmelCase_ = BeautifulSo... | 231 | 1 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that will be used ... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XG... | 231 | 1 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def lowerCamelCase__ ( __lowerCAmelCase : List[str] , __lowerCAmelCase ... | 231 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowerCAmelCase ( __a , unittest.TestCase ):
_lo... | 231 | 1 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=2 , _UpperCamelCase=3 , _UpperCamelCase=64 , _UpperCamelCase=None ) -> ... | 231 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _lowerCAmelCase ( pl.LightningModule ):
def __init__( self , _UpperCamelCase ) -> List[str]:
super().__i... | 231 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class _lowerCAmelCase ( unittest.TestCase ):
def __a ... | 231 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 231 | 1 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( __a ):
_lowercase =''''''
_lowercase =(
None # protocol passed in prefix to the url. ex: "gzip", for gzi... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
_A = {
"configuration_speech_to_text": ["SPEECH_TO_TEXT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Spee... | 231 | 1 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTokenizer
else:
_A ... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_A = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 231 | 1 |
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : float | Decimal , __lowerCAmelCase : float = 10**-10 ):
"""simple docstring"""
... | 231 |
import requests
_A = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def lowerCamelCase__ ( __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = requests.get(_NEWS_API + bbc_news_api_key ).json()
# each article in the list is a dict
... | 231 | 1 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common ... | 231 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 231 | 1 |
from __future__ import annotations
_A = 10
def lowerCamelCase__ ( __lowerCAmelCase : list[int] ):
"""simple docstring"""
lowerCAmelCase_ = 1
lowerCAmelCase_ = max(__lowerCAmelCase )
while placement <= max_digit:
# declare and initialize empty buckets
... | 231 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class _lowerCAmelCase ( __a ):
_lowercase ='''megatron-bert'''
def _... | 231 | 1 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( __a ):
_lowercase =(EulerDiscreteScheduler,)
_lowercase =10
def __a ( self , **_Upper... | 231 |
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=__a ):
_lowercase =['''torch''']
def __init__( self , *_UpperCamelCase , **_UpperCamelCase ) -> Dict:
requires_backends(self , ["torch"] )
@classmeth... | 231 | 1 |
import functools
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase )
lowerCAmelCase_ = len(__lowerCAmelCase )
@functools.cache
def min_distance(__lowerCAmelCase : ... | 231 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fro... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : Optional[int] , __lowerCAmelCase : Union[str, Any] , __lowerCAmelCase : Any=False ):
"""simple docstring"""
if isinstance(__lowerCAmelCase , __lowerCAmelCase ) and isinstance(__lowerCAmelCase , __lowerCAmelCa... | 231 |
import math
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = 0
lowerCAmelCase_ = 0
while num > 0:
lowerCAmelCase_ = num % 8
lowerCAmelCase_ = octal + (remainder * math.floor(math.pow(10 , __lowerCAme... | 231 | 1 |
# coding=utf-8
# Copyright 2023 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 applicabl... | 231 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class _lowerCAmelCase :
def __init__( self , _UpperCamelCase=2 , _UpperCamelCase=3 , _UpperCamelCase=64 , _UpperCamelCase=None ) -> ... | 231 | 1 |
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://huggingface.co/models?filter=gpt_neo... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {
"configuration_distilbert": [
"DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"... | 231 | 1 |
from collections.abc import Callable
def lowerCamelCase__ ( __lowerCAmelCase : Callable[[float], float] , __lowerCAmelCase : float , __lowerCAmelCase : float ):
"""simple docstring"""
lowerCAmelCase_ = a
lowerCAmelCase_ = b
if function(__lowerCAmelC... | 231 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json",
# See all SEW models at https://huggingface.co... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
if number > 0:
raise ValueError("input must be a negative integer" )
lowerCAmelCase_ = len(bin(__lowerCAmelCase )[3:] )
lowerCAmelCase_ = bin(abs(__lowerCAmelCase ) - (1 << binary_number_... | 231 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_copies # noqa: E402
# This is the reference code that will be used ... | 231 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
class _l... | 231 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interl... | 231 | 1 |
import math
from collections.abc import Iterator
from itertools import takewhile
def lowerCamelCase__ ( __lowerCAmelCase : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Nega... | 231 |
from pathlib import Path
import fire
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str , __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = Path(__lowerCAmelCase )
lowerCAmelCase_ = Path(__lowerCAmelCase )
... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : str ):
"""simple docstring"""
return " ".join(
"".join(word[::-1] ) if len(__lowerCAmelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words... | 231 |
import functools
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase )
lowerCAmelCase_ = len(__lowerCAmelCase )
@functools.cache
def min_distance(__lowerCAmelCase : ... | 231 | 1 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : Union[str, Any] , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ =... | 231 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytesserac... | 231 | 1 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCamelCase__ ( __lowerCAmelCase : ndarray ):
"""simple docstring"""
return np.dot(__lowerCAmelCase , __lowerCAmelCase )
class _lowerCAmelCase :
... | 231 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from .... | 231 | 1 |
from collections import UserDict
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
... | 231 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( __lowerCAmelCase : str = "" ):
"""simple docstring"""
lowerCAmelCase_ = url or "https://www.imdb.com/chart/top/?ref_=nv_mv_250"
lowerCAmelCase_ = BeautifulSo... | 231 | 1 |
from __future__ import annotations
def lowerCamelCase__ ( __lowerCAmelCase : list[int] , __lowerCAmelCase : int ):
"""simple docstring"""
lowerCAmelCase_ = 0
lowerCAmelCase_ = len(__lowerCAmelCase ) - 1
while i < j:
if nums[i] + nums[j] == target:
... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A = {"configuration_xglm": ["XGLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XG... | 231 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : int = 1000 ):
"""simple docstring"""
lowerCAmelCase_ = 2**power
lowerCAmelCase_ = str(__lowerCAmelCase )
lowerCAmelCase_ = list(__lowerCAmelCase )
lowerCAmelCase_ = 0
for i in list_num:
sum_of_num += int(__... | 231 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowerCAmelCase ( __a , unittest.TestCase ):
_lo... | 231 | 1 |
from math import pow, sqrt
def lowerCamelCase__ ( *__lowerCAmelCase : float ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase ) > 0 and all(value > 0.0 for value in values )
return result
def lowerCamelCase__ ( __lowerCAmelCase : float , ... | 231 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class _lowerCAmelCase ( pl.LightningModule ):
def __init__( self , _UpperCamelCase ) -> List[str]:
super().__i... | 231 | 1 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
)
def low... | 231 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 231 | 1 |
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