code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .... | 576 | 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 import Split, TokenC... | 576 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/L... | 471 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowercase ( a_ ):
pass
class lowercase :
def __init__( self , _snake_case) -> None:
UpperCAmelCase_ : Any = data
Up... | 471 | 1 |
import argparse
import copy
def lowerCAmelCase_ ( lowerCamelCase ):
__magic_name__ : Tuple ={}
with open(lowerCamelCase ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
__magic_name__ : Optiona... | 21 |
'''simple docstring'''
_UpperCAmelCase : Any = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(100000)]
def snake_case__ ( UpperCamelCase ) -> int:
_UpperCamelCase : Any = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.... | 683 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
UpperCamelCase__ = logging.get_logger(__name__)
class __lowercase ( UpperCamelCase__ ):
def __init__( self : Any , *lowercase__ : U... | 710 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
UpperCamelCase__ = (3, 9, -11, 0, 7, 5, 1, -1)
UpperCamelCase__ = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __lowercase :
_lowerCAmelCase ... | 143 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProces... | 109 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
# TODO Update this
a = {
"facebook/esm-1b": "https://huggingface.co/facebook/esm-1b/re... | 109 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __A (UpperCamelC... | 718 | '''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
... | 10 | 0 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_comman... | 28 | def _UpperCamelCase ( snake_case__ ) -> str:
__UpperCAmelCase : Tuple = int(snake_case__ )
if decimal in (0, 1): # Exit cases for the recursion
return str(snake_case__ )
__UpperCAmelCase , __UpperCAmelCase : List[str] = divmo... | 382 | 0 |
def lowercase ( a ):
'''simple docstring'''
if length <= 0 or not isinstance(a , a ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(a )]
if __name__ == "__main__":
print(hexagonal_numbers(length=5))
print(hexagonal_numbe... | 140 |
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class _UpperCAmelCase :
def __init__( self : Tuple , UpperCAmelCase : Collection[float] | None = None):
if components is None:
SCREAMING_... | 140 | 1 |
def lowerCAmelCase_ ( __a ) -> None:
"""simple docstring"""
lowerCamelCase__: List[Any] =generate_pascal_triangle(__a )
for row_idx in range(__a ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=" " )
# Print ... | 59 |
"""simple docstring"""
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class _... | 156 | 0 |
def SCREAMING_SNAKE_CASE_ ( __A : int ) -> Optional[Any]:
"""simple docstring"""
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise ValueError('multiplicative_persistence() only accepts integral values' )
if num <... | 710 |
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 tokeni... | 443 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepE... | 33 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Union[str, Any] = logging.get_logger(__name__)
lowercase_ : Any = {
'''facebook/timesformer''': '''https://huggingface.co/facebook/timesformer... | 572 | 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_sq... | 528 |
'''simple docstring'''
from __future__ import annotations
import time
import numpy as np
UpperCamelCase__: Tuple = [8, 5, 9, 7]
UpperCamelCase__: int = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
Uppe... | 528 | 1 |
"""simple docstring"""
from typing import Any
class a__ :
def __init__( self : List[str] , UpperCamelCase_ : Any):
"""simple docstring"""
__UpperCAmelCase : str = data
__UpperCAmelCase : Optional[Any] = None
... | 77 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a : Optional[Any] = logging.get_logger(__name__)
a : List[str] = {name: getattr(transformers, n... | 679 | 0 |
'''simple docstring'''
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
_a : Optional[Any] = importlib.util.find_spec("s3fs") is not Non... | 720 | '''simple docstring'''
def _lowercase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ) -> bool:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumer... | 10 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def snake_case ( A__ ):
UpperCAmelCase_ : int = int(number**0.5 )
return number == sq * sq
def snake_case ( A__ ,A__ ,A__ ,A__ ,A__ ,A... | 95 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def snake_case ( A__ ):
UpperCAmelCase_ : int = int(number**0.5 )
return number == sq * sq
def snake_case ( A__ ,A__ ,A__ ,A__ ,A__ ,A... | 95 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ = logging.get_logger(__name__)
A__ = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
# See all PEGASUS models at https://huggi... | 49 | def _lowerCamelCase ( a_ : list):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''')
for cell_n in range(1 , len(grid[0])):
grid[0][cell_n] += grid[0][cell_n - 1]
lowerCamelCase :Any = grid[0]
for ... | 49 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class _SCREAMING_SNAKE_CASE ( Generic[T] ):
def __init__( self , lowerCamelCase ):
snake_case__ = data
sna... | 276 |
def SCREAMING_SNAKE_CASE__ ( __lowerCAmelCase ):
if any(not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or x < 0 for x in sequence ):
raise TypeError("Sequence must be list of non-negative integers" )
for _ in range(len(__lowerCAmelCase ) ):
for i, (rod_u... | 276 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_co... | 296 | """simple docstring"""
from math import ceil
def lowerCAmelCase (__UpperCamelCase : List[str] , __UpperCamelCase : Any ):
"""simple docstring"""
__UpperCamelCase =list(range(0 , __UpperCamelCase ) )
__UpperCamelCase =[item for subli... | 296 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_... | 284 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( a_ ):
SCREAMING_SNAKE_CASE : Dict = (DDPMScheduler,)
def _SCREAMING_SNAKE_CASE ( self , **_SCREAMING_SNAKE_CASE ):
... | 284 | 1 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 impo... | 388 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_conf... | 388 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A : Optional[Any] = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFI... | 516 | """simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import On... | 516 | 1 |
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
_A = logging.get_logger(__name__)
def lowercase_ ... | 294 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoMod... | 294 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase__ : List[Any] = {
'microsoft/wavlm-base': 'https://huggingface.... | 614 | '''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
UpperCamelCase__ : str = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __UpperCamel... | 614 | 1 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = r'\n Args:\n inp... | 194 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils... | 194 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A( lowerCamelCase__ ):
"""simple docstring"""
def __in... | 355 |
"""simple docstring"""
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... | 355 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case ( _UpperCamelCase , unittest.TestCase):
__UpperCamelCase ... | 621 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFe... | 621 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
a... | 109 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils... | 109 | 1 |
"""simple docstring"""
def A_ ( _lowerCAmelCase : int = 10_00 ):
"""simple docstring"""
_a , _a = 1, 1
_a = 2
while True:
_a = 0
_a = fa + fa
_a , _a = fa, f
index += 1
... | 701 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def A_ ( _lowerCAmelCase : Dict ):
"""simple docstring"""
if "img_encoder.pos_embed" in name:
_a ... | 285 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __magic_name__ : int = 1000 ) -> int:
lowercase : Optional[Any] =2**power
lowercase : Dict =0
while n:
lowercase , lowercase : Optional[Any] =r + n % 10, n // 10
return r
... | 92 |
'''simple docstring'''
from typing import Union
import fire
import torch
from tqdm import tqdm
def A__ ( __lowerCAmelCase : str , __lowerCAmelCase : str = "cpu" , __lowerCAmelCase : Union[str, None] = None ):
lowerCamelCase__ = torch.load(__lowerCAme... | 50 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, ... | 151 |
from itertools import product
def UpperCamelCase_ ( __a , __a ) -> list[int]:
a__ : Union[str, Any] = sides_number
a__ : Optional[int] = max_face_number * dice_number
a__ : Any = [0] * (max_total + 1)
a__ : Optional[Any... | 151 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
SCREAMING_SNAKE_CASE_ = R'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to con... | 523 | '''simple docstring'''
def UpperCamelCase__ ( _lowercase : List[Any] ) -> Dict:
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
... | 523 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 713 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def SCREAMING_SNAKE_CASE( __UpperCamelCase ) -> int:
a__ : List[Any] = prime_factors(__UpperCamelCase )
if is_square_free(__UpperCamelCase ):
return -1 if len(__UpperCamelCa... | 207 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation impo... | 54 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
__lowercase = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''albert-large-v1... | 370 | 0 |
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_MAPPING,
FEATURE_E... | 657 |
def __lowercase ( __lowerCAmelCase : int ):
if length <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(__lowerCAmelCase )]
if _... | 657 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_... | 167 |
# 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 between checkouts... | 513 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowercase)
class lowerCamelCase__ ( __lowercase):
'''simple docstring'''
_A = field(default='summar... | 701 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import D... | 94 | 0 |
"""simple docstring"""
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRI... | 76 |
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 IterableDataset
from... | 30 | 0 |
'''simple docstring'''
import collections
import importlib.util
import os
import re
from pathlib import Path
__SCREAMING_SNAKE_CASE = 'src/transformers'
# Matches is_xxx_available()
__SCREAMING_SNAKE_CASE = re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_stru... | 712 |
'''simple docstring'''
import numpy as np
def __a ( lowerCAmelCase__ : np.array ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 340 | 0 |
"""simple docstring"""
A: List[str] = 'Alexander Joslin'
import operator as op
from .stack import Stack
def _snake_case ( UpperCamelCase : Union[str, Any] ):
UpperCAmelCase : Dict = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-''': op.sub}
UpperCAmelCas... | 160 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase : Any ={
'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Llama... | 696 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 548 |
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,
require_t... | 548 | 1 |
'''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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
Ima... | 467 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table ... | 467 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = """▁"""
... | 488 |
import qiskit
def lowerCamelCase__ ( lowercase , lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : List[str] = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
SCREAMING_SNAKE_CASE : Dict ... | 488 | 1 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE = 1000 ) ->int:
"""simple docstring"""
lowerCAmelCase__ :List[str] = 3
lowerCAmelCase__ :str = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
resul... | 93 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase: Optional[int] = logging.get_logger(__name__)
lowerCAmelCase: int = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class a__( lowerCamelCase__ )... | 526 | 0 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # He... | 703 |
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,
)
UpperCAmelCase = {
"""configuration_xlm_... | 351 | 0 |
'''simple docstring'''
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 _a ( __lowerCAmelCase : Optional[int] , __... | 347 |
'''simple docstring'''
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
... | 347 | 1 |
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...test_pi... | 367 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging... | 367 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified... | 142 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , ... | 142 | 1 |
def __lowerCamelCase ( snake_case__ ) -> Tuple:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = [0 for i in range(len(snake_case__ ) )]
# initialize interval's left pointer and right pointer
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 0... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __UpperCAmelCase (_UpperCAmelCase ):... | 569 | 0 |
# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | 84 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class __A( nn.Module ):
... | 219 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 719 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_barthez import B... | 604 | 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 impo... | 592 |
def lowerCamelCase__ ( snake_case_ : Dict=2_8123 ) -> Tuple:
__snake_case = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ):
sum_divs[k * i] += k + i
__... | 592 | 1 |
'''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,
... | 702 |
'''simple docstring'''
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as ... | 434 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ = {'''configuration_plbart''': ['''PLBART_PRETRAINED_C... | 75 |
import collections
import os
import re
from pathlib import Path
lowerCamelCase_ : Optional[Any] = """src/transformers"""
# Matches is_xxx_available()
lowerCamelCase_ : Union[str, Any] = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCamelCase_ : i... | 548 | 0 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__magic_name__ : Tuple = logging.get_logger(__name__)
def lowerCAme... | 608 |
import math
def lowerCAmelCase ( snake_case__ : int )-> str:
A_ = 0
A_ = 0
while num > 0:
A_ = num % 8
A_ = octal + (remainder * math.floor(math.pow(10 , snake_case__ ) ))
counter += 1... | 608 | 1 |
def __a ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return number | (1 << position)
def __a ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return number & ~(1 << position)
def __a ( __lowerCAmelCase , __lowerCAmelCase )... | 352 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_lowerCamelCase : List[str] = """\
"""
_lowerCamelCase : Optional[int] = """
Perplexity (PPL... | 352 | 1 |
class _UpperCamelCase :
"""simple docstring"""
def __init__( self ) -> Optional[Any]:
A = 0
A = 0
A = {}
def _UpperCAmelCase ( self , a__ ) -> Union[str, Any]:
if vertex not in self.adjacency:
A ... | 546 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def _lowerCAmelCase ( UpperCamelCase__: Any ) -> Tuple:
"""simple docstring"""
def wrapper(*UpperCamelCase__: Union[str, Any] ... | 546 | 1 |
from itertools import product
def __lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase ) -> list[int]:
'''simple docstring'''
lowerCamelCase__: Any = sides_number
lowerCamelCase__: int = max_face_number * dice_number
... | 306 |
_lowercase = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
_lowercase = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def __lowerCAmelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ) -> list[int]:
'''simple docstring'''
... | 306 | 1 |
'''simple docstring'''
from __future__ import annotations
__A : Union[str, Any] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowerCamelCase_ ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , ... | 187 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__A : ... | 187 | 1 |
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def snake_case ( lowerCamelCase = 8 ):
'''simple docstring'''
__lowercase = ascii_letters + digits + punctuation
return "".join(secrets.choice(... | 80 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase :List[Any] = logging.get_logger(__name__)
_lowerCAmelCase :Tuple = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.j... | 251 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import ... | 400 |
from collections.abc import Callable
def _lowercase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ ) -> float:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = a
SCREAMING_SNAKE_CASE__ = b
if function(UpperCamelCase_ ) == 0: # one of the a ... | 400 | 1 |
'''simple docstring'''
from maths.prime_check import is_prime
def snake_case__ ( _A: int ) -> int:
'''simple docstring'''
if not isinstance(__snake_case , __snake_case ):
lowerCAmelCase = f"Input value of [number={number}] must be an integer"
raise Typ... | 370 |
'''simple docstring'''
from collections.abc import Sequence
def a_ ( __snake_case : Sequence[float] , __snake_case : float ) -> float:
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(__snake_case ) )
def a_ ( __snake_case : Se... | 676 | 0 |
'''simple docstring'''
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuratio... | 417 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : Any = logging.get_logger(__name__)
# TODO Update this
__UpperCamelCase : int =... | 417 | 1 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelC... | 152 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase__ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available():
raise ... | 581 | 0 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_a : Tuple= logging.get_logger(__name__)
_a : str= {
"vocab_file": "vocab.json",
"merg... | 192 | """simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
_a : List[str]= yaml.safe_load(
"\\nname: \"\"\nallow_empty: false\nallow_empty_text: ... | 192 | 1 |
'''simple docstring'''
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 between checkouts and running tests.
snake_case_ = abspath(join(dirname(dirname(dirname(__f... | 507 | '''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_UpperCamelCase : str = logging.get_logger(__name__)
class _lowercase( _lowerCamelCase ):
"""simple docstring"""
def __init__( self: List[Any... | 396 | 0 |
"""simple docstring"""
from functools import reduce
a__ : List[str] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""1254069874715852386305071569... | 309 |
"""simple docstring"""
import operator as op
a__ : Optional[int] = """scaler.pt"""
a__ : Dict = """pytorch_model"""
a__ : List[Any] = """random_states"""
a__ : Union[str, Any] = """optimizer"""
a__ : Tuple = """scheduler"""
a... | 309 | 1 |
from heapq import heappop, heappush
import numpy as np
def __lowerCAmelCase ( A , A , A , A , ):
UpperCAmelCase_ , UpperCAmelCase_ = grid.shape
UpperCAmelCase_ = [-1, 1, 0, 0]
UpperCAmelCase_ = [0, 0, -1, 1]
if allow_diago... | 162 |
from __future__ import annotations
import pandas as pd
def __lowerCAmelCase ( A , A , A ):
UpperCAmelCase_ = [0] * no_of_processes
UpperCAmelCase_ = [0] * no_of_processes
# Copy the burst time into remaining_time[]
for i in range(A ):
UpperCAmelC... | 162 | 1 |
'''simple docstring'''
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class lowercase (... | 280 |
'''simple docstring'''
import json
import sys
def a ( __a , __a ) -> str:
'''simple docstring'''
with open(__a , encoding='''utf-8''' ) as f:
UpperCamelCase__ :List[str] = json.load(__a )
UpperCamelCase__ :int ... | 280 | 1 |
'''simple docstring'''
from PIL import Image
def A_( A : Image , A : float):
def brightness(A : int) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise ValueError('level must be between -255.0 (... | 3 |
'''simple docstring'''
def lowerCamelCase ( lowerCAmelCase : str ):
"""simple docstring"""
__magic_name__ : str = 0
# if input_string is "aba" than new_input_string become "a|b|a"
__magic_name__ : Optional[Any] = ''
__magic_name__ : Optio... | 561 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full RobertaForMaskedLM or GPT2LMHea... | 88 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( __magic_name__ : list[list[int]] ) -> bool:
lowercase : str =len(__magic_name__ )
# We need to create solution object to save path.
lowercase : int =[[0 f... | 88 | 1 |
'''simple docstring'''
def _UpperCAmelCase ( ) -> Tuple:
_lowerCAmelCase : List[Any] = 0
for i in range(1 , 10_01 ):
total += i**i
return str(_lowerCamelCase )[-10:]
if __name__ == "__main__":
print(solution())
| 384 | from __future__ import annotations
import math
A_ = "2020.9.26"
A_ = "xcodz-dot, cclaus, dhruvmanila"
def __UpperCAmelCase ( UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase, UpperCAmelCase )-> tuple[float, float]:
"""simple docs... | 604 | 0 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from diffus... | 127 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
lowercase_: List[Any] = logging.get_logger(__name__)
class lowercase__ :
"""simple docst... | 127 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def A_ ( lowercase_ ) -> str:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Uni... | 326 |
lowerCAmelCase_ = {
0: "0",
1: "1",
2: "2",
3: "3",
4: "4",
5: "5",
6: "6",
7: "7",
8: "8",
9: "9",
1_0: "a",
1_1: "b",
1_2: "c",
1_3: "d",
1_4: "e",
1_5: "f",
}
def A_ ( lowercase_ ) -> str:
assert type(lowercase_ ) in... | 326 | 1 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class __lowercase ( lowerCamelCase__ ):
__UpperCAmelCase = CustomTokenizer
pass
| 676 |
def A ( snake_case__ : int ) -> bool:
'''simple docstring'''
if not isinstance(snake_case__ , snake_case__ ):
__snake_case = f"Input value of [number={number}] must be an integer"
raise TypeError(snake_case__ )
if number < 0:
return Fal... | 676 | 1 |
import os
import re
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 logging
UpperCamelCase_ : Optional[int] = logging.get_logger(__name__)
UpperC... | 461 |
from __future__ import annotations
def UpperCamelCase ( _UpperCAmelCase : str , _UpperCAmelCase : list[str] | None = None ) -> list[list[str]]:
'''simple docstring'''
_lowercase : Dict = word_bank or []
# create a table
_lowercase : int... | 461 | 1 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__lowerCamelCase = '''\
'''
__lowerCamelCase = '''
Perplexity (PPL) is one of the most common metrics for evaluat... | 708 |
import operator
def _snake_case ( __snake_case , __snake_case = False , __snake_case = None ) -> list:
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = operator.lt if reverse else operator.gt
UpperCAmelCase_ : int = so... | 455 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> int:
"""simple docstring"""
if not isinstance(lowercase_ , lowercase_ ):
raise TypeError('''Input value must be an \'int\' type''' )
A__ = 0
while number:
position += 1
... | 87 | import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTeste... | 221 | 0 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStruct... | 716 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
_UpperCAmelCase = {"""configuration_dpt""": ["""DPT_PRETRAINED_CONFIG_ARCHIVE_MAP"""... | 36 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__a )
class _SCREAMING_SNAKE_CASE ( __a ):
__SCREAMING_SNAKE_CASE :str ... | 432 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def UpperCamelCase ( a , a , a ) -> float:
'''simple docstring'''
__magic_name__ = x
__magic_name__ = y
for step in range(a ): # noqa: B007
__ma... | 432 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCamelCase_(__SCREAMING_SNAKE_CASE = 1_000_000 , __SCREAMING_SNAKE_CASE = 10 )-> str:
_SCREAMING_SNAKE_CASE : defaultdict = defaultdict(__lowercase )
for outer_width in range(3... | 704 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase_ = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSp... | 635 | 0 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class lowerCAmelCase_ ( unittest.TestCa... | 395 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
snake_case__ = logging.getLogger()
@unittest.skip('Temporarily disable the doc tests.')
@require_t... | 395 | 1 |
"""simple docstring"""
def _snake_case ( UpperCamelCase : int = 1000 ):
UpperCAmelCase : Optional[int] = 2**power
UpperCAmelCase : Optional[Any] = str(UpperCamelCase )
UpperCAmelCase : Union[str, Any] = list(UpperCamelCase )
UpperCAmelCase : Dict = 0
for i ... | 359 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _snake_case ( UpperCamelCase : str = "AAPL" ):
UpperCAmelCase : Any = F"https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"
UpperCAmelCase : Optional[int] = BeautifulSoup(requests.get(UpperCamelCase ).text ... | 359 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless... | 485 |
import argparse
import collections
import os
import re
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_table.py
SCREAMING_SNAKE_CASE = 'src/transfo... | 485 | 1 |
import math
def __lowerCAmelCase ( __snake_case ):
__lowerCAmelCase = 0
__lowerCAmelCase = 0
while num > 0:
__lowerCAmelCase = num % 8
__lowerCAmelCase = octal + (remainder * math.floor(math.pow(10 , __s... | 290 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : int = logging.get_logger(__name__)
lowerCamelCase : Tuple = {
'''caidas/swin2sr-classicalsr-x2-64''': (
'''https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/m... | 290 | 1 |
def A ( ) -> Optional[Any]:
UpperCamelCase__ :int = 0
for i in range(1 , 1001 ):
total += i**i
return str(lowercase__ )[-10:]
if __name__ == "__main__":
print(solution()) | 45 |
'''simple docstring'''
from __future__ import annotations
__UpperCAmelCase = list[list[int]]
# assigning initial values to the grid
__UpperCAmelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0... | 90 | 0 |
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
_lowerCAmelCase : int = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def lowerCamelCase_( _lower... | 719 |
"""simple docstring"""
import unittest
from transformers import LiltConfig, 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... | 386 | 0 |
'''simple docstring'''
import os
def _UpperCamelCase ( ) -> Union[str, Any]:
with open(os.path.dirname(__UpperCamelCase ) + '/grid.txt' ) as f:
lowerCamelCase_ = [] # noqa: E741
for _ in range(20 ):
l.append([int(__UpperCamelCase ) for x in f.r... | 42 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@r... | 333 | 0 |
'''simple docstring'''
import inspect
import re
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_config_docstrings.py
lowerCAmelCase : Union[str,... | 630 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfi... | 630 | 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_d... | 47 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_... | 298 | 0 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
UpperCamelCase__ :... | 496 | '''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ : Optional[Any] ... | 496 | 1 |
import argparse
from collections import defaultdict
def lowerCAmelCase_ ( __a , __a , __a , __a , __a ) -> Optional[int]:
"""simple docstring"""
lowerCamelCase__: str =F"""{file}_{class_name}_{test_name}"""
done_test[_id] ... | 59 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
snake_case_ : Tuple = loggin... | 212 | 0 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class SCREAMING_SNAKE_CASE_ ( _a ):
"""simple docstring"""
def UpperCamelCase__ ( self :Any, snake_case :str):
"""simple docstring"""
... | 557 |
from math import isqrt, loga
def _snake_case (_snake_case : int) -> list[int]:
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1) + 1):
if is_prime[i]:
for j in range(i**2 , _snake_case , _snake_case):
... | 557 | 1 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def A__ ( self ) -> Any:
__lowerCAmelCase = [
... | 465 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 0 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCamelCase ( lowercase_ = 3 ) -> str:
'''simple docstring'''
if isinstance(lowerCAmelCase__ , lowerCAmelCas... | 714 |
import argparse
import os
import re
lowerCamelCase__ : List[Any] = """src/transformers"""
# Pattern that looks at the indentation in a line.
lowerCamelCase__ : Union[str, Any] = re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
lowerCamel... | 495 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Tuple ={
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TimeSeriesTransform... | 54 |
from __future__ import annotations
def a__ ( lowercase__ , lowercase__ ):
'''simple docstring'''
if b == 0:
return (1, 0)
((UpperCAmelCase_) , (UpperCAmelCase_)) =extended_euclid(lowercase__ , a % b )
UpperCAmelC... | 54 | 1 |
'''simple docstring'''
def __A ( _SCREAMING_SNAKE_CASE : Dict ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : List[Any] = 0
__SCREAMING_SNAKE_CASE : Tuple = len(_SCREAMING_SNAKE_CASE )
... | 564 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base impo... | 564 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase__ )
class SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ ):
"""simple docstring"""
lower... | 327 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffusers.sched... | 327 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase = logging.get_logger(__name__)
class lowerCamelCase ( _A ):
def __init__( self , *a_ , **a_ ):
warnings.w... | 551 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlo... | 551 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class SCREAMING_SNAKE_CASE ( snake_case_ ):
def __init__( self : Optional[Any] ):
'''simple docstring'''
self.test()
... | 442 |
'''simple docstring'''
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transform... | 442 | 1 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # noqa: F401 # Here to have a nice mi... | 390 | from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class SCREAMING_SNAKE_CASE__ ( __UpperCamelCase ):
def __lt__( self : Tuple , _lowerCAmelCase : Optional[int] ):
ret... | 390 | 1 |
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