code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import Padding... | 320 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__snake_case = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
... | 320 | 1 |
"""simple docstring"""
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class _a ... | 350 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from torch... | 211 | 0 |
"""simple docstring"""
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
__UpperCamelCase : Any = datasets.logging.get_logger(__name__)
__UpperCamelCase : Tuple ... | 106 |
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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 226 | 0 |
"""simple docstring"""
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def snake_case__ ( __lowerCamelCase : Any , __lowerCamelCase : Optional[Any] ):
"""simple docs... | 272 |
"""simple docstring"""
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("3.8"):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
_lowerc... | 272 | 1 |
'''simple docstring'''
def _A (lowerCAmelCase__ :int = 1_00 ) -> Optional[int]:
'''simple docstring'''
_a = n * (n + 1) * (2 * n + 1) / 6
_a = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
i... | 168 |
'''simple docstring'''
lowerCAmelCase : Optional[int] =256
# Modulus to hash a string
lowerCAmelCase : Tuple =1_000_003
def UpperCAmelCase_ ( __lowerCamelCase : str ,__lowerCamelCase : str ):
lowercase_ :Dict = len(__lowe... | 223 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch... | 350 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
_A = {'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTConfig', 'ViTOnnxConfig']}
try:
... | 117 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowercase__ : Any = logging.get_logger(__name__)
cl... | 324 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
lowerCAmelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class _lowerCamelC... | 153 | 0 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCAmelCase: Optional[int] = datasets.load_iris()
lowerCAmelCase: List[Any] = np.array(data['data'])
lowerCAmelCase: Union[str, ... | 369 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase: Any = {
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfi... | 96 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m... | 64 |
'''simple docstring'''
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,
)
_SCREAMING_SNAKE_CASE = {"config... | 158 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
... | 287 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
lowercase__ : Optional[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def __ini... | 287 | 1 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _lowerCAmelCase ( _UpperCamelCase : Dict , _UpperCamelCase : Any=False ) -> Optional[Any]:
"""simple docstring"""
... | 47 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MA... | 45 | 0 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
f... | 220 |
'''simple docstring'''
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
Ber... | 220 | 1 |
"""simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Optional[Any] ,_lowerCamelCase : int ) ... | 44 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCamelCase__ = {'UserAgent': UserAgent().random}
def __lowerCAmelCase (__lowerCAmelCase ):
_UpperCAme... | 234 | 0 |
'''simple docstring'''
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( __UpperCAmelCase ):
__SCREAMING_SNAKE_CASE : Union[str, Any] = (KDPMaDiscre... | 353 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import co... | 135 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A_ : Optional[int] = {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}
try... | 165 |
"""simple docstring"""
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class _a ( lowerCAmelCase):
"""simple docstring"""
def lowercase__ ( self : List[Any] , __Upper... | 260 | 0 |
'''simple docstring'''
import random
class UpperCAmelCase_ :
'''simple docstring'''
@staticmethod
def _lowercase ( _lowercase ):
"""simple docstring"""
_lowerCAmelCase = [ord(a_ ) for i in text]
_lowerCAmelCase ... | 359 |
'''simple docstring'''
from __future__ import annotations
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , _lowercase ):
"""simple docstring"""
_lowerCAmelCase = order
# a_{0} ... a_{k}
_low... | 229 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils ... | 56 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/main/conf... | 234 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWi... | 187 |
'''simple docstring'''
from torch import nn
def _snake_case ( _SCREAMING_SNAKE_CASE : Optional[int] ) -> Union[str, Any]:
"""simple docstring"""
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif a... | 187 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_A : Dict =logging.get_logger(__name__)
class _lowercase ( _lowercase ):
def __init__( self: Optional[int] , ... | 41 |
import os
snake_case__ : Any = {'I': 1, 'V': 5, 'X': 10, 'L': 50, 'C': 100, 'D': 500, 'M': 1000}
def _a ( lowerCamelCase: str ) -> int:
'''simple docstring'''
__A = 0
__A = 0
while i... | 117 | 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 import (
FlaxForcedBOS... | 367 |
import os
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
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {... | 116 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase : str , _lowerCamelCase : Union[str, Any] , _lowerCamelCase : Union[str, Any] ) -> Optional[int]:
if days_between_payments <= ... | 183 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}
try:
if not is_... | 96 | 0 |
"""simple docstring"""
import math
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, al... | 352 |
from math import pi
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : int , __magic_name__ : int ) -> float:
"""simple docstring"""
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 62 | 0 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = OrderedDict(
... | 325 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 325 | 1 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also sa... | 266 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class snake_case__ (A__ ):
"""simple docstring"""
def __init__( self , __lowercase , __lowercase ) -> int:
"""simple docstring"""
... | 266 | 1 |
"""simple docstring"""
_UpperCamelCase : List[str] = {
'meter': 'm',
'kilometer': 'km',
'megametre': 'Mm',
'gigametre': 'Gm',
'terametre': 'Tm',
'petametre': 'Pm',
'exametre': 'Em',
'zettametre': 'Zm',
'yottametre': 'Ym',
}
# Exponent of the factor(meter)
_UpperCame... | 220 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def _SCREAMING_SNAKE_CASE ( __snake_case : List[Any] ):... | 220 | 1 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowercase ... | 371 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase : Optional[Any] = '''src/diffusers'''
# Matches is_xxx_available()
lowercase : Any ... | 36 | 0 |
from __future__ import annotations
from random import random
class __snake_case :
'''simple docstring'''
def __init__( self : Any , A : int | None = None ):
__snake_case: Tuple = value
__snake_case: int = random... | 111 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''camembert-base''': '''https://huggingface.co/camembert-... | 135 | 0 |
'''simple docstring'''
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartCo... | 357 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : list ) -> list:
"""simple docstring"""
UpperCAmelCase_ : str = len(_SCREAMING_SNAKE_CASE )
for _ in range(_SCREAMING_SNAKE_CASE ):
for i in range(_ % 2 , arr_size - 1 ... | 67 | 0 |
'''simple docstring'''
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
lowerCamelCase : str = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow(... | 2 |
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __UpperCAmelCase :
def __init__( self: List[str] , UpperCAmelCase_: Dict ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE ... | 306 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
_a = '''2020.9.26'''
_a = '''xcodz-dot, cclaus, dhruvmanila'''
def _A ( UpperCamelCase_ : List[str], UpperCamelCase_ : int, UpperCamelCase_ : Optional[Any], UpperCamelCase_ : Opt... | 358 |
"""simple docstring"""
_a = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
... | 144 | 0 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase__ : str = {
"facebook/mask2former-swin-small-coco-instance": (
"https://huggingface.co/faceboo... | 187 |
def lowerCamelCase__ ( _A ):
'''simple docstring'''
snake_case_ = len(_A )
for i in range(_A ):
for j in range(i + 1 , _A ):
if numbers[j] < numbers[i]:
snake_case_ , snake_case_ = numbers[j], numbers[i]
... | 187 | 1 |
"""simple docstring"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
A : List[str] = re.compile(R"^(?P<major>\d+)" R"\.(?P<minor>\d+)" R"\.(?P<patch>\d+)$")
@total_ordering
@dataclas... | 259 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def _lowerCamelCase ( ):
'''simple docstring'''
__lowerCAmelCase = {}
__lowerCAmelCase = 2
while True:
__lowerCAmelCase = factor_map.pop(_UpperCamelCase ... | 259 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase : Union[str, Any] = {
"""configuration_clap""": [
"""CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
"""ClapAudioConfig""",
"""ClapConfig""",
... | 14 |
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase ) -> int:
"""simple docstring"""
while second != 0:
A : int = first & second
first ^= second
A : Tuple = c << 1
return first
if __name__ == "__main__":
im... | 116 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : List[str] = {
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig',
]
}
try:
if not is_torch_available():
... | 146 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A ( UpperCAmelCase__ ):
'''s... | 146 | 1 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
a__ : Optional[Any] ='''\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'''
a__ : Tuple ='''\nArgs:... | 53 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : int = 10**12 ):
__UpperCamelCase =1
__UpperCamelCase =0
__UpperCamelCase =1
__UpperCamelCase =1
while numerator <= 2 * min_total - 1:
prev_numerator += 2 * numerator
... | 62 | 0 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class _SCREAMING_SNAKE_CASE( A ):
def __init__( self ,SCREAMING_SNAKE... | 239 |
"""simple docstring"""
def __lowerCamelCase ( a_ : int , a_ : int ) -> int:
return int((input_a, input_a).count(0 ) == 0 )
def __lowerCamelCase ( ) -> None:
assert and_gate(0 , 0 ) == 0
... | 239 | 1 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
"""simple docstring"""
__A = word.split()
def justify(__UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> str:
__A = max_width - width
__A ... | 266 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, T... | 266 | 1 |
'''simple docstring'''
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 = logging.get_logger(__name__)
class __magic_name__ :
def __... | 360 |
'''simple docstring'''
lowercase =[0, 2, 4, 6, 8]
lowercase =[1, 3, 5, 7, 9]
def lowerCamelCase__ ( __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : list[int] , __lowerCamelCase : int ):
'''simple docstring'''
i... | 242 | 0 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 117 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
_snake_case = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
">": operator.gt,
}
def A ( _lowerCamel... | 36 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging... | 367 |
"""simple docstring"""
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
_A = logging.getLogger()
@unittest.skip('Temporarily disable the doc tests... | 166 | 0 |
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
a_ = re.compile(r'^(?P<major>\d+)' r'\.(?P<minor>\d+)' r'\.(?P<patch>\d+)$')
@total_ordering
@dataclass
class _lowercase :
lowercase = 42
lowerca... | 175 | '''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 67 | 0 |
import argparse
from collections import defaultdict
import yaml
lowerCamelCase_ = '''docs/source/en/_toctree.yml'''
def UpperCamelCase( lowercase_ ) -> Dict:
'''simple docstring'''
snake_case_ = defaultdict(__UpperCAmelCase )
for doc in model_doc:
... | 352 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def UpperCamelCase( lowercase_ = "" ) -> dict[str, float]:
'''simple docstring'''
snake_case_ = url or """https://www.imdb.com/chart/top/?ref_=nv_mv_250"""
snake_case_ = ... | 34 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ :Any = logging.get_logger(__name__)
A_ :List[str] = {
'''xlm-roberta-base''... | 71 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
... | 144 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__lowerCamelCase = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''LongT5OnnxCon... | 101 |
'''simple docstring'''
import requests
__lowerCamelCase = '''''' # <-- Put your OpenWeatherMap appid here!
__lowerCamelCase = '''https://api.openweathermap.org/data/2.5/'''
def UpperCAmelCase__ ( UpperCAmelCase__ = "Chicago", UpperCAmelCase__ = APPID ) -> dict:
... | 101 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()... | 259 |
def _A ( ):
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :Optional[int] = 1
UpperCamelCase :List[Any] = 2
while i * i <= n:
UpperCamelCase :str ... | 259 | 1 |
def UpperCamelCase ( _a ) -> Optional[Any]:
'''simple docstring'''
return str(UpperCAmelCase_ ) == str(UpperCAmelCase_ )[::-1]
def UpperCamelCase ( _a ) -> int:
'''simple docstring'''
return int(UpperCAm... | 353 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase ( _a , _a , _a ) -> Tuple:
'''si... | 252 | 0 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __magic_name__ ( __lowerCAmelCase , unittest.TestCase):
A: Any = PhobertTokenizer
A: ... | 146 |
def _a ( SCREAMING_SNAKE_CASE : int = 1000000 ):
"""simple docstring"""
UpperCamelCase__ : Any = set(range(3 , SCREAMING_SNAKE_CASE , 2 ) )
primes.add(2 )
for p in range(3 , SCREAMING_SNAKE_CASE , 2 ):
if p not in primes:
continue
... | 146 | 1 |
def lowerCAmelCase_ ( __a ) -> Optional[Any]:
"""simple docstring"""
lowerCamelCase__: Union[str, Any] =[0] * len(a__ )
lowerCamelCase__: List[str] =[]
lowerCamelCase__: Any =[1] * len(a__ )
for values in graph.values():
for i in values:
... | 371 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCAmelCase_ ( __a ) -> int:
"""simple docstring"""
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output... | 273 | 0 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patc... | 239 | '''simple docstring'''
from collections import defaultdict
def lowerCamelCase ( UpperCAmelCase__ : str , UpperCAmelCase__ : str ) -> bool:
lowercase_ : Tuple = first_str.lower().strip()
lowercase_ : List[Any] = ... | 239 | 1 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 267 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class lowerCAmelCase_ ( lowerCamelCase__ ):
'''simple docstring'''
def __init__( ... | 267 | 1 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase , __UpperCamelCase )-> List[Any]:
UpperCamelCase = """"""
for i in table:
res += inp[i - 1]
return res
def lowercase__ ( __UpperCamelCase )-> List[str]:
... | 321 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = 8.31_44_62 # Unit - J mol-1 K-1
def lowercase__ ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase )-> float:
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError("""Invalid in... | 321 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : list[str] | None = None ):
"""simple docstring"""
UpperCAmelCase_ : Any = word_bank or []
# create a table
UpperC... | 356 | '''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ , ... | 274 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, 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_t... | 79 |
'''simple docstring'''
# 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
#
... | 166 | 0 |
"""simple docstring"""
class lowerCamelCase__ : # Public class to implement a graph
"""simple docstring"""
def __init__( self : Optional[Any] , UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : list[list[bool]] ):
'''simple docstrin... | 360 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvaila... | 320 | 0 |
'''simple docstring'''
from math import sqrt
def lowerCAmelCase_ ( snake_case_ : int ) -> int:
'''simple docstring'''
UpperCAmelCase_ = 0
for i in range(1 , int(sqrt(snake_case_ ) + 1 ) ):
if n % i == 0 and i != sqrt(snake_case_ ... | 1 |
'''simple docstring'''
import os
from distutils.util import strtobool
def snake_case_ (_a : Union[str, Any] , _a : List[Any] ):
for e in env_keys:
UpperCAmelCase = int(os.environ.get(_a , -1 ) )
if val >= 0:
return ... | 34 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from... | 370 |
"""simple docstring"""
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase , _UpperCamelCase = None ):
if version.parse(hfh.__version__ ).release < version.parse('0.11.0' ).rel... | 182 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ :Tuple = logging.get_logger(__name__)
lowercase__ :Optional[int] = {
"andreasmadsen/efficient_mlm_m0.40": (
... | 101 |
def UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def UpperCame... | 101 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : Any = {}
class _UpperCAmelCase ( lowerCAmelCase__):
_lowerCAmelCase : List[Any] = ... | 155 |
"""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 ..auto import CONFIG_MAPPING
lowercase__ : List[str] = logging... | 155 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : Any = {
'''kssteven/ibert-ro... | 38 |
"""simple docstring"""
import math
def _snake_case ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
if initial_intensity < 0:
raise ValueError("""The value of intensity cannot be negative""" )
# handling of negative values of ini... | 335 | 0 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, 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_modelin... | 365 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowercase : Any = 'src/transform... | 311 | 0 |
import os
import pytest
from attr import dataclass
lowercase : Any = """us-east-1""" # defaults region
@dataclass
class A__ :
"""simple docstring"""
__A : str
__A : str = '''arn:aws:iam::558105141721:role/sagemaker_execution_role'''
__A : ... | 99 |
from __future__ import annotations
from collections import namedtuple
def __SCREAMING_SNAKE_CASE ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> tuple:
'''simple docstring'''
UpperCAmelCase = namedtuple('''result''' , '''name value''' )
if (vol... | 273 | 0 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def _snake_case ( lowercase__ , lowercase__ , lowercase__ , lowercase__=5 ):
# Adapted from https://github.com/pytorch/fairseq/blob/ma... | 12 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
... | 12 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers... | 267 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise ... | 267 | 1 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> bool:
"""simple docstring"""
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 371 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = False )-> str:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase_ = f"Expected string as input, found {type(SCREAMING_SNAKE_CASE_ )}"
... | 60 | 0 |
from string import ascii_lowercase, ascii_uppercase
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : str ):
if not sentence:
return ""
__UpperCamelCase =dict(zip(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) )
return lower_to_upper.get(sentence[0]... | 62 |
from math import ceil
def __lowerCamelCase ( __a :int = 1_0_0_1 ) -> int:
"""simple docstring"""
A__ = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
A__ = 2 * i + 1
A__ = 2 * i
A__ =... | 274 | 0 |
'''simple docstring'''
def UpperCAmelCase_ ( __lowercase : int ) -> int:
'''simple docstring'''
if not isinstance(__lowercase , __lowercase ):
_UpperCAmelCase = f'Input value of [number={number}] must be an integer'
raise TypeEr... | 156 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import... | 156 | 1 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_available, is_vision_available
... | 9 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case = {
'''configuration_bloom''': ['''BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BloomConfig''', '''BloomOnnxConfig'''],
}... | 320 | 0 |
'''simple docstring'''
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def a__ ( a__ , a__ , a__=None ):
... | 331 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
# TODO: upload to AWS
UpperCAmelCase : Optional[int] = {
'yjernite/retribert-base-uncased': (
'https... | 331 | 1 |
'''simple docstring'''
def snake_case ( UpperCAmelCase )-> Optional[Any]:
"""simple docstring"""
__A = len(_lowercase )
for _ in range(_lowercase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i... | 161 | 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 : Any = {'configuration_mbar... | 182 | 0 |
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCamelCase : List[str] = [
"word_embeddings_layernorm.... | 159 |
_lowerCamelCase : List[Any] = tuple[float, float, float]
_lowerCamelCase : Tuple = tuple[float, float, float]
def _UpperCAmelCase (UpperCamelCase_ : Pointad , UpperCamelCase_ : Pointad ):
'''simple docstring'''
_lowerCAmelCase : Tuple = end_pointa[0] - en... | 159 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a = {
'configuration_clip': ... | 155 |
"""simple docstring"""
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_T... | 155 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: Optional[Any] = logging.get_logger(__name__)
_lowercase: Any = {
"microsoft/git-base": "https://huggingface.co/microsoft/git-base/resolve/main/c... | 71 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def a( A : Optional[Any] ) -> Tuple:
"""simple docstring"""
... | 71 | 1 |
"""simple docstring"""
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __A ( A_ ,unittest.TestCase ):
'''simple docstrin... | 16 |
'''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
from... | 267 | 0 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under gi... | 336 |
"""simple docstring"""
import argparse
from collections import defaultdict
def __SCREAMING_SNAKE_CASE ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ):
_lowercase : str = F"""{file}_{class_name}_{test_n... | 336 | 1 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowerCamelCase__ ( A__ : int , A__ : Optional[int] , A__ : Any , A__ : Any=5 ):
'''simple docstring'''
assert masked_input.count("""<mask>""... | 12 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
UpperCAmelCase_ = logging.get_logger(__name__)
class lowerCamelCase__:
def __init__( self: Any , ... | 12 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.test... | 362 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 0 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from f... | 333 |
"""simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavin... | 60 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slo... | 356 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from ... | 87 | 0 |
def UpperCAmelCase_ ( __lowerCAmelCase ) -> Any:
__lowercase : Union[str, Any] = [0] * len(__lowerCAmelCase )
__lowercase : Optional[int] = []
__lowercase : str = []
__lowercase : Optional[Any] = 0
for values in graph.values()... | 156 |
from __future__ import annotations
from PIL import Image
# Define glider example
__lowerCAmelCase : Optional[int] = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0... | 156 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=A ):
'''simple docstring'''
lowerCAmelCase__ = ["""torch""", """scipy"""]
def __init__( self : Union[str, Any] , *_lowerCAmelCa... | 48 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_efficientformer""": [
"""EFFICIENTFORMER_PRETRAINED_C... | 48 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 .... | 151 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCAmelCase : List[str] = {
"configuration_blenderbot": [
"BLENDERBOT_PRETRAINED_CON... | 236 | 0 |
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Dict:
'''simple docstring'''
SCREAMING_SNAKE_CASE = len(__a ) + 1
SCREAMING_SNAKE_CASE = len(__a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix ... | 350 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_com... | 193 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __lowerCAmelCa... | 159 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
fro... | 159 | 1 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCAmelCase__ ( UpperCAmelCase__, UpperCAmelCase__, UpperCAmelCase__ ) -> List[Any]:
A_ = 0
if start < end:
A_ = randint(UpperCAmelCase__, ... | 101 |
'''simple docstring'''
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 impo... | 101 | 1 |
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def A ( a_ ) -> Union[str, Any]:
... | 71 |
import re
def A ( a_ ) -> bool:
__UpperCamelCase : Any =re.compile(
r'^(?:0|94|\+94|0{2}94)' r'7(0|1|2|4|5|6|7|8)' r'(-| |)' r'\d{7}$' )
return bool(re.search(a_ ,a_ ) )
if __name__ == "__main__":
... | 71 | 1 |
'''simple docstring'''
from math import isqrt
def A__ ( UpperCAmelCase_ ):
return all(number % divisor != 0 for divisor in range(2 , isqrt(_lowercase ) + 1 ) )
def A__ ( UpperCAmelCase_ = 1_0**6 ):
_UpperCamelCase : List[str] = 0
... | 359 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase__ ( lowercase ):
@staticmethod
@abstractmethod
def UpperCamelCase_ ( lowerCamelCase__ : ArgumentParser ):
'''simple docstring'''
raise... | 236 | 0 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since th... | 336 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def a__ ( ) -> tuple[list[int], int]:
UpperCAmelCase : str = [randint(-1_000 , 1_000 ) for i in range(10 )]
UpperCAmelCase : Any = randint(-5_... | 336 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except Optional... | 363 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ : List[Any] , lowerCamelCase__ : List[str] , lowerCamelCase__ : str ):
'''simple docstring'''
lowerCamelCase = 0... | 66 | 0 |
class _SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__(self : Optional[Any] , UpperCAmelCase_ : int) ->Optional[int]:
'''simple docstring'''
lowerCamelCase__: Any =n
lowerCamelCase__: Tuple =[None] * self.n
lowerCamelCase__: ... | 10 |
def lowerCamelCase_ ( UpperCamelCase__ : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 90 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCamelCase : Any = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """... | 363 |
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
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Any = r"""
Args:
input_ids (... | 140 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Dict = {
"microsoft/git-ba... | 93 | 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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_ch... | 87 | 0 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import as... | 348 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
... | 348 | 1 |
from __future__ import annotations
import math
import random
from typing import Any
class UpperCamelCase__ :
'''simple docstring'''
def __init__( self ) -> None:
lowerCamelCase : list[Any] = []
lowerCamelCase : int ... | 48 |
def A ( _SCREAMING_SNAKE_CASE = 100_0000 ) -> int:
lowerCamelCase : Tuple = 1
lowerCamelCase : int = 1
lowerCamelCase : Optional[Any] = {1: 1}
for inputa in range(2 ,_SCREAMING_SNAKE_CASE ):
lowerCa... | 48 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_ ( snake_ca... | 311 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase_ ( snake_case__ = "laptop" ):
'''simple docstring'''
A : Tuple = F'https://www.amazon.i... | 311 | 1 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from... | 18 |
import numpy as np
def UpperCamelCase__( UpperCamelCase__ : np.array )->np.array:
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 193 | 0 |
snake_case : str = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-",
"V": "...-"... | 356 |
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,
)
... | 41 | 0 |
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ ):
'''simple docstring'''
if density <= 0:
raise ValueError('''Impossible fluid density''' )
if bulk_modulus <= 0:
raise ValueError('''Impossible bulk modulus''' )
return (bulk_modulus / density) ** ... | 101 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ :Dict = logging.get_logger(__name__)
lowercase__ :Optional[int] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json",
# See a... | 101 | 1 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ... | 210 |
import random
from typing import Any
def UpperCAmelCase_ ( __UpperCAmelCase : list ) -> list[Any]:
for _ in range(len(__UpperCAmelCase ) ):
SCREAMING_SNAKE_CASE_ = random.randint(0 , len(__UpperCAmelCase ) - 1 )
... | 210 | 1 |
"""simple docstring"""
from collections import deque
from .hash_table import HashTable
class _SCREAMING_SNAKE_CASE ( A__ ):
def __init__( self , *__A , **__A ) -> List[str]:
super().__init__(*__A , **__A )
... | 84 |
import os
from math import logaa
def UpperCAmelCase__ ( lowerCamelCase = "base_exp.txt" ):
lowercase :float = 0
lowercase :str = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(lowerCamelCase ), lowerCamelCase ) ) ):
lowercase , low... | 236 | 0 |
'''simple docstring'''
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_lower... | 368 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...te... | 67 | 0 |
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