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 |
|---|---|---|---|---|
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
_lowerCAmelCase : Optional[int] = '''facebook/wmt19-en-de'''
_lowerCAmelCase : Optional[Any] = FSMTTokenizer.from_pretrained(mname)
# get the correct vocab sizes, etc. from the master mode... | 454 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/r... | 560 | 0 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_avai... | 319 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Sque... | 319 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from ... | 599 | """simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
... | 277 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
__lowerCAmelCase = 0
__lowerCAmelCase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0,... | 708 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _lowerCAmelCase ( nn.Module ):
__lowerCAmelCase : int
__lowerCAmelCase ... | 396 | 0 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 |
def lowerCAmelCase ( UpperCAmelCase, UpperCAmelCase ) ->list:
"""simple docstring"""
__magic_name__ : Optional[Any] = word.split()
def justify(UpperCAmelCase, UpperCAmelCase, UpperCAmelCase ) -> str:
__mag... | 154 | 0 |
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 tensorflow as tf
from transformers import AutoTokenizer, TFAutoModelForSeqaSeqLM
@req... | 576 | from collections.abc import Sequence
def __lowercase ( _UpperCAmelCase = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__lowercase = nums[0]
for i in range(1 , len(_UpperCAmelCase ) ):
__lowerc... | 576 | 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 .... | 64 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class a__ ( nn.Module ):
def __init__(self : Union[str, Any], __UpperCAmelCase : int = 16, __UpperCAmelCase : int = 88, ... | 507 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import B... | 144 |
import math
UpperCamelCase = 1_0
UpperCamelCase = 7
UpperCamelCase = BALLS_PER_COLOUR * NUM_COLOURS
def _a ( lowerCamelCase__ = 20 ) -> str:
lowerCamelCase_ : List[str] = math.comb(lowerCamelCase__ , lowerCamelCase__ )
lowerCamelCase_ ... | 144 | 1 |
import copy
import random
from transformers import CLIPTokenizer
class A_ ( UpperCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[Any] ,*__A : Any ,**__A : Tuple ) -> Dict... | 67 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A_ ( unittest.TestCas... | 67 | 1 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _a( UpperCamelCase__ : NDArray[floataa], UpperCamelCase__ : NDArray[floataa], UpperCamelCase__ : list[int], UpperCamelCase_... | 665 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _a( UpperCamelCase__ : NDArray[floataa], UpperCamelCase__ : NDArray[floataa], UpperCamelCase__ : list[int], UpperCamelCase_... | 665 | 1 |
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,
PixaStructProcessor,
PixaSt... | 258 |
def lowerCAmelCase_ ( __a , __a ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE : list[list[str]] =[[] for _ in range(__a )]
SCREAMING_SNAKE_CASE : Any =key - 1
if key <= 0:
... | 258 | 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,
)
__UpperCamelCase : int = {
... | 417 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp ... | 417 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_... | 93 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
__A = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""">=""": operator.ge,
"... | 93 | 1 |
"""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,
)
if is_sentencepiece_available():
from ..ta.t... | 51 |
"""simple docstring"""
def lowercase__ ( lowercase_ ,lowercase_ ) -> None:
"""simple docstring"""
_UpperCamelCase : List[Any] = len(lowercase_ )
print("The following activities are selected:" )
# The first activity is always selected
_U... | 51 | 1 |
from typing import List
import numpy as np
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ) -> int:
SCREAMING_SNAKE_CASE_ : Dict = {key: len(SCREAMING_SNAKE_CASE ) for key, value in gen_kwargs.items() if isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )}
if len(set(lists_leng... | 345 |
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
lowerCAmelCase__: int = datasets.logging.get_logger(__name__)
lowerCAmelCase__: Optional[int] = "\\n@InProceedings{moosavi... | 345 | 1 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCAmelCase_ : int = '%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input... | 708 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def A_ ( _lowerCAmelCase : Union[str, Any] ):
"""simple docstring"""
if "img_encoder.pos_embed" in name:
... | 11 | 0 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
_lowercase : Union[str, Any] =collections.namedtuple('''_Datasets'... | 305 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
a : Dict = logging.get_logger(__name__)
a : Tuple = [
["attention", "attn"],
... | 63 | 0 |
def _lowerCAmelCase ( lowerCamelCase__ : int, lowerCamelCase__ : int ) -> bool:
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 708 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import... | 295 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def A (__lowerCamelCase :List[str] ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wik... | 5 |
"""simple docstring"""
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
UpperCAmelCase__ = models.Seque... | 224 | 0 |
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,
BertSelfOutput,
)
from transformers.utils import logging
lo... | 713 |
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_form... | 75 | 0 |
class A :
'''simple docstring'''
def __init__(self : Any , _UpperCAmelCase : str = "" , _UpperCAmelCase : bool = False ) -> None:
"""simple docstring"""
lowercase__ = {}
# A node will be a leaf if the... | 15 |
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 AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER, get... | 493 | 0 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def __lowerCAmelCase ( __magic_name__ ):
_lowercase: Dict = []
_lowercase: List[str] = []
_lowercase: int = ... | 206 |
def __lowerCAmelCase ( __magic_name__ ):
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect number or not...')
_SCREAMING_SNAKE_CASE : str = int(input(... | 206 | 1 |
class SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : Dict ):
SCREAMING_SNAKE_CASE : Optional[int] = {}
def _A ( self : str ):
print(self.vertex )
for i in self.vertex:
... | 62 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
a : Optional[int] = logging.getLogger(__name__)
@dataclass
class _a ( _lowerCAmelCase ... | 556 | 0 |
def lowerCAmelCase_ ( __UpperCAmelCase: Optional[Any] ) -> Any:
stooge(__UpperCAmelCase , 0 , len(__UpperCAmelCase ) - 1 )
return arr
def lowerCAmelCase_ ( __UpperCAmelCase: int , __UpperCAmelCase: str , __UpperCAmelCase: Union[str... | 369 |
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... | 369 | 1 |
import sys
__A = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098711121722383113"
... | 68 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'''kakaobrain/alig... | 52 | 0 |
from collections import deque
from .hash_table import HashTable
class SCREAMING_SNAKE_CASE__ ( __UpperCamelCase ):
def __init__( self : str , *_lowerCAmelCase : str , **_lowerCAmelCase : Union[str, Any] ):
super().__init__(*_lowerCAmelCase , **_lowerCAm... | 720 | from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTes... | 390 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
_UpperCAmelCase : Optional[Any] = {
'''tanreinama/GPTSAN-2.8B-spout_is_uniform''': (
'''https://huggingface.co/tanreinama/GPTSAN... | 72 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_... | 651 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_av... | 700 | '''simple docstring'''
def A_ ( SCREAMING_SNAKE_CASE_ ) ->int:
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise ValueError("""multiplicative_persistence() only accepts integral values""" )
if num < 0:
raise ValueError("""multiplicative_persistence() does not accept n... | 603 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 569 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
snake_case_ = argparse.ArgumentParser()
parser.add_argument(
'--chec... | 421 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {"vo... | 710 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCAmelCase = logging.get_logger(__name__)
class __A ( a ):
"""simple docstring"""
def __init__( self ... | 318 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_ut... | 572 |
'''simple docstring'''
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
_lowerCAmelCase = 0B10_11_00_11_11_10_11_00_10_01_00_00_... | 432 | 0 |
# Copyright 2022 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 required by appl... | 719 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils imp... | 375 | 0 |
"""simple docstring"""
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
__snake_case = logging.get_logger(__name__)
__snake_case ... | 200 |
"""simple docstring"""
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
__snake_case = 'src/transfor... | 200 | 1 |
"""simple docstring"""
from string import ascii_lowercase, ascii_uppercase
def __lowerCamelCase ( SCREAMING_SNAKE_CASE ) -> Optional[Any]:
"""simple docstring"""
if not sentence:
return ""
_UpperCAmelCase = dict(zip(lowerCAmel... | 703 |
"""simple docstring"""
# Copyright 2023 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... | 494 | 0 |
import functools
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
# Validation
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or not all(isinstance(__lowerCAmelCase , __lowerCAmelCase ) for day in days ):
rais... | 33 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
__A = logging.get_logger(__name__)
class lowerCamelCase__ ( lowerCamelCase_ ):
def __init__( self , *SCREAMING_SNAKE_CASE ... | 134 | 0 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def a_ ( lowerCamelCase : Union[dict,... | 513 |
'''simple docstring'''
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__snake_case ="""scheduler_config.json"""
class UpperCAmelCase_ ( __lowercase... | 513 | 1 |
import requests
from bsa import BeautifulSoup
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = BeautifulSoup(requests.get(__SCREAMING_SNAKE_CASE , params=__SCREAMING_SNAKE_CASE ).content , 'html.parser' )
lowercase = ... | 84 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet ... | 108 | 0 |
'''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/lic... | 517 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
_SCREAMING_SNAKE_CASE = False
cla... | 517 | 1 |
def UpperCAmelCase ( UpperCAmelCase )-> int:
'''simple docstring'''
if not isinstance(UpperCAmelCase ,UpperCAmelCase ):
raise TypeError('''Input value must be an \'int\' type''' )
SCREAMING_SNAKE_CASE_ = 0
while number:
position += ... | 393 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from transformers.testi... | 393 | 1 |
'''simple docstring'''
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase( a__):
_SCREAMING_SNAKE_CASE =[
'''decoder.version''',
'''decoder.output_projection.weight''',
... | 712 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def lowerCamelCase( a__ ,a__=() ,a__=None ,a__="no" ,a__="29500"):
_SCREAMING_SNAKE_CASE =False
_SCREAMING_SNAKE_C... | 191 | 0 |
'''simple docstring'''
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def _a ( __lo... | 347 |
'''simple docstring'''
def _a ( __lowerCAmelCase : int , __lowerCAmelCase : int ):
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 347 | 1 |
"""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_modeling_common import ... | 709 | """simple docstring"""
# 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 swi... | 275 | 0 |
def _UpperCAmelCase (UpperCamelCase__ : List[Any] = 1000000 ):
_A : Any = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , UpperCame... | 503 | '''simple docstring'''
import numpy as np
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> str:
__lowerCamelCase = int(np.ceil((x_end - xa) / h ) )
... | 546 | 0 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int = 3, __snake_case : int = 7, __snake_case : int = 1_000_000 ) -> int:
"""simple docstring"""
A__ : int =0
A__ : Tuple =1
for current_denominator in range(1, limit + 1 ):... | 687 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decode... | 687 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def a_ ( __snake_case : Callable , __snake_case : float , __snake_case : float , __snake_case : float , __snake_case : float ) -> np.ndarray:
"""simple docstrin... | 676 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
a_ :... | 676 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"funnel-transformer/small": "https://huggingface.co/funnel-transformer/small/resolve/main/config.json",
"funnel-transformer/small-base": "https://huggingface.co/funnel... | 721 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCAmelCase__(__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,__snake_case ,) -> float | int:
'''simple docstring'''
for nxt, d in graph[v]... | 29 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : Optional[int] = {
'config... | 49 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig... | 130 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ =logging.get_logger(__name__)
UpperCAmelCase__ ={
"microsoft/swinv2-tiny-patch4-window8-256": (
"https://huggingface.co/microsoft/swinv2-tiny-patch4-wi... | 708 |
"""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
if is_torch_available()... | 442 | 0 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> bool:
UpperCAmelCase__ : Dict = len(lowerCAmelCase__ ) + 1
UpperCAmelCase__ : Union[str, Any] = len(lowerCAmelCase__ ) + 1
# dp is a 2d matrix where dp[i][j... | 75 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowercase = logging.get_logger(__name__)
def __UpperCamelCase ( a : Union[tf.Tensor, np.ndarray] ) ->List[in... | 342 | 0 |
"""simple docstring"""
from collections.abc import Sequence
from queue import Queue
class __lowercase :
'''simple docstring'''
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase=None , _Uppe... | 101 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=_UpperCamelCase )
class __lowercase ( _UpperCamelCase ):
... | 101 | 1 |
'''simple docstring'''
def a_ ( UpperCamelCase_ , UpperCamelCase_ ):
return 1 if input_a == input_a else 0
def a_ ( ):
assert xnor_gate(0 , 0 ) == 1
assert xnor_gate(0 , 1 ) == 0
assert xnor_gate(1 , 0 ) == 0
assert xnor_gate(1 ... | 452 |
'''simple docstring'''
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def a_ ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 452 | 1 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...f... | 707 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
"""simple docstring"""
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 a... | 302 | 0 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 647 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logg... | 647 | 1 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils im... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_bert""": ["""B... | 688 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class UpperCamelCase_ ( UpperCAmelCase__ ):
'''simple docstring'''
... | 87 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("""Googling.....""")
A_ : List[str] ="""https://www.google.com/search?q=""" + """ """.join(sys.argv[1:])
A_ : int =r... | 483 | 0 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowerCamelCase__ ( a : Tuple ) -> Union[str, Any]:
"""simple docstring"""... | 718 |
import datasets
from .evaluate import evaluate
snake_case__ = '''\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={EMNLP},
year={2016}
}
'''
snake... | 373 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
a__ : int = logging.get_logger(__name__)
a__ : in... | 188 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
a__ : Optional[int] = TypeVar('T')
class UpperCAmelCase_ ( Generic[T] ):
def __init__( ... | 188 | 1 |
"""simple docstring"""
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
... | 720 |
"""simple docstring"""
from __future__ import annotations
from math import pow, sqrt
def lowercase ( A_ , A_ , A_ )-> dict[str, float]:
'''simple docstring'''
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError("One ... | 135 | 0 |
from __future__ import annotations
class _a :
"""simple docstring"""
def __init__( self : Dict , UpperCAmelCase : int ):
A_ = order
# a_{0} ... a_{k}
A_ = [1.0] + [0.0] * order
# b_{... | 86 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
E... | 86 | 1 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __lowerCamelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowercase__ : List[str] = F"""{sampling_rate}"""
lowercase__ : ... | 715 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://huggingface.co/huggingface/i... | 81 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class UpperCamelCase__ ( __magic_name__ ):
__SCREAMING_SN... | 412 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
ComputeEnvironment,
... | 412 | 1 |
"""simple docstring"""
from __future__ import annotations
import pandas as pd
def __snake_case ( SCREAMING_SNAKE_CASE: list[int] , SCREAMING_SNAKE_CASE: list[int] , SCREAMING_SNAKE_CASE: int ):
"""simple docstring"""
_lowerCAmelC... | 491 |
"""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
if is_torch_available()... | 491 | 1 |
'''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,
PixaStructProcessor,
Pi... | 78 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__a : Optional[Any] = {
"""configuration_distilbert""": [
"... | 606 | 0 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ..... | 716 |
import math
import qiskit
def _lowerCamelCase ( _a = 1 , _a = 1 , _a = 1 ):
"""simple docstring"""
if (
isinstance(_a , _a )
or isinstance(_a , _a )
or isinstance(_a , _a )
):
raise TypeError('''inputs must be integers.''' )
... | 297 | 0 |
'''simple docstring'''
from manim import *
class a_ ( UpperCAmelCase__ ):
def lowercase__ ( self : Optional[int] ):
__snake_case = Rectangle(height=0.5 , width=0.5 )
__snake_case = Rectangle(height=0.46 , width=0.46 ).... | 356 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class a_ ( unittest.TestCase ):
def lowercase__ ( self... | 356 | 1 |
'''simple docstring'''
def snake_case__ ( _A: List[str] , _A: Tuple , _A: int , _A: Dict , _A: Tuple , _A: Optional[Any] ) -> Any:
'''simple docstring'''
if index == r:
for j in range(_A ):
print(data[j] , ... | 605 | '''simple docstring'''
from __future__ import annotations
import time
__lowercase = list[tuple[int, int]]
__lowercase = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, ... | 605 | 1 |
import requests
def _SCREAMING_SNAKE_CASE ( lowercase : str , lowercase : str ):
'''simple docstring'''
lowerCamelCase_ = {'Content-Type': 'application/json'}
lowerCamelCase_ = requests.post(lowercase , json={'... | 70 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE) -> int:
_lowerCamelCase : int = data
_lowerCamelCase : List[str] = None
_lowerCamelCase : Any ... | 88 | 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 = logging.get_logger(__name__)
_a = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
}
... | 711 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 29 | 0 |
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
SCREAMING_... | 79 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Any = {
"""huggingface/informer-tourism-monthly""": (
... | 79 | 1 |
from __future__ import annotations
def lowerCamelCase_ ( UpperCamelCase__ : list[float], UpperCamelCase__ : int ):
'''simple docstring'''
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(UpperCamelCase__ ):
... | 591 | # This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers imp... | 591 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_f... | 505 |
"""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_mobilebert import MobileBertTokenizer
UpperCamelCase : str = logging.ge... | 690 | 0 |
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_xlnet impor... | 712 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
ren... | 207 | 0 |
'''simple docstring'''
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def a__ ( lowercase : Any, lowercase : Dict, lowercase : str ) -> Dict:
... | 98 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ,_UpperCAmelCase : str ) -> list:
_a : Tuple =len(_UpperCAmelCase )
_a : str =[]
for i in range(len(_UpperCAmelCase ) - pat... | 694 | 0 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def snake_case ( a_ ... | 703 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
UpperCamelCase =re.compile(R"([A-Z]+)([A-Z][a-z])")
UpperCamelCase =re.compile(R"([a-z\d])([A-Z])")
UpperCamelCase =re.compile(R"(?<!_)_(?!_)")
UpperCamelCase =re.compile(R"(_{2,})")
UpperCamelCase =... | 543 | 0 |
"""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 im... | 115 |
"""simple docstring"""
from __future__ import annotations
def A_ (__a ):
'''simple docstring'''
A_ = 0.00
A_ = 0
for resistor in resistors:
if resistor <= 0:
A_ = f'Resistor at index {index} has a negative or zero value!'
... | 115 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "LlamaConfig"]... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"""configuration_bert""": ["""B... | 688 | 0 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, T... | 76 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch... | 431 | 0 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = "T5Config"
class __magic_name__ ( _a):
_UpperCAmelCase ... | 713 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __magic_name__ ( _a):
@require_torch
def _UpperCAmelCase ( self : Tuple ):
# this test is a bit tricky since TRAN... | 405 | 0 |
'''simple docstring'''
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 (
Aud... | 75 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : Optional[int] = logging.get_logger(__name__)
A : Dict = {
'''vinvino02/glpn-kitti''': '''https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json''',
# See all GLPN mod... | 176 | 0 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowerCAmelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
imp... | 6 |
'''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_uti... | 6 | 1 |
"""simple docstring"""
def __lowerCamelCase ( a_ : str ) -> bool:
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''') )
def __lowerCamelCase ( a_ : str ) -> bool:
__SCREAMING_SNAKE_CASE :Dict =... | 498 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBacken... | 498 | 1 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A ( A_ : Dict , A_ : Optional[Any]=False ):
snake_case : List[Any] = OmegaConf.load(__UpperCAmelCase )
if display:
... | 713 |
'''simple docstring'''
from __future__ import annotations
import math
def A ( A_ : int ):
if num <= 0:
snake_case : List[Any] = F"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(A_ )
snake_case ... | 555 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__: Optional[Any] = {
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 694 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> int:
if n == 1 or not isinstance(_UpperCAmelCase ,_UpperCAmelCase ):
return 0
elif n == 2:
return 1
else:
_a ... | 694 | 1 |
import math
def SCREAMING_SNAKE_CASE__ ( __a , __a ):
return math.pow(__a , 2 ) - a
def SCREAMING_SNAKE_CASE__ ( __a ):
return 2 * x
def SCREAMING_SNAKE_CASE__ ( __a ):
snake_case_ : List[Any] = 2.0
while start <=... | 534 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class SCREAMING_SNAKE_CASE_ ( unitt... | 534 | 1 |
import datasets
from .evaluate import evaluate
_lowercase = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268},
y... | 659 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> int:
if depth < 0:
raise ValueError("""Depth canno... | 2 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
__... | 2 | 1 |
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 import PaddingStrateg... | 47 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_lowerCamelCase = {'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailabl... | 6 | 0 |
"""simple docstring"""
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torc... | 703 |
"""simple docstring"""
lowercase_ = 8.31_4462 # Unit - J mol-1 K-1
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
"""simple docstring"""
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueError('''Invalid inputs. Enter positiv... | 215 | 0 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
__magic_name__ : Tuple = [int(0.5 * n * (n + 1)) for n in range(1, 1_0_1)]
def UpperCamelCase ():
UpperCamelCase : List[Any] = os.path.dirname(os.path.realpath... | 102 |
def _lowerCamelCase ( __A : int ) -> str:
_UpperCAmelCase : Tuple = int(__A )
if decimal in (0, 1): # Exit cases for the recursion
return str(__A )
_UpperCAmelCase , _UpperCAmelCase : int = divmod(__A , 2 )
... | 485 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCame... | 161 |
import unittest
import numpy as np
def UpperCamelCase( lowercase_ , lowercase_ , lowercase_ , lowercase_ = None , ) -> np.ndarray:
'''simple docstring'''
snake_case_ = np.shape(lowercase_ )
snake_case_ = np.shape(lowercase_ )
... | 161 | 1 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
lowerCam... | 228 |
from PIL import Image
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase ) -> Image:
def brightness(__lowerCAmelCase ) -> float:
return 128 + level + (c - 128)
if not -2_5_5.0 <= level <= 2_5_5.0:
raise Va... | 228 | 1 |
import math
def lowercase_ ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
if (
not isinstance(_UpperCamelCase , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError('''power_factor must be a valid float v... | 711 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self , snake_case_=2 , snake_case_=3 , snake_case_=6_4 , snake_case_=Non... | 527 | 0 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'kwargs, expected' , [
({'num_shards': 0, 'max_num_jobs': 1}, []),
({'num_shards': 10, 'm... | 430 |
'''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... | 430 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
UpperCAmelCase__ = logging.get_logger(__name__)
class a ( _UpperCAmelCase ):
def __init__( self : List[str] , *__lowerCAmelCase : List[Any] , ... | 704 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
"""shi-labs/nat-mini-i... | 275 | 0 |
import argparse
import json
import subprocess
def lowercase__ ( __snake_case : str , __snake_case : Any ):
'''simple docstring'''
UpperCAmelCase_ : List[Any] = []
UpperCAmelCase_ : str = (
F"curl -H \"Accept: appl... | 406 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
__A : List[str] = logging.get_logger(__name__)
__A : Optional[Any] = {
'''Intel/dpt-large''': '''https://huggingface.co/Intel/dpt-large/resolve/main/config.json''',
... | 343 | 0 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def UpperCamelCase__ ( ):
'''simple docstring'''
__lowerCamelCase = [randint(-1000 , 1000 ) for i in range(10 )]
... | 704 |
from ...processing_utils import ProcessorMixin
class UpperCamelCase_ ( __UpperCamelCase ):
"""simple docstring"""
A = ['''image_processor''', '''feature_extractor''']
A = '''TvltImageProcessor'''
A = '''TvltFeatureExtractor'''
def __init__( self ,... | 571 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
lowerCAmelCase__ = {
'configuration_audio_spectrogram_transformer': [
'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIV... | 621 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
fro... | 621 | 1 |
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def __magic_name__( _A ):
'''simple docstring'''
... | 719 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase_ : List[str] = TypeVar('''T''')
lowerCamelCase_ : Optional[int] = TypeVar('''U''')
class _SCREAMING_SNAKE_CASE ( Generic[T, U] ... | 265 | 0 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def UpperCAmelCase__( __UpperCAmelCase : float , __UpperCAmelCase : float , __UpperCAmelCase : bool = False ):
if radian_mode:
r... | 576 | from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
__magic_name__ = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
__magic_name__ = typing.Union[np.floataa, int, float] # noqa: UP007
def Upper... | 576 | 1 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is... | 567 |
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 ImageProcessingSavingTestMixin, prepare_image_i... | 567 | 1 |
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