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 |
|---|---|---|---|---|
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[Any] =logging.get_logger(__name__)
__snake_case : Optional[Any] ={'vocab_file': 'vocab.json'}
__snake_case : Optional[int] ={
'v... | 94 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( lowerCamelCase_ : ndarray):
'''simple docstring'''
return np.dot(lowerCamelCase_ ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstri... | 94 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase_ : float ,lowerCamelCase_ : float ,lowerCamelCase_ : float ,):
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0) != 1:
raise ValueError('''You cannot supply more or less tha... | 94 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int] ,lowerCamelCase_ : List[Any]=1024 ,lowerCamelCase_ : in... | 94 | 1 |
from __future__ import annotations
__snake_case : Optional[Any] =tuple[int, int, int]
__snake_case : str =tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
__snake_case : List[Any] ='ABCDEFGHIJKLMNOPQRSTUVWXYZ'
# -------------------------- default selec... | 94 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 94 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : Optional[int] ={
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBertConfig',
'Squeeze... | 94 |
import string
import numpy
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =string... | 94 | 1 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
__snake_case : Union[str, Any] =TypeVar('T')
__snake_case : Tuple =Union[List[T], Tuple[T, ...]]
__snake_case : Union[str, Any] =Union[T, List[T], Dict[str, T]]
__snake_case : Tuple =Union[str, bytes, os.PathLike]
| 94 |
__snake_case : Any ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : Tuple =[{'type':... | 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return int((input_a, input_a).count(1) != 0)
def lowerCAmelCase__ ( ):
'''simple docstring'''
assert or_gate(0 ,0) == 0
assert or_gate(0 ,1) == 1
assert or_gate(... | 94 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 94 | 1 |
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
snake_case_ =(DDPMParallelScheduler,)
def lowerCAmelCase__ (self ,**__lowerCamelCase ) -> ... | 94 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransform... | 94 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResamp... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : int = 1, 1
lowerCAmelCase__ : Any = 2
while True:
lowerCAmelCase__ : Optional[Any] = 0
... | 94 | 1 |
import math
from collections.abc import Iterator
from itertools import takewhile
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Any ={
'configuration_blenderbot_small': [
'BLENDERBOT_SMALL_PRETRAINED_C... | 94 | 1 |
from maths.prime_factors import prime_factors
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
if not isinstance(lowerCamelCase_ ,lowerCamelCase_):
lowerCAmelCase__ : Dict = f"""Input value of [number={number}] must be an integer"""
... | 94 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 94 | 1 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
__snake_case : Tuple ='\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indi... | 94 |
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltF... | 94 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str = "The quick brown fox jumps over the lazy dog" ,):
'''simple docstring'''
lowerCAmelCase__ : Any = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : List[Any] = input_str.re... | 94 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase__ ( ):
'''simple docstring'''
print('''Making key files...''')
make_key_files('''rsa''' ,1024)
print('''Key f... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
while b:
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = b, a % b
return a
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase... | 94 | 1 |
from jiwer import compute_measures
import datasets
__snake_case : Any ='\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved evaluation measures for... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000000):
'''simple docstring'''
lowerCAmelCase__ : int = set(range(3 ,lowerCamelCase_ ,2))
primes.add(2)
for p in range(3 ,lowerCamelCase_ ,2):
if p not in primes:
continue
primes.differ... | 94 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
snake_case_ ="""ClapFeatureExtractor"""
snake_case_ =("""RobertaTokenizer""", """RobertaTokenizerFast""")
de... | 94 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Any =logging.get_logger(__name__)
__snake_case : Tuple ={
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://huggi... | 94 | 1 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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
__snake... | 94 |
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase_ : int = 100):
'''simple docstring'''
return sum(map(lowerCamelCase_ ,str(factorial(lowerCamelCase_))))
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 94 | 1 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
__snake_case : Dict ='\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2... | 94 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_G... | 94 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : List[str] =logging.get_logger(__name__)
__snake_case : Union[str, Any] ={
'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
'microsoft/markuplm-lar... | 94 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCamelCase__ ( nn.Module):
'''simple docstring'''
snake_case_ =42
snake_case_ =jnp.floataa
def lowerCAmelCase__ (self ) -> List[str]:
"""simple docstring"""
lowerCAmelCase... | 94 | 1 |
from timeit import timeit
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
if number < 0:
raise ValueError('''the value of input must not be negative''')
lowerCAmelCase__ : Any = 0
while number:
number &= number - 1
... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case : Optional[int] ={
'configuration_vision_text_dual_encoder': ['VisionTextDualEncoderConfig'],
'processing_vi... | 94 | 1 |
import math
from collections import defaultdict
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 KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def lowerCAmelCase__... | 94 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case : Dict =HfArgumentParser(InitializationArguments)
__snake_case : Tuple =parser.parse_args()
# Load codeparrot tokenizer trained for Pyth... | 94 | 1 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accele... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
lowerCAmelCase__ : str = len(lowerCamelCase_)
lowerCAmelCase__ : Union[str, Any] ... | 94 | 1 |
import math
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase=0 ) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
lowerCAmelCase__ : int = n
lowerCAmelCase__ : List[str] ... | 94 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case : str ={
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ConditionalDetrConfig',
'Conditi... | 94 | 1 |
import warnings
from .generation import TFGenerationMixin
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed in Transformers ... | 94 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( lowerCamelCase_ : ndarray):
'''simple docstring'''
return np.dot(lowerCamelCase_ ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstri... | 94 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase_ : dict ,lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = set(lowerCamelCase_), [start]
while stack:
lowerCAmelCase__ ... | 94 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int] ,lowerCamelCase_ : List[Any]=1024 ,lowerCamelCase_ : in... | 94 | 1 |
import os
from distutils.util import strtobool
def lowerCAmelCase__ ( lowerCamelCase_ : Tuple ,lowerCamelCase_ : List[str]):
'''simple docstring'''
for e in env_keys:
lowerCAmelCase__ : str = int(os.environ.get(lowerCamelCase_ ,-1))
if val >= 0:
... | 94 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : bool = False):
'''simple docstring'''
if not isinstance(lowerCamelCase_ ,lowerCamelCase_):
lowerCAmelCase__ : int = f"""Expected string as input, found {type(lowerCamelCase_)}"""
raise Val... | 94 |
import string
import numpy
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =string... | 94 | 1 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
__snake_case : Union[str, Any] =logging.getLogger()
@unittest.skip("""Temporarily disable the doc test... | 94 |
__snake_case : Any ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : Tuple =[{'type':... | 94 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case : Dict =HfArgumentParser(InitializationArguments)
__snake_case : Tuple =parser.parse_args()
# Load codeparrot tokenizer trained for Pyth... | 94 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 94 | 1 |
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,
EulerDiscreteS... | 94 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransform... | 94 | 1 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : int = 1, 1
lowerCAmelCase__ : Any = 2
while True:
lowerCAmelCase__ : Optional[Any] = 0
... | 94 | 1 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
__snake_case : str =datasets.utils.logging.get_logger(__name__)
@dataclass
class lowerCamelCase__ ( dat... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Any ={
'configuration_blenderbot_small': [
'BLENDERBOT_SMALL_PRETRAINED_C... | 94 | 1 |
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditionalGeneration, BartTokeniz... | 94 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 94 | 1 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
snake_case_ ="""Speech2TextFeatureExtractor"""
snake_case_ ="""Speech2TextTokenizer"""
def __init__(self ... | 94 |
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltF... | 94 | 1 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase ,__lowerCamelCase ,__lowerCamelCase ) -> Dict:
"""simple docstring"""
if dst_width < 0 or dst_height ... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str = "The quick brown fox jumps over the lazy dog" ,):
'''simple docstring'''
lowerCAmelCase__ : Any = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : List[Any] = input_str.re... | 94 | 1 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowerCAmelCase__ ( ):
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dir... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
while b:
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = b, a % b
return a
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase... | 94 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__snake... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000000):
'''simple docstring'''
lowerCAmelCase__ : int = set(range(3 ,lowerCamelCase_ ,2))
primes.add(2)
for p in range(3 ,lowerCamelCase_ ,2):
if p not in primes:
continue
primes.differ... | 94 | 1 |
import baseaa
def lowerCAmelCase__ ( lowerCamelCase_ : str):
'''simple docstring'''
return baseaa.baaencode(string.encode('''utf-8'''))
def lowerCAmelCase__ ( lowerCamelCase_ : bytes):
'''simple docstring'''
return baseaa.baadecode(lowerCamelCase_).decode(... | 94 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Any =logging.get_logger(__name__)
__snake_case : Tuple ={
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://huggi... | 94 | 1 |
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
__snake_case : Union[str, Any] =logging.get_logger(__name__)
... | 94 |
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase_ : int = 100):
'''simple docstring'''
return sum(map(lowerCamelCase_ ,str(factorial(lowerCamelCase_))))
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : list):
'''simple docstring'''
lowerCAmelCase__ : Optional[int] = len(lowerCamelCase_)
for i in range(1 ,lowerCamelCase_):
lowerCAmelCase__ : int = collection[i]
lowerCAmelCase__ : ... | 94 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_G... | 94 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class lowerCamelCase__ ( unittest.TestCase):
'''simpl... | 94 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCamelCase__ ( nn.Module):
'''simple docstring'''
snake_case_ =42
snake_case_ =jnp.floataa
def lowerCAmelCase__ (self ) -> List[str]:
"""simple docstring"""
lowerCAmelCase... | 94 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase_ : list[int]):
'''simple docstring'''
lowerCAmelCase__ : List[str] = len(lowerCamelCase_) // 2
# choose the middle 3 elements
lowerCAmelCase__ : Dict = lst[m - ... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case : Optional[int] ={
'configuration_vision_text_dual_encoder': ['VisionTextDualEncoderConfig'],
'processing_vi... | 94 | 1 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
Wav... | 94 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case : Dict =HfArgumentParser(InitializationArguments)
__snake_case : Tuple =parser.parse_args()
# Load codeparrot tokenizer trained for Pyth... | 94 | 1 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def lowerCAmelCase__ ( lowerCamelCase_ : str):
'''simple docstring'''
return "".join(sorted(lowerCamelCase_))
def lowerCAmelCase__ ( lowerCamelCase_ : str):
'''simple ... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
lowerCAmelCase__ : str = len(lowerCamelCase_)
lowerCAmelCase__ : Union[str, Any] ... | 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : Optional[Any] ,lowerCamelCase_ : Union[str, Any]):
'''simple docstring'''
lowerCAmelCase__ : Any = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def lowerCA... | 94 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case : str ={
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ConditionalDetrConfig',
'Conditi... | 94 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__snake_case : Any ='\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yonghui Wu and ... | 94 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( lowerCamelCase_ : ndarray):
'''simple docstring'''
return np.dot(lowerCamelCase_ ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstri... | 94 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
__snake_case : Dict =(3, 9, -1_1, 0, 7, 5, 1, -1)
__snake_case : Optional[int] =(4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class lowerCamelCase__ :
'''simple docstring'''
s... | 94 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int] ,lowerCamelCase_ : List[Any]=1024 ,lowerCamelCase_ : in... | 94 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Any =logging.get_logger(__name__)
__snake_case : Tuple ={
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://huggi... | 94 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 94 | 1 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .benchm... | 94 |
import string
import numpy
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =string... | 94 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : List[str] ={
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'XCLIPVisionConfig',
],... | 94 |
__snake_case : Any ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : Tuple =[{'type':... | 94 | 1 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
__snake_case : Union[str, Any] =get_tes... | 94 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 94 | 1 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class lowerCamelCase__ ( lowerCamelCa... | 94 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransform... | 94 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case : Union[str, Any] ={
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct': ['MCTCTFeatureExtractor'],
'processi... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : int = 1, 1
lowerCAmelCase__ : Any = 2
while True:
lowerCAmelCase__ : Optional[Any] = 0
... | 94 | 1 |
def lowerCAmelCase__ ( ):
'''simple docstring'''
for n in range(1 ,1000000):
yield n * (n + 1) // 2
def lowerCAmelCase__ ( lowerCamelCase_ : int):
'''simple docstring'''
lowerCAmelCase__ : Union[str, Any] = 1
lowerCAmelCase__ ... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Any ={
'configuration_blenderbot_small': [
'BLENDERBOT_SMALL_PRETRAINED_C... | 94 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : list[str] | None = None ,lowerCamelCase_ : dict[str, float] | None = None ,lowerCamelCase_ : bool = False ,):
'''simple docstring'''
lowerCAmelCase__ : str = c... | 94 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 94 | 1 |
from __future__ import annotations
__snake_case : Optional[int] =[-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
__snake_case : Tuple =[-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]
def lowerCAmelCase__ ( lowerCamelCase_ : list[float]):
'''simple... | 94 |
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltF... | 94 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__snake_case : List[Any] ={'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
raise OptionalDe... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str = "The quick brown fox jumps over the lazy dog" ,):
'''simple docstring'''
lowerCAmelCase__ : Any = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : List[Any] = input_str.re... | 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
if not isinstance(lowerCamelCase_ ,lowerCamelCase_):
raise ValueError('''iterations must be defined as integers''')
if not isinstance(lowerCamelCase_ ,lowerCamelCase_) or not number >= ... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
while b:
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = b, a % b
return a
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase... | 94 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.u... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000000):
'''simple docstring'''
lowerCAmelCase__ : int = set(range(3 ,lowerCamelCase_ ,2))
primes.add(2)
for p in range(3 ,lowerCamelCase_ ,2):
if p not in primes:
continue
primes.differ... | 94 | 1 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCamelCase__) , """Tatoeba di... | 94 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Any =logging.get_logger(__name__)
__snake_case : Tuple ={
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://huggi... | 94 | 1 |
from __future__ import annotations
from random import random
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase = None ) -> List[str]:
"""simple docstring"""
lowerCAmelCase__ : List[str] = value
lowerCAm... | 94 |
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase_ : int = 100):
'''simple docstring'''
return sum(map(lowerCamelCase_ ,str(factorial(lowerCamelCase_))))
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 94 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCAmelCase__ ( lowerCamelCase_ : Any):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0X3400 and... | 94 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_G... | 94 | 1 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 94 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCamelCase__ ( nn.Module):
'''simple docstring'''
snake_case_ =42
snake_case_ =jnp.floataa
def lowerCAmelCase__ (self ) -> List[str]:
"""simple docstring"""
lowerCAmelCase... | 94 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : int =logging.get_logger(__name__)
__snake_case : Tuple ={
'abeja/gpt-neox-japanese-2.7b': 'https://huggingface.co/abeja/gpt-neox-japanese-2.7b/resolve/main/config.json',
}
class lowerCamelCase__ ... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case : Optional[int] ={
'configuration_vision_text_dual_encoder': ['VisionTextDualEncoderConfig'],
'processing_vi... | 94 | 1 |
import random
from typing import Any
def lowerCAmelCase__ ( lowerCamelCase_ : list):
'''simple docstring'''
for _ in range(len(lowerCamelCase_)):
lowerCAmelCase__ : Optional[Any] = random.randint(0 ,len(lowerCamelCase_) - 1)
lowerCAmelCase__ : ... | 94 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case : Dict =HfArgumentParser(InitializationArguments)
__snake_case : Tuple =parser.parse_args()
# Load codeparrot tokenizer trained for Pyth... | 94 | 1 |
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before toke... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
lowerCAmelCase__ : str = len(lowerCamelCase_)
lowerCAmelCase__ : Union[str, Any] ... | 94 | 1 |
from __future__ import annotations
from math import pow, sqrt
def lowerCAmelCase__ ( lowerCamelCase_ : float ,lowerCamelCase_ : float ,lowerCamelCase_ : float):
'''simple docstring'''
if (resistance, reactance, impedance).count(0) != 1:
raise ValueError('''One and only one... | 94 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case : str ={
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ConditionalDetrConfig',
'Conditi... | 94 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_toke... | 94 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( lowerCamelCase_ : ndarray):
'''simple docstring'''
return np.dot(lowerCamelCase_ ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstri... | 94 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : int ={'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig']}
try:
... | 94 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int] ,lowerCamelCase_ : List[Any]=1024 ,lowerCamelCase_ : in... | 94 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
from ...test_confi... | 94 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 94 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 94 |
import string
import numpy
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =string... | 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
while b:
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = b, a % b
return a
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase... | 94 |
__snake_case : Any ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : Tuple =[{'type':... | 94 | 1 |
__snake_case : Union[str, Any] ='Input must be a string of 8 numbers plus letter'
__snake_case : int ='TRWAGMYFPDXBNJZSQVHLCKE'
def lowerCAmelCase__ ( lowerCamelCase_ : str):
'''simple docstring'''
if not isinstance(lowerCamelCase_ ,lowerCamelCase_):
lowerCAmelCase__ ... | 94 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 94 | 1 |
from manim import *
class lowerCamelCase__ ( lowerCamelCase__):
'''simple docstring'''
def lowerCAmelCase__ (self ) -> int:
"""simple docstring"""
lowerCAmelCase__ : Any = Rectangle(height=0.5 ,width=0.5 )
lowerCAmelCase__ ... | 94 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransform... | 94 | 1 |
def lowerCAmelCase__ ( lowerCamelCase_ : list):
'''simple docstring'''
if len(lowerCamelCase_) <= 1:
return [tuple(lowerCamelCase_)]
lowerCAmelCase__ : List[str] = []
def generate(lowerCamelCase_ : int ,lowerCamelCase_ : list):
lowerCAmelCa... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : int = 1, 1
lowerCAmelCase__ : Any = 2
while True:
lowerCAmelCase__ : Optional[Any] = 0
... | 94 | 1 |
import sys
__snake_case : Optional[int] =(
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'6689664895044524452316173185640309... | 94 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Any ={
'configuration_blenderbot_small': [
'BLENDERBOT_SMALL_PRETRAINED_C... | 94 | 1 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.te... | 94 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 94 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
... | 94 |
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltF... | 94 | 1 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCamelCase__ ( lowerCamelCase__):
'''simple ... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : str = "The quick brown fox jumps over the lazy dog" ,):
'''simple docstring'''
lowerCAmelCase__ : Any = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : List[Any] = input_str.re... | 94 | 1 |
from ..utils import DummyObject, requires_backends
class lowerCamelCase__ ( metaclass=SCREAMING_SNAKE_CASE_):
'''simple docstring'''
snake_case_ =["""torch"""]
def __init__(self ,*__lowerCamelCase ,**__lowerCamelCase ) -> Optional[Any]:
"""simple docstring"""
... | 350 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
while b:
lowerCAmelCase__ , lowerCAmelCase__ : Optional[Any] = b, a % b
return a
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase... | 94 | 0 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_commo... | 351 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000000):
'''simple docstring'''
lowerCAmelCase__ : int = set(range(3 ,lowerCamelCase_ ,2))
primes.add(2)
for p in range(3 ,lowerCamelCase_ ,2):
if p not in primes:
continue
primes.differ... | 94 | 0 |
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
class lowerCamelCase__ ( _UpperCAmelCase):
'''simple docstring'''
snake_case_ ="philschmid/bart-large-cnn-samsum"
snake_case_ =(
"This is a tool that summarizes an English text. It... | 352 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Any =logging.get_logger(__name__)
__snake_case : Tuple ={
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://huggi... | 94 | 0 |
from copy import deepcopy
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase = None ,__lowerCamelCase = None ) -> None:
"""simple docstring"""
if arr is None and size is not None:
lowerCAmelCase__ : Optional[int] ... | 353 |
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase_ : int = 100):
'''simple docstring'''
return sum(map(lowerCamelCase_ ,str(factorial(lowerCamelCase_))))
if __name__ == "__main__":
print(solution(int(input('Enter the Number: ').strip())))
| 94 | 0 |
from __future__ import annotations
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase ) -> Union[str, Any]:
"""simple docstring"""
lowerCAmelCase__ : Union[str, Any] = order
# a_{0} ... a_{k}
lower... | 354 |
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_G... | 94 | 0 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__snake_case : List[Any] ='.'
if __name__ == "__main__":
__snake_case : Dict =os.path.join(REPO_PATH, 'utils/docume... | 355 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCamelCase__ ( nn.Module):
'''simple docstring'''
snake_case_ =42
snake_case_ =jnp.floataa
def lowerCAmelCase__ (self ) -> List[str]:
"""simple docstring"""
lowerCAmelCase... | 94 | 0 |
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.mo... | 356 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case : Optional[int] ={
'configuration_vision_text_dual_encoder': ['VisionTextDualEncoderConfig'],
'processing_vi... | 94 | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( lowerCamelCase_ : list[list[int]]):
'''simple docstring'''
lowerCAmelCase__ : int = len(__A)
# We need to create solution object to save path.
lowerCAmelCase__ : Any = [[0 for ... | 357 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case : Dict =HfArgumentParser(InitializationArguments)
__snake_case : Tuple =parser.parse_args()
# Load codeparrot tokenizer trained for Pyth... | 94 | 0 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : List[Any]=7):
'''simple docstring'''
lowerCAmelCase__ : Dict = None
if token... | 358 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Optional[Any] = len(lowerCamelCase_)
lowerCAmelCase__ : str = len(lowerCamelCase_)
lowerCAmelCase__ : Union[str, Any] ... | 94 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCamelCase__ ( metaclass=__A):
'''simple docstring'''
snake_case_ =['keras_nlp']
def __init__(self ,*__lowerCamelCase ,**__lowerCamelCase ) -> Any:
"""simple docstring"""
... | 359 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case : str ={
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ConditionalDetrConfig',
'Conditi... | 94 | 0 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase__ :
'''simple docstring'''
def __init__(self ,__lowerCamelCase ) -> None:
"""simple docstring"""
lowerCAmelCase__ : Optional[Any] = value
lower... | 360 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( lowerCamelCase_ : ndarray):
'''simple docstring'''
return np.dot(lowerCamelCase_ ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstri... | 94 | 0 |
import argparse
import os
import re
__snake_case ='src/transformers'
# Pattern that looks at the indentation in a line.
__snake_case =re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
__snake_case =re.compile(R'^\s*\"([^\"]+)\":')
# Pattern that matches `_import_structure["key... | 361 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int] ,lowerCamelCase_ : List[Any]=1024 ,lowerCamelCase_ : in... | 94 | 0 |
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
__snake_case : i... | 362 |
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data import Dataset
from tra... | 94 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case : Any ={'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}
try:
if not is_torch_available():
r... | 363 |
import string
import numpy
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstring'''
snake_case_ =string... | 94 | 0 |
__snake_case : List[Any] ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : List[str] ... | 364 |
__snake_case : Any ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : Tuple =[{'type':... | 94 | 0 |
def lowerCAmelCase__ ( lowerCamelCase_ : list[int] ,lowerCamelCase_ : int):
'''simple docstring'''
lowerCAmelCase__ : List[str] = len(__a)
lowerCAmelCase__ : Optional[int] = [[False] * (required_sum + 1) for _ in range(arr_len + 1)]
# fo... | 365 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 94 | 0 |
def lowerCAmelCase__ ( lowerCamelCase_ : int ,lowerCamelCase_ : int):
'''simple docstring'''
return "\n".join(
f"""{number} * {i} = {number * i}""" for i in range(1 ,number_of_terms + 1))
if __name__ == "__main__":
print(multiplication_table(number=5, numb... | 366 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransform... | 94 | 0 |
def lowerCAmelCase__ ( lowerCamelCase_ : str ,lowerCamelCase_ : str):
'''simple docstring'''
def get_matched_characters(lowerCamelCase_ : str ,lowerCamelCase_ : str) -> str:
lowerCAmelCase__ : List[Any] = []
lowerCAmelCase__ : List[str] ... | 367 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : int = 1, 1
lowerCAmelCase__ : Any = 2
while True:
lowerCAmelCase__ : Optional[Any] = 0
... | 94 | 0 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowerCamelCase__ ( unittest.TestCase):
'''simple docstring'''
snake_case... | 368 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Any ={
'configuration_blenderbot_small': [
'BLENDERBOT_SMALL_PRETRAINED_C... | 94 | 0 |
def lowerCAmelCase__ ( lowerCamelCase_ : Optional[int] ,lowerCamelCase_ : Union[str, Any]):
'''simple docstring'''
return int((input_a, input_a).count(0) == 0)
def lowerCAmelCase__ ( ):
'''simple docstring'''
assert and_gate(0 ,0) == 0
assert and_gate(0 ,1) ... | 369 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTest... | 94 | 0 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should r... | 370 |
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 (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltF... | 94 | 0 |
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class lowerCamelCase__ ( _UpperCAmelCase):
'''simple docstring'''
snake_case_ ="""openai/whisper-base"""
snake_case_ =(
"""This is a tool that transcribes an audio ... | 371 |
def lowerCAmelCase__ ( lowerCamelCase_ : str = "The quick brown fox jumps over the lazy dog" ,):
'''simple docstring'''
lowerCAmelCase__ : Any = set()
# Replace all the whitespace in our sentence
lowerCAmelCase__ : List[Any] = input_str.re... | 94 | 0 |
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