code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_com... | 92 |
'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCAmelCase_ = logging.getLogger()
@unittest.skip("""Temporarily disab... | 346 | 0 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase ( metaclass=lowerCamelCase_ ):
'''simple docstring'''
lowerCAmelCase_ = ["""flax"""]
def __init__( self : str , *__lowercase : Optio... | 187 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _UpperCamelCase ( ):
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path im... | 346 | 0 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase_... | 104 |
'''simple docstring'''
from timeit import timeit
UpperCAmelCase_ = {
'MALAYALAM': True,
'String': False,
'rotor': True,
'level': True,
'A': True,
'BB': True,
'ABC': False,
'amanaplanacanalpanama': True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
... | 346 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
UpperCamelCase_ = False
class _a ... | 251 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase_ = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 346 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def _lowercase ( __snake_case ) -> str:
if num <= 0:
__lowerCAmelCase : Optional[int] = F"""{num}: Invalid input, please enter a positive integer."""
raise ... | 269 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase_ ( lowerCamelCase_ ... | 346 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/config.json'''
),
# See all Vivit mode... | 337 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCAm... | 346 | 0 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : list[int] ):
'''simple docstring'''
lowercase__ : str = len(SCREAMING_SNAKE_CASE__ )
for i in range(SCREAMING_SNAKE_CASE__ ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE__ ):
if numbers[j] ... | 214 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
loggin... | 346 | 0 |
import heapq
def _UpperCamelCase ( lowercase__ ):
__SCREAMING_SNAKE_CASE : int = []
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like a Priority Queue
# heapq works with ... | 9 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase_ = '\\n@misc{chen2021evaluating,\n title={Eva... | 346 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 177 |
'''simple docstring'''
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and ... | 346 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets i... | 198 |
'''simple docstring'''
import string
from math import logaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = document.translate(
str.maketrans("""""" , """""" , string.punctuatio... | 346 | 0 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCamelCase : Any =False
class __a ( unitte... | 189 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCAmelCase_ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
... | 346 | 0 |
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, BartTokeni... | 92 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, Any] = (PNDMScheduler,)
lowerC... | 346 | 0 |
lowercase__ : Tuple = [0, 2, 4, 6, 8]
lowercase__ : Optional[int] = [1, 3, 5, 7, 9]
def lowerCamelCase__ ( _A , _A , _A , _A ):
'''simple docstring'''
if remaining_length == 0:
if digits[0] == 0 or digits[-1] == 0:
... | 187 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/con... | 346 | 0 |
'''simple docstring'''
import random
class lowercase_ :
"""simple docstring"""
@staticmethod
def SCREAMING_SNAKE_CASE ( lowercase__ : str ):
__lowercase = [ord(_UpperCAmelCase ) for i in text]
__lowercase = []
__lowercase = []
f... | 104 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Lis... | 346 | 0 |
'''simple docstring'''
from timeit import timeit
UpperCamelCase_ = {
"MALAYALAM": True,
"String": False,
"rotor": True,
"level": True,
"A": True,
"BB": True,
"ABC": False,
"amanaplanacanalpanama": True, # "a man a plan a canal panama"
}
# Ensure... | 251 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
UpperCAmelCase_ = logging.... | 346 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__snake_cas... | 269 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
UpperCAmelCase_ = logging.getLogger(__name__)
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = argparse.Argumen... | 346 | 0 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import os... | 337 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase_ = '\\n\n'
UpperCAmelCase_ = '\nPerplexity (PPL) is one of the most common me... | 346 | 0 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : int = 1_000_000 ):
'''simple docstring'''
lowercase__ : Dict = [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 , ... | 214 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 1000000 ):
'''simple docstring'''
UpperCAmelCase__ = [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 , SC... | 346 | 0 |
from collections import defaultdict
from math import ceil, sqrt
def _UpperCamelCase ( lowercase__ = 1000000 , lowercase__ = 10 ):
__SCREAMING_SNAKE_CASE : Dict = defaultdict(SCREAMING_SNAKE_CASE__ )
for outer_width in range(3 , (t_limit // 4)... | 9 |
'''simple docstring'''
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
... | 346 | 0 |
"""simple docstring"""
from manim import *
class UpperCAmelCase (lowerCamelCase_ ):
"""simple docstring"""
def _snake_case ( self ):
lowercase__: Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
lowercase__: List[Any] = Rectangle... | 177 |
'''simple docstring'''
from math import factorial
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 20 ):
'''simple docstring'''
UpperCAmelCase__ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ = n // 2... | 346 | 0 |
'''simple docstring'''
import math
def __UpperCamelCase ( UpperCAmelCase ):
lowercase__ : Optional[Any] = 0
lowercase__ : List[Any] = 0
while num > 0:
lowercase__ : Tuple = num % 8
lowercase__ : int = octal + (remainder * math.floor(math.pow(10 , S... | 198 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require... | 346 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Any:
UpperCamelCase__ : List[Any] = list(range(len(SCREAMING_SNAKE_CASE__ ) ) )
UpperCamelCase__ : Dict ... | 189 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Union[str, Any] ):
"""simple docstring"""
self.test()
def ... | 346 | 0 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def _a ( SCREAMING_SNAKE_CASE_ : str ):
return x + 2
class a__ ( unittest.TestCase ):
def __SCREAMING_SNAKE_CASE( s... | 92 |
'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCAmelCase_ = logging.getLogger()
@unittest.skip("""Temporarily disab... | 346 | 0 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("9.1.0"):
lowercase__ : Optional[Any] = {
"linear": PIL.Image.Resampling.BILINEAR,
"bilinear": PIL.Imag... | 187 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _UpperCamelCase ( ):
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path im... | 346 | 0 |
'''simple docstring'''
import requests
lowerCAmelCase__ = '''YOUR API KEY'''
def _A ( A__ , A__ = giphy_api_key ):
"""simple docstring"""
__lowercase = '''+'''.join(query.split() )
__lowercase = F"https://api.giphy.com/v1/gifs/search?q={formatte... | 104 |
'''simple docstring'''
from timeit import timeit
UpperCAmelCase_ = {
'MALAYALAM': True,
'String': False,
'rotor': True,
'level': True,
'A': True,
'BB': True,
'ABC': False,
'amanaplanacanalpanama': True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
... | 346 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"M... | 251 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase_ = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 346 | 0 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
... | 269 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase_ ( lowerCamelCase_ ... | 346 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__a = logging.get_logger(__name__) # pylint: disable=invalid-name
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ... | 337 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCAm... | 346 | 0 |
from functools import lru_cache
@lru_cache
def snake_case__ ( SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
if num < 0:
raise ValueError('Number should not be negative.' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
... | 214 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
loggin... | 346 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _UpperCamelCase ( lowercase__ , lowercase__ , **lowercase__ ):
__SCREAMING_SNAKE_CASE : Tuple = AutoConfig.from_pretrained(SCREAMING_SNAKE_CASE__ , **SCRE... | 9 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase_ = '\\n@misc{chen2021evaluating,\n title={Eva... | 346 | 0 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> List[str]:
lowercase__: int = math.sqrt(SCREAMING_SNAKE_CASE__ )
lowercase__: Optional[Any] = 1 / (sigma * math.sqrt(2 * ... | 177 |
'''simple docstring'''
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and ... | 346 | 0 |
'''simple docstring'''
import math
def __UpperCamelCase ( UpperCAmelCase ):
lowercase__ : Dict = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(SCREAMING_SNAKE_CASE__ )
def __UpperCamelCase ( UpperCAmelCase = 1 / 1_2345 ):
lo... | 198 |
'''simple docstring'''
import string
from math import logaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = document.translate(
str.maketrans("""""" , """""" , string.punctuatio... | 346 | 0 |
import numpy as np
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> List[str]:
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod() | 189 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCAmelCase_ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
... | 346 | 0 |
from __future__ import annotations
def _a ( SCREAMING_SNAKE_CASE_ : list[int | str] ):
create_state_space_tree(SCREAMING_SNAKE_CASE__ , [] , 0 , [0 for i in range(len(SCREAMING_SNAKE_CASE__ ) )] )
def _a ( SCREAMING_SNA... | 92 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, Any] = (PNDMScheduler,)
lowerC... | 346 | 0 |
import random
def lowerCamelCase__ ( _A , _A , _A ):
'''simple docstring'''
snake_case_ = a[left_index]
snake_case_ = left_index + 1
for j in range(left_index + 1 , SCREAMING_SNAKE_CASE__ ):
if a[j] < pivot:
snake_... | 187 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/con... | 346 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
class lowercase_ (lowerCamelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : str = """timm_backbone"""
... | 104 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Lis... | 346 | 0 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTeste... | 251 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
UpperCAmelCase_ = logging.... | 346 | 0 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
f... | 269 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
UpperCAmelCase_ = logging.getLogger(__name__)
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = argparse.Argumen... | 346 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__a = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxConfig'''],
}
try:
if not is_torch_available():
rais... | 337 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase_ = '\\n\n'
UpperCAmelCase_ = '\nPerplexity (PPL) is one of the most common me... | 346 | 0 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE__ (lowerCamelCase_ ):
__lowerCamelCase : Any = ["""image_processor""", """tokenizer"""]
__lowerCamelCase : Dict ... | 214 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 1000000 ):
'''simple docstring'''
UpperCAmelCase__ = [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 , SC... | 346 | 0 |
from string import ascii_lowercase, ascii_uppercase
def _UpperCamelCase ( lowercase__ ):
if not sentence:
return ""
__SCREAMING_SNAKE_CASE : List[str] = dict(zip(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) )
return low... | 9 |
'''simple docstring'''
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
... | 346 | 0 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
__A = importlib.util.find_spec("s3fs") is not None
if _has_safs:
from .safilesystem impo... | 177 |
'''simple docstring'''
from math import factorial
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 20 ):
'''simple docstring'''
UpperCAmelCase__ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ = n // 2... | 346 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def __UpperCamelCase ( UpperCAmelCase ):
if (
(cp >= 0x4_e00 and cp <= 0x9_fff)
or (cp >= 0x3_400 and cp <= 0x4_dbf) #
... | 198 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require... | 346 | 0 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transf... | 189 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Union[str, Any] ):
"""simple docstring"""
self.test()
def ... | 346 | 0 |
from collections.abc import Callable
import numpy as np
def _a ( SCREAMING_SNAKE_CASE_ : Callable , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ ... | 92 |
'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCAmelCase_ = logging.getLogger()
@unittest.skip("""Temporarily disab... | 346 | 0 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCAmelCase ( lowerCamelCase_ ):
... | 187 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _UpperCamelCase ( ):
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path im... | 346 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''microsoft/wavlm-base''': '''https://huggingface.co/microsoft/wavlm-base/res... | 104 |
'''simple docstring'''
from timeit import timeit
UpperCAmelCase_ = {
'MALAYALAM': True,
'String': False,
'rotor': True,
'level': True,
'A': True,
'BB': True,
'ABC': False,
'amanaplanacanalpanama': True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
... | 346 | 0 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_avail... | 251 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase_ = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 346 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_te... | 269 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase_ ( lowerCamelCase_ ... | 346 | 0 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__a = 1.0_5457_1817e-34 # unit of ℏ : J * s
__a = 3e8 # unit of c : m * s^-1
def __lowercase ( _UpperCamelCase, _UpperCamelCase, ... | 337 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCAm... | 346 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
snake_case_ = TypeVar('''T''')
snake_case_ = TypeVar('''U''')
class SCREAMING_SNAKE_CASE__ (Generic[T, U] ):
def __init__( self , a , a):
lowercase... | 214 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
loggin... | 346 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeli... | 9 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase_ = '\\n@misc{chen2021evaluating,\n title={Eva... | 346 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageR... | 177 |
'''simple docstring'''
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and ... | 346 | 0 |
'''simple docstring'''
class UpperCAmelCase :
'''simple docstring'''
def __init__( self , __lowerCAmelCase , __lowerCAmelCase ) -> Any:
lowercase__ : Optional[Any] = name
lowercase__ : Optional[Any] = val
def __str__( self ) -> T... | 198 |
'''simple docstring'''
import string
from math import logaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = document.translate(
str.maketrans("""""" , """""" , string.punctuatio... | 346 | 0 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
lowerCamelCase : str =lo... | 189 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCAmelCase_ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
... | 346 | 0 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTokenizerFast,
... | 92 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, Any] = (PNDMScheduler,)
lowerC... | 346 | 0 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
lowercase__ : List[Any] = (
"This metric will be removed from the li... | 187 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/con... | 346 | 0 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
lowerCAmelCase__ = '''examples/'''
lowerCAmelCase__ = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.c... | 104 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCAmelCase_ = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Lis... | 346 | 0 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class _a ( lowerCamelCase_ ):
'''simple docstring'''
A : Dict = (UnCLIPScheduler,)
... | 251 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
UpperCAmelCase_ = logging.... | 346 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtraction... | 269 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
UpperCAmelCase_ = logging.getLogger(__name__)
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = argparse.Argumen... | 346 | 0 |
from typing import TYPE_CHECKING
import torch
from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool
if TYPE_CHECKING:
from PIL import Image
class __SCREAMING_SNAKE_CASE ( lowerCamelCase_ ):
A : ... | 337 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase_ = '\\n\n'
UpperCAmelCase_ = '\nPerplexity (PPL) is one of the most common me... | 346 | 0 |
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts and running tests.
snake_case_ = abspath(join(dirname(dirname(__file__)), '''src'''))
sys.path.insert... | 214 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 1000000 ):
'''simple docstring'''
UpperCAmelCase__ = [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 , SC... | 346 | 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_albert impor... | 9 |
'''simple docstring'''
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
... | 346 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {"configuration_timm_backbone": ["TimmBackboneConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except ... | 177 |
'''simple docstring'''
from math import factorial
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int = 20 ):
'''simple docstring'''
UpperCAmelCase__ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ = n // 2... | 346 | 0 |
'''simple docstring'''
def __UpperCamelCase ( ):
lowercase__ : Tuple = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowercase__ : List[Any] = 6
lowercase__ : Dict = 1
lowercase__ : Optional[int] = 1901
lowercase__ : Union[str, Any] = 0
whil... | 198 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require... | 346 | 0 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCamelCase : Optional[int] =None
try:
import msvcrt
except ImportError:
lowerCamelCase : int =None
try:
import fcntl
except ImportError:
lowerCamelCase : ... | 189 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
def __init__( self : Union[str, Any] ):
"""simple docstring"""
self.test()
def ... | 346 | 0 |
import requests
UpperCamelCase__ = """""" # <-- Put your OpenWeatherMap appid here!
UpperCamelCase__ = """https://api.openweathermap.org/data/2.5/"""
def _a ( SCREAMING_SNAKE_CASE_ : str = "Chicago" , SCREAMING_SNAKE_CASE_ : str = APPID ):
re... | 92 |
'''simple docstring'''
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCAmelCase_ = logging.getLogger()
@unittest.skip("""Temporarily disab... | 346 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( lowerCamelCase_ , ... | 187 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _UpperCamelCase ( ):
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path im... | 346 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {'''vocab_file''': '''vocab.json'''}
lowerCAmelCase__ ... | 104 |
'''simple docstring'''
from timeit import timeit
UpperCAmelCase_ = {
'MALAYALAM': True,
'String': False,
'rotor': True,
'level': True,
'A': True,
'BB': True,
'ABC': False,
'amanaplanacanalpanama': True, # "a man a plan a canal panama"
}
# Ensure our test data is valid
... | 346 | 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 PreTrainedTokenizer
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
Upp... | 251 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase_ = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 346 | 0 |
"""simple docstring"""
from PIL import Image
def _lowercase ( __snake_case ,__snake_case ) -> int:
__lowerCAmelCase : List[Any] = (259 * (level + 255)) / (255 * (259 - level))
def contrast(__snake_case ) -> int:
return int(128 + factor ... | 269 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase_ ( lowerCamelCase_ ... | 346 | 0 |
from __future__ import annotations
__a = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''C'''],
}
class __SCREA... | 337 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowerCAm... | 346 | 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_tf, s... | 214 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
loggin... | 346 | 0 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers im... | 9 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase_ = '\\n@misc{chen2021evaluating,\n title={Eva... | 346 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> List[str]:
if "cls_token" in name:
lowercase__: Any = n... | 177 |
'''simple docstring'''
import math
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
assert isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and ... | 346 | 0 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_te... | 198 |
'''simple docstring'''
import string
from math import logaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = document.translate(
str.maketrans("""""" , """""" , string.punctuatio... | 346 | 0 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import... | 189 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCAmelCase_ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
... | 346 | 0 |
def _a ( SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : list[list[int]] ):
def update_area_of_max_square(SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ) -> int:
... | 92 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( lowerCamelCase_ ):
'''simple docstring'''
lowerCAmelCase_ : Union[str, Any] = (PNDMScheduler,)
lowerC... | 346 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 187 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'google/vivit-b-16x2-kinetics400': (
'https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main/con... | 346 | 0 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _a ( _SCREAMING_SNAKE_CASE ) ... | 347 |
"""simple docstring"""
from __future__ import annotations
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[Any]:
print(f"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(_SCREAMING_SNAKE_CASE ):
print(f"""{i}\t\t{d}""" )
... | 347 | 1 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentPa... | 347 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__SCREAMING_SNAKE_CASE : List[str... | 347 | 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,
)
__SCREAMING_SNAKE_CASE : List[str] = {
'configuration_roberta': ... | 347 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> float:
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""" )
return (bulk_modulus / d... | 347 | 1 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
snake_case_ = len(_SCREAMING_SNAKE_CASE )
snake_case_ = sum(_SCREAMING_SNAKE_CASE )
snake_case_ = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1... | 347 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE ) -> bool:
if num < 0:
return False
snake_case_ = num
snake_case_ = 0
while num > 0:
snake_case_ = rev_num * 10 + (num % 10)
num //= 10
return ... | 347 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
__SCREAMI... | 347 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_token... | 347 | 1 |
"""simple docstring"""
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... | 347 |
"""simple docstring"""
import datasets
__SCREAMING_SNAKE_CASE : Tuple = '\\n@InProceedings{conneau2018xnli,\n author = "Conneau, Alexis\n and Rinott, Ruty\n and Lample, Guillaume\n and Williams, Adina\n and Bowman, Samuel R.\n ... | 347 | 1 |
"""simple docstring"""
class __A :
'''simple docstring'''
def __init__( self : Tuple , UpperCAmelCase_ : int , UpperCAmelCase_ : Optional[Any]=None , UpperCAmelCase_ : int=None ) ->int:
"""simple docstring... | 347 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A (metaclass=snake_case__):
'''simple docstring'''
__lowercase: List[Any] = ["""sentencepiece"""]
def __init__( self : int , *UpperCAmelCase_ : Any ... | 347 | 1 |
"""simple docstring"""
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_C... | 347 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
class __A (snake_case__):
'''simple docstring'''
def __init__( self : ... | 347 | 1 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE ) -> bool:
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
snake_case_ = f"""Input value of [number={number}] must be an integer"""
raise TypeError(_SCREAMING_SNAKE_CASE )
if nu... | 347 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.uti... | 347 | 1 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def _a ( ) -> None:
snake_case_ = input("""Enter message: """ )
snake_case_ = input("""Enter key [alphanumeric]: """ )
snake_case_ = input("""Encrypt/... | 347 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.n... | 347 | 1 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Union[str, Any] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__SCREAMING_SNAKE_CASE : Tuple = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__SCREAMING_SNAKE_CASE : Dict = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wedne... | 347 |
"""simple docstring"""
from __future__ import annotations
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> bool:
snake_case_ = get_failure_array(_SCREAMING_SNAKE_CASE )
# 2) Step through text searching for pattern
snake_case_ , snake_case_ = ... | 347 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def _a ( _SCREAMING_SNAKE_CASE ) -> Optional[int]:
... | 347 |
"""simple docstring"""
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class __... | 347 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertToken... | 347 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't ... | 347 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : List[str] = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE : List[Any] = {
'google/pix2struct-text... | 347 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
f... | 347 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 347 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import Flax... | 347 | 1 |
"""simple docstring"""
from itertools import product
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> list[int]:
snake_case_ = sides_number
snake_case_ = max_face_number * dice_number
snake_case_ = [0] * (max_total + 1)
sna... | 347 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__SCREAMING_SNAKE_CASE : Any = logging.get_logger(__name__)
class __A (snake_case__):
'''simple docstring'''... | 347 | 1 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> float:
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""" )
return (bulk_modulus / d... | 347 |
"""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):
'''simple docstring'''
def ... | 347 | 1 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__SCREAMING_SNAKE_CASE : Union[str, Any] = None
try:
import msvcrt
except ImportError:
__SCREAMING_SNAKE_CASE : List[Any] = None
try:
import fcnt... | 347 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentPa... | 347 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, 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():
... | 347 |
"""simple docstring"""
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from ... | 347 | 1 |
"""simple docstring"""
from __future__ import annotations
def _a ( _SCREAMING_SNAKE_CASE ) -> int:
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1 , ... | 347 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE : str = logging.get_logger(__name__)
__SCREAMI... | 347 | 1 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMM... | 347 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from .... | 347 | 1 |
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