code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def a__ ( A_, A_ ):
'''simple docstring'''
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a, lowerCamelCase__ )
def a__ ( A_, A_ ):
'''simple docstring'''
while y: # --> when y=0 then loop will terminate and ... | 529 | """simple docstring"""
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
... | 644 | 0 |
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, 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_attenti... | 1 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
fro... | 640 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowercase =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402
# This is the... | 446 | """simple docstring"""
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_... | 644 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMSched... | 469 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
__snake_case ... | 178 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
from __future__ import annotations
lowerCAmelCase_ = 8.988E9 # units = N * m^s * C^-2
def lowerCamelCase_ ( lowerCAmelCase: Optional[int] , lowerCAmelCase: List[Any] , lowerCAmelCase: Optional[int] , lowerCAmelCase: List[str] )-> Optional[int]:... | 411 | """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_toke... | 644 | 0 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetFo... | 482 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def _a ( UpperCamelCase_ : List[str] ) -> Any:
"""simple docstring"""
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecation_warnings" , set() )
@pytest... | 339 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class _UpperCamelCase( unittest.TestCase ):
def __lowerCAmelCase ( self : Optional[int] ):
'''simple docstring'''
__a : ... | 47 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
ControlNetModel,
DDIMScheduler,
StableDiffusionControlNetImgaImgPipeline,
U... | 593 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def a__ ( A_, A_, A_ ):
'''simple docstring'''
if not arr:
return None, None, 0
if low == high:
return low, ... | 529 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
import os
def _A ( ) -> List[Any]:
"""simple docstring"""
with open(os.path.dirname(lowerCamelCase__ ) + '/grid.txt' ) as f:
__UpperCamelCase = [] # noqa: E741
for _ in range(20 ):
l.append([int(lowerCamelCase__ ) for x in f.readlin... | 1 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
snake_case_ = current_set.copy()
for row_index, row in enumerate(lowerCamelCase__ ):
snake_case_ = row[0]
for column_in... | 640 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase ={
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
],... | 446 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : Optional[Any] ) -> Tuple:
"""simple docstring"""
__lowerCamelCase = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function' )
__lowerCamelCase = ... | 469 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrateg... | 178 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class _lowerCAmelCase ( nn.Module ):
'''simple docstring'''
def __init__( self : Optional[int] , UpperCamelCase : int = 16 , ... | 411 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", lev... | 482 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
def _a ( UpperCamelCase_ : Optional[int] , UpperCamelCase_ : Dict = False ) -> Any:
"""simple docstring"""
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
lowerCAmelCase__ = F"Expected string as input, found {type(lowerCamelCas... | 339 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered... | 47 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_common... | 593 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
def a__ ( A_ ):
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 529 | """simple docstring"""
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
... | 644 | 0 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common impo... | 1 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> Any:
'''simple docstring'''
if number > 0:
raise ValueError('''input must be a negative integer''' )
snake_case_ = len(bin(lowerCamelCase__ )[3:] )
snake_case_ ... | 640 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( __lowerCamelCase : List[Any] ):
'''simple docstring'''
_UpperCAmelCase : int =[]
for data in source_data:
for i, el in enumerate(lowerCamelCase__ ):
if len(lowerCamelCase__ ) < i + 1:
dat... | 446 | """simple docstring"""
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_... | 644 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
if not is_torch_available():
... | 469 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
"""simple docstring"""
def __lowerCAmelCase ( lowercase : Any ) -> Dict:
"""simple docstring"""
snake_case : List[str] = set()
# edges = list of graph's edges
snake_case : Optional[Any] = get_edges(lowerCamelCase__ )
# While there... | 178 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
lowerCAmelC... | 411 | """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_toke... | 644 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
cla... | 482 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
import math
def _a ( UpperCamelCase_ : Any ) -> Any:
"""simple docstring"""
lowerCAmelCase__ = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowerCamelCase__ )
def _a ( UpperCamelCase_ : Union[str, A... | 339 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
SCREAMING_SNAKE_CASE__ = loggin... | 47 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
__A = {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}
__A = {
"... | 593 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowerCAmelCase : Tuple = logging.get_logger(__name__)
__lowerCAmelCase : Any = {"vocab_file... | 529 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
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_available():
import torch
if is... | 1 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
'''simple docstring'''
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 BartForCondition... | 640 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''simple docstring'''
from manim import *
class __magic_name__ ( __UpperCamelCase ):
def lowerCAmelCase ( self) -> List[str]:
'''simple docstring'''
_UpperCAmelCase : Tuple =Rectangle(height=0.5 , width=0.5)
... | 446 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_co... | 469 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _lowerCAmelCase :
def __init__( self , UpperCamelCase__ ) -> int:
'''simple docstring'''
snake_case : Dict = []
self.adlist.append(
... | 178 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 411 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
"""simple docstring"""
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase__ =datase... | 482 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]}
try:
if not is... | 339 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_availa... | 47 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def __a ( lowerCAmelCase_ : Tuple ,lowerCAmelCase_ : Optional[Any] ,lowerCAmelCase_ : Any ,lowerCAmelCase_ : int ,) -> Optional[Any]:
'''simple do... | 593 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
__lowerCAmelCase : Any = False
try:
__lowerCAmel... | 529 | """simple docstring"""
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
... | 644 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMS... | 1 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from... | 640 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase ={"configuration_plbart": ["PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP", "PLBartCo... | 446 | """simple docstring"""
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_... | 644 | 0 |
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.... | 469 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
"configuration_roberta": ["ROBERTA_PRETRAINED_C... | 178 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase: List[str] , lowerCAmelCase: str , lowerCAmelCase: List[Any] , )-> Dict:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more o... | 411 | """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_toke... | 644 | 0 |
"""simple docstring"""
import numpy
# List of input, output pairs
lowerCAmelCase__ =(
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowerCAmelCase__ =(((515, 22, 13), 555), ((61, 35, 49), 150))
lowerCAmelCase__ =[2, 4,... | 482 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
class lowercase__ :
def __init__( self , __UpperCAmelCase )-> str:
'''simple docstring'''
lowerCAmelCase__ = size
lowerCAmelCase__ = [0] * size
lowerCAmelCase__ = [0] * size
@staticmethod
def UpperCAmelCase ( __Upper... | 339 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
from __future__ import annotations
class _UpperCamelCase:
def __init__( self : int , SCREAMING_SNAKE_CASE__ : List[str]=None ):
'''simple docstring'''
__a : Optional[int] = data
__a : List[str] = ... | 47 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
__A = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n author={Wang, Alex and Singh, Amanpreet a... | 593 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class Uppe... | 529 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
... | 1 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__UpperCamelCase )
class a ( __UpperCamelCase ):
# `task` is not a ClassVar since we... | 640 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''simple docstring'''
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_see... | 446 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 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 __lowerCAmelCase ( __Uppe... | 469 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
"""simple docstring"""
import numpy as np
class _lowerCAmelCase :
def __init__( self , UpperCamelCase__=None , UpperCamelCase__=None , UpperCamelCase__=None , UpperCamelCase__=None , UpperCamelCase__=None ) -> str:
'''simple docstring'''... | 178 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json",
}
class _lowerCAmelCase ... | 411 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
lowerCAmelCase__ =logging.get_logger(__name__)
class A__:
def __init... | 482 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
import argparse
from collections import defaultdict
def _a ( UpperCamelCase_ : Dict , UpperCamelCase_ : Tuple , UpperCamelCase_ : List[Any] , UpperCamelCase_ : Dict , UpperCamelCase_ : Optional[int] ) -> Tuple:
"""simple docstrin... | 339 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
def UpperCAmelCase__ ( lowerCamelCase_ : int = 1_0_0_0 ):
__a , __a : int = 1, 1
__a : Union[str, Any] = []
for i in range(1 , n + 1 ):
__a : Optional[int] = prev_numerator + 2 * prev_denomi... | 47 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __a ( lowerCAmelCase_ : Optional[int] ) -> List[Any]:
'''simple docstring'''
return getitem, k
def __a ( lowerCAmelCase_ : Dict ,lo... | 593 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase : Any = {"configuration_unispeech": ["UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP", "UniSpeechConf... | 529 | """simple docstring"""
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
... | 644 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingfac... | 1 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == ... | 640 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase ={
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
"tokenization_... | 446 | """simple docstring"""
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_... | 644 | 0 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
... | 469 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _lowerCAmelCase ( nn.Module ):
__UpperCAmelCase : int
__UpperCAmelCase : ... | 178 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import... | 411 | """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_toke... | 644 | 0 |
"""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
lowerCAmelCase__ =logging.get_logger(__name__)
lowerCAmelCase__ ... | 482 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowercase__ :
def __init__( self )-> Optional[int]:
'''simple docstring'''
lowerCAmelCase__ = ""
lowerCAmelCase__ = ""
lowerCAmelCase__ ... | 339 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
def UpperCAmelCase__ ( lowerCamelCase_ : Tuple , lowerCamelCase_ : Optional[int] ):
while b:
__a , __a : Optional[int] = b, a % b
return a
def UpperCAmelCase__ ( lowerCamelCase_ : List[... | 47 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 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_pipel... | 593 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 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_torch_av... | 529 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
import re
from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class __lowerCamelCase (__UpperCamelCase ):
... | 1 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
return abs(lowerCamelCase__ ) if a == 0 else greatest_common_divisor(b % a , lowerCamelCase__ )
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCa... | 644 | 0 |
'''simple docstring'''
from math import factorial
def __magic_name__ ( __UpperCAmelCase = 100 ) -> Optional[int]:
'''simple docstring'''
return sum(int(lowerCamelCase__ ) for x in str(factorial(lowerCamelCase__ ) ) )
if __name__ == "__main__":
... | 640 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
'''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
lowercase =logging.get_logger(__name__)
lowercase ={
"facebook/levit... | 446 | """simple docstring"""
from collections.abc import Generator
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ = 0, 1
while True:
lowerCAmelCase__ , lowerCAmelCase__ = b, a + b
yield b
def _UpperCAmelCase ( ... | 644 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__A = logging.get_logger(__name__)
__A = {
"facebook/convnextv2-tiny-1k-224": "https://h... | 469 | """simple docstring"""
from __future__ import annotations
from statistics import mean
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = [0] * no_of_processes
lowerCAmelCase__ = [0] * no_of_proces... | 644 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 178 | """simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return getitem, k
def _UpperCAmelCase ( lowerCamelCase__ ... | 644 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {
"configuration_autoformer": [
"AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AutoformerConfig",
],
}
try:... | 411 | """simple docstring"""
from __future__ import annotations
from typing import Any
class a_ :
def __init__( self : Union[str, Any] , snake_case__ : int = 6 ):
lowerCAmelCase__ = None
lowerCAmelCase__ = None
self.create_linked_list(snake_case__ )
def ... | 644 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
lowerCAmelCase__ =lo... | 482 | """simple docstring"""
from itertools import permutations
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase__ = ... | 644 | 0 |
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tenso... | 339 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
if len(lowerCamelCase__ ) <= 1:
return lst
lowerCAmelCase__ = 1
while i < len(lowerCamelCase__ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
lowerCAmelCase__ , lowerCAm... | 644 | 0 |
from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProce... | 47 | """simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__lowerCAmelCase : Optional[int] = None
try:
import msvcrt
except ImportError:
__lowerCAmelCase : List[Any] = None
try:
import fcntl
except Impor... | 644 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __a ( lowerCAmelCase_ : Optional[Any] ,lowerCAmelCase_ : str ) -> Dict:
'''simple docstring'''
UpperCAme... | 593 | """simple docstring"""
import math
from datetime import datetime, timedelta
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = year % 19
lowerCAmelCase__ = year % 4
lowerCAmelCase__ = year % 7
lowerCAmelCase__ = math.floor(year / 100 )
... | 644 | 0 |
from itertools import permutations
def a__ ( A_ ):
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
__magic_name__ = [7, 11, 13, 17]
for i, te... | 529 | """simple docstring"""
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
... | 644 | 0 |
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 __lowerCamelCase (unittest.TestCase ):
def snake_case_ ... | 1 | """simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 644 | 0 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
a : Optional[int] = logging.get_logger(__name__)
def __magic_name__ ( __UpperCAmelCase ) ... | 640 | """simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCAmelCase : Optional[Any] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation ... | 644 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase ={
"configuration_electra": ["ELECTRA_PRETRAINED_CONFIG_ARCH... | 446 | """simple docstring"""
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_... | 644 | 0 |
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
__A = "\\n@misc{chen2021evaluating,\n title={Evaluating Large Lan... | 469 | """simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
lo... | 644 | 0 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Any
class _lowerCAmelCase :
def __init__( self , UpperCamelCase__ = None ) -> Union[str, Any]:
'''simple docstring'''
snake_case : List[str] = value
... | 178 | """simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : Dict = TypeVar("KT")
__lowerCAmelCase : Optional[Any] = TypeVar("VT")
class a_ ( Generic[KT, VT] ):
def __init__( s... | 644 | 0 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: List[Any] )-> List[str]:
_snak... | 411 | """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_toke... | 644 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMi... | 482 | """simple docstring"""
def _UpperCAmelCase ( lowerCamelCase__ ):
"""simple docstring"""
return " ".join(
"""""".join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rev... | 644 | 0 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase__ ( unittest.TestCase ):
def UpperCAmelCase ( self )-> str:
'''simple docstring'''
debug_launcher(te... | 339 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, fl... | 644 | 0 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mod... | 47 | """simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _UpperCAmelCase ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ ):
"... | 644 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __a ( lowerCAmelCase_ : List[Any] ,lowerCAmelCase_ : Any = True ,lowerCAmelCase_ : int = math.inf ,lowerCAmelCase_ : Tuple = -math.inf ,lowerCAmelCase_ : int = math.inf ,lowe... | 593 | """simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
__lowerCAmelCase : str = "__DUMMY_TRANSFORMERS_USER__"
__lowerCAmelCase : Dict = "Dummy User"
__lowe... | 644 | 0 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self : str , UpperCamelCase__ : list[tuple[float, float]] ) -> List[Any]:
... | 529 | """simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDi... | 644 | 0 |
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