code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase ( UpperCAmelCase__ : list[int] ) -> Optional[int]:
lowercase_ : List[str] = len(UpperCAmelCase__ ) // 2
# choose the middle 3 elements
lowercase_ : Optional[Any] ... | 369 | '''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : Any = prime_factors(UpperCAmelCase__ )
if is_square_free(UpperCAmelCase__ ... | 21 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils impor... | 370 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000000 ) -> int:
lowercase_ : List[Any] = limit + 1
lowercase_ : Optional[Any] = [0] * limit
for first_term in range(1 , UpperCAmelCase__ ):
for n in r... | 21 | 0 |
from __future__ import annotations
class __magic_name__ :
def __init__( self : Optional[int] , lowercase_ : int ):
lowercase_ : str = data
lowercase_ : Node | None = None
lowercase_ : Node | None = None
... | 371 | '''simple docstring'''
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_stagin... | 21 | 0 |
'''simple docstring'''
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@r... | 350 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 0 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
_lowercase : List[Any] = """... | 351 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import x... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : Dict , UpperCAmelCase__ : List[str] = 0 ) -> Dict:
lowercase_ : str = length or len(lowerCamelCase__ )
lowercase_ : Dict = False
for i in range(length - 1 ):
... | 352 | '''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> float:
lowercase_ : List[Any] = x
lowercase_ : Any = ... | 21 | 0 |
'''simple docstring'''
_lowercase : Union[str, Any] = {str(digit): digit**5 for digit in range(10)}
def lowerCamelCase ( UpperCAmelCase__ : List[str] ) -> Optional[int]:
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_lowerCAmelCase ) )
def l... | 353 | '''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__... | 21 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTeste... | 354 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowercase : Union[str, Any] = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise Optional... | 21 | 0 |
'''simple docstring'''
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class __magic_name__ ( snake_case_):
UpperCamelCase__ = '''M-CLIP'''
def __init__( self : Optional[Any] , lowercase_ : int=1024 , lowercase_ :... | 355 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Union[str, Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
... | 21 | 0 |
'''simple docstring'''
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class __magic_name__ ( __lowerCAmelCase):
def __init__( ... | 356 | '''simple docstring'''
import os
import numpy
import onnx
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Tuple:
lowercase_ : Tuple = a.name
lowercase_ : Tuple = b.name
lowercase_ : Any ... | 21 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : List[str] = {"configuration_xlnet": ["XLNE... | 357 | '''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
... | 21 | 0 |
'''simple docstring'''
_lowercase : Optional[int] = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T'... | 358 | '''simple docstring'''
class __magic_name__ :
def __init__( self : int , lowercase_ : list ):
lowercase_ : Dict = set_counts
lowercase_ : List[Any] = max(lowercase_ )
lowercase_ : str = len(lowercase_ ... | 21 | 0 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
_lowercase : Optional[Any] = "\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n ... | 359 | '''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from de... | 21 | 0 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 360 | '''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availab... | 21 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, re... | 361 | '''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ... | 21 | 0 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transformers.te... | 362 | '''simple docstring'''
def lowerCamelCase ( ) -> Dict:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple = 1
while len(UpperCAmelCase__ ) < 1e6:
constant.append(str(UpperCAmelCase__ ) )
i += 1
lowerc... | 21 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
re... | 363 | '''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : Union[str, Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
cla... | 21 | 0 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCamelCase ( UpperCAmelCase__ : str = "" ) -> Optional[int]:
lowercase_ : Optional[Any] = url or """https://www.imdb.com/chart/top/?ref_=nv_mv_250"""
lowercase_ :... | 364 | '''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowercase : Union[str, Any] ... | 21 | 0 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_lowercase : Union[str, A... | 365 | '''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __magic_name__ ( ctypes.Structure):
# _fields is a specific attr expected by ctypes
UpperCamelCase__ ... | 21 | 0 |
'''simple docstring'''
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,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepI... | 366 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_av... | 21 | 0 |
'''simple docstring'''
from __future__ import annotations
import queue
class __magic_name__ :
def __init__( self : Any , lowercase_ : Dict ):
lowercase_ : Dict = data
lowercase_ : Optional[int] = None
lowercase_ ... | 367 | '''simple docstring'''
from __future__ import annotations
from typing import Any
def lowerCamelCase ( UpperCAmelCase__ : list ) -> int:
if not postfix_notation:
return 0
lowercase_ : Any = {"""+""", """-""", """*""", """/"""}
lowercase_ ... | 21 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
_lowercase : int = {
"configuration_speecht5": [
"SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 368 | '''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
def lowerCamelCase ( UpperCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list ) -> list:
if len(_lowerCamelCase ) <= 1:
return [tuple(_lowerCamelCase )]
lowercase_ : Union[str, Any] = []
def generate(UpperCAmelCase__ : int , UpperCAmelCase_... | 369 | '''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : Any = prime_factors(UpperCAmelCase__ )
if is_square_free(UpperCAmelCase__ ... | 21 | 0 |
'''simple docstring'''
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is... | 370 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000000 ) -> int:
lowercase_ : List[Any] = limit + 1
lowercase_ : Optional[Any] = [0] * limit
for first_term in range(1 , UpperCAmelCase__ ):
for n in r... | 21 | 0 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase : List[Any] = logging.get_logger(__name__)
def lowerCamelCase ( UpperCAmelCase__ : Any ) -> U... | 371 | '''simple docstring'''
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_stagin... | 21 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Optional[Any] = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
... | 350 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 0 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
_lowercase : int = '__DUMMY_TRANSFORMERS_USER__'
_lowercase : List[Any] = 'Dummy User'
_lowercase ... | 351 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import x... | 21 | 0 |
'''simple docstring'''
_lowercase : Union[str, Any] = range(2, 20 + 1)
_lowercase : Dict = [10**k for k in range(ks[-1] + 1)]
_lowercase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase ( UpperCAmelCase__ : Tuple , UpperCAmelC... | 352 | '''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> float:
lowercase_ : List[Any] = x
lowercase_ : Any = ... | 21 | 0 |
'''simple docstring'''
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ... | 353 | '''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__... | 21 | 0 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowerCamelCase ( UpperCAmelCase__ : Any , UpperCAmelCase__ : int , UpperCAmelCase__ : Tuple=None , **UpperCAmelCase__ : Union[str, Any] ) -> Any:
lowercase_ : Tuple ... | 354 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowercase : Union[str, Any] = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise Optional... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] ) -> list[list]:
lowercase_ : Any = current_set.copy()
for row_index, row in enumerate(__UpperCAmelCase ):
lowercase_ : int = row[0]
for column... | 355 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Union[str, Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
... | 21 | 0 |
'''simple docstring'''
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
_lowercase : Any = yaml.safe_load(
"\\nname: \"\"\nallow_empty: false\nallow_empty_text: true\nsubs... | 356 | '''simple docstring'''
import os
import numpy
import onnx
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Tuple:
lowercase_ : Tuple = a.name
lowercase_ : Tuple = b.name
lowercase_ : Any ... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : List[str] , UpperCAmelCase__ : Dict ) -> List[Any]:
return number | (1 << position)
def lowerCamelCase ( UpperCAmelCase__ : List[str] , UpperCAmelCase__ : Optional[Any] ) -> Union[s... | 357 | '''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
... | 21 | 0 |
'''simple docstring'''
import os
def lowerCamelCase ( ) -> List[Any]:
lowercase_ : Dict = os.path.join(os.path.dirname(_lowercase ) , """num.txt""" )
with open(_lowercase ) as file_hand:
return str(sum(int(_lowercase ) for line in fil... | 358 | '''simple docstring'''
class __magic_name__ :
def __init__( self : int , lowercase_ : list ):
lowercase_ : Dict = set_counts
lowercase_ : List[Any] = max(lowercase_ )
lowercase_ : str = len(lowercase_ ... | 21 | 0 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class __magic_name__ :
def __init__( self : Optional[Any] ... | 359 | '''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from de... | 21 | 0 |
import logging
import os
from .state import PartialState
class __magic_name__ ( logging.LoggerAdapter):
@staticmethod
def SCREAMING_SNAKE_CASE_ ( lowercase_ : int ):
lowercase_ : Any = PartialState()
return not main_process_only or (main_... | 360 | '''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availab... | 21 | 0 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spect... | 361 | '''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ... | 21 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemant... | 362 | '''simple docstring'''
def lowerCamelCase ( ) -> Dict:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple = 1
while len(UpperCAmelCase__ ) < 1e6:
constant.append(str(UpperCAmelCase__ ) )
i += 1
lowerc... | 21 | 0 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCamelCase ( ... | 363 | '''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : Union[str, Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
cla... | 21 | 0 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def lowerCamelCase ( UpperCAmelCase__ : Dict , U... | 364 | '''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowercase : Union[str, Any] ... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Optional[int]:
"""simple docstring"""
lowercase_ : str = len(lowerCAmelCase__ )
lowercase_ : Any = sum(lowerCAmelCase__ )
lowercase_ : Tuple ... | 365 | '''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __magic_name__ ( ctypes.Structure):
# _fields is a specific attr expected by ctypes
UpperCamelCase__ ... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : Optional[Any] ):
lowercase_ : Any = current_set.copy()
for row_index, row in enumerate(SCREAMING_SNAKE_CASE__ ):
lowercase_ : Optional[int] = row[0]
for column_index... | 366 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_av... | 21 | 0 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class __magic_name__ ( unittest.TestCase):
@r... | 367 | '''simple docstring'''
from __future__ import annotations
from typing import Any
def lowerCamelCase ( UpperCAmelCase__ : list ) -> int:
if not postfix_notation:
return 0
lowercase_ : Any = {"""+""", """-""", """*""", """/"""}
lowercase_ ... | 21 | 0 |
'''simple docstring'''
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from t... | 368 | '''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
def lowerCamelCase ( UpperCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[... | 21 | 0 |
'''simple docstring'''
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 .tra... | 369 | '''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : Any = prime_factors(UpperCAmelCase__ )
if is_square_free(UpperCAmelCase__ ... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int ) -> List[Any]:
while second != 0:
lowercase_ : str = first & second
first ^= second
lowercase_ : Optional[Any] ... | 370 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000000 ) -> int:
lowercase_ : List[Any] = limit + 1
lowercase_ : Optional[Any] = [0] * limit
for first_term in range(1 , UpperCAmelCase__ ):
for n in r... | 21 | 0 |
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Optional[int]:
if not isinstance(__a , __a ):
raise ValueError("""Input series is not valid, valid series - [2, 4, 6]""" )
if len(__a ) == 0:
raise ValueError("""Input list must be a non empt... | 371 | '''simple docstring'''
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_stagin... | 21 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
_lowercase : Optional[int] = {"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP",... | 350 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000 ) -> List[Any]:
lowercase_ : int = -1
lowercase_ : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N elim... | 351 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import x... | 21 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.util... | 352 | '''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> float:
lowercase_ : List[Any] = x
lowercase_ : Any = ... | 21 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowercase : Tuple = logging.get_logger(__name__)
_lowerca... | 353 | '''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__... | 21 | 0 |
'''simple docstring'''
from math import isqrt, loga
def lowerCamelCase ( UpperCAmelCase__ : List[Any] ) -> Union[str, Any]:
lowercase_ : Optional[int] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]... | 354 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowercase : Union[str, Any] = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise Optional... | 21 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class __magic_name__ :
UpperCamelCase__ = None
UpperCamelCase__ = False
UpperCamelCase__ = False
UpperCamelCase__ = False
UpperCam... | 355 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Union[str, Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
... | 21 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from ... | 356 | '''simple docstring'''
import os
import numpy
import onnx
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Tuple:
lowercase_ : Tuple = a.name
lowercase_ : Tuple = b.name
lowercase_ : Any ... | 21 | 0 |
'''simple docstring'''
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigT... | 357 | '''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
... | 21 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
_lowercase : Tuple = pd.read_csv("sample_data.csv", header=Non... | 358 | '''simple docstring'''
class __magic_name__ :
def __init__( self : int , lowercase_ : list ):
lowercase_ : Dict = set_counts
lowercase_ : List[Any] = max(lowercase_ )
lowercase_ : str = len(lowercase_ ... | 21 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_lowercase : List[Any] = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available(... | 359 | '''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from de... | 21 | 0 |
def lowerCamelCase ( UpperCAmelCase__ : int = 10**12 ) -> int:
lowercase_ : List[Any] = 1
lowercase_ : Optional[Any] = 0
lowercase_ : int = 1
lowercase_ : str = 1
while numerator <= 2 * min_total - 1:
... | 360 | '''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availab... | 21 | 0 |
'''simple docstring'''
from PIL import Image
def lowerCamelCase ( UpperCAmelCase__ : Any , UpperCAmelCase__ : Tuple ) -> Image:
def brightness(UpperCAmelCase__ : Tuple ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
... | 361 | '''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ... | 21 | 0 |
'''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, Bert... | 362 | '''simple docstring'''
def lowerCamelCase ( ) -> Dict:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple = 1
while len(UpperCAmelCase__ ) < 1e6:
constant.append(str(UpperCAmelCase__ ) )
i += 1
lowerc... | 21 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import float... | 363 | '''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : Union[str, Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
cla... | 21 | 0 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase ( UpperCAmelCase__ : Tuple , UpperCAmelCase__ : int , UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Any:
lowercase_ : Tuple = sorted(zip(snake_case__ , ... | 364 | '''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowercase : Union[str, Any] ... | 21 | 0 |
'''simple docstring'''
import math
def lowerCamelCase ( UpperCAmelCase__ : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 365 | '''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __magic_name__ ( ctypes.Structure):
# _fields is a specific attr expected by ctypes
UpperCamelCase__ ... | 21 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from typing import Any
class __magic_name__ :
def __init__( self : Union[str, Any] ):
lowercase_ : list[Any] = []
lowercase_ : int = 0
lower... | 366 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_av... | 21 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_f... | 367 | '''simple docstring'''
from __future__ import annotations
from typing import Any
def lowerCamelCase ( UpperCAmelCase__ : list ) -> int:
if not postfix_notation:
return 0
lowercase_ : Any = {"""+""", """-""", """*""", """/"""}
lowercase_ ... | 21 | 0 |
'''simple docstring'''
import baseaa
def lowerCamelCase ( UpperCAmelCase__ : str ) -> bytes:
return baseaa.aaaencode(string.encode("""utf-8""" ) )
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] ) -> str:
return baseaa.aaadecode(lower... | 368 | '''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
def lowerCamelCase ( UpperCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[... | 21 | 0 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRCon... | 369 | '''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : Any = prime_factors(UpperCAmelCase__ )
if is_square_free(UpperCAmelCase__ ... | 21 | 0 |
'''simple docstring'''
import warnings
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 : Optional[int] = logging.get_log... | 370 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000000 ) -> int:
lowercase_ : List[Any] = limit + 1
lowercase_ : Optional[Any] = [0] * limit
for first_term in range(1 , UpperCAmelCase__ ):
for n in r... | 21 | 0 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
_lowercase : int = logging.get_logger(__name__)
def lowerCamelCase ( UpperCAme... | 371 | '''simple docstring'''
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_stagin... | 21 | 0 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
cl... | 350 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 0 |
'''simple docstring'''
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCamelCase ( UpperCAmelCase__ : ndarray ) -> float:
return np.dot(UpperCAmelCase__ , UpperCAmelCase__ )
class __magic_name__ ... | 351 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import x... | 21 | 0 |
'''simple docstring'''
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Any = {
"snap-research/efficientformer-l1-300": (
"https://huggin... | 352 | '''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> float:
lowercase_ : List[Any] = x
lowercase_ : Any = ... | 21 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowercase : Any = logging.get_logger(__name__)
_lowercase : List[Any] = {
"SenseTime/deformable-detr": "https://huggingface... | 353 | '''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__... | 21 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( _UpperCAmelCase):
Upp... | 354 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowercase : Union[str, Any] = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise Optional... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : list ) -> list:
def merge(UpperCAmelCase__ : list , UpperCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= ... | 355 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Union[str, Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
... | 21 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
def lowerCamelCase ( UpperCAmelCase__ : str ) -> dict:
lowercase_ : Any = F'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(UpperCAmelCa... | 356 | '''simple docstring'''
import os
import numpy
import onnx
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Tuple:
lowercase_ : Tuple = a.name
lowercase_ : Tuple = b.name
lowercase_ : Any ... | 21 | 0 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 357 | '''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
... | 21 | 0 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_toke... | 358 | '''simple docstring'''
class __magic_name__ :
def __init__( self : int , lowercase_ : list ):
lowercase_ : Dict = set_counts
lowercase_ : List[Any] = max(lowercase_ )
lowercase_ : str = len(lowercase_ ... | 21 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowercase : int = logging.get_logge... | 359 | '''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from de... | 21 | 0 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def lowerCamelCase ( UpperCAmelCase__ : Dict[str, torch.Tensor] ) -> Dict[str, torch.Tensor]:
lowercase_ : Tuple = []
... | 360 | '''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availab... | 21 | 0 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequenceC... | 361 | '''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ... | 21 | 0 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowercase : Optional[Any] = ... | 362 | '''simple docstring'''
def lowerCamelCase ( ) -> Dict:
lowercase_ : Union[str, Any] = []
lowercase_ : Tuple = 1
while len(UpperCAmelCase__ ) < 1e6:
constant.append(str(UpperCAmelCase__ ) )
i += 1
lowerc... | 21 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCamelCase ( UpperCAmelCase__ : Union[str, Any] , UpperCAmelCase__ : str , UpperCAmelCase__ : str ,... | 363 | '''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowercase : Union[str, Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
cla... | 21 | 0 |
import os
from collections.abc import Iterator
def lowerCamelCase ( UpperCAmelCase__ : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(UpperCAmelCase__ ):
lowercase_ : Dict = [d for d in dir_names if d != """scripts""" and d[0]... | 364 | '''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowercase : Union[str, Any] ... | 21 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ... | 365 | '''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __magic_name__ ( ctypes.Structure):
# _fields is a specific attr expected by ctypes
UpperCamelCase__ ... | 21 | 0 |
'''simple docstring'''
import argparse
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_seed
from accelerate import A... | 366 | '''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_av... | 21 | 0 |
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowerCamelCase ( UpperCAmelCase__ : Tuple ) -> Optional[int]:
return x + 2
class __magic_name__ ( unittest.Tes... | 367 | '''simple docstring'''
from __future__ import annotations
from typing import Any
def lowerCamelCase ( UpperCAmelCase__ : list ) -> int:
if not postfix_notation:
return 0
lowercase_ : Any = {"""+""", """-""", """*""", """/"""}
lowercase_ ... | 21 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_co... | 368 | '''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
def lowerCamelCase ( UpperCAmelCase__ : Union[tf.Tensor, np.ndarray] ) -> List[... | 21 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowercase : Union[str, Any] = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise Optional... | 369 | '''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def lowerCamelCase ( UpperCAmelCase__ : int ) -> int:
lowercase_ : Any = prime_factors(UpperCAmelCase__ )
if is_square_free(UpperCAmelCase__ ... | 21 | 0 |
'''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] ) -> Union[str, Any]:
lowercase_ : List[str] = []
lowercase_ : Optional[Any] = []
lowercase_ : List[str] = {
"""^""": 3,
""... | 370 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000000 ) -> int:
lowercase_ : List[Any] = limit + 1
lowercase_ : Optional[Any] = [0] * limit
for first_term in range(1 , UpperCAmelCase__ ):
for n in r... | 21 | 0 |
from __future__ import annotations
from typing import Any
def lowerCamelCase ( UpperCAmelCase__ : list ) -> int:
if not postfix_notation:
return 0
lowercase_ : Any = {"""+""", """-""", """*""", """/"""}
lowercase_ : list[Any] =... | 371 | '''simple docstring'''
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_stagin... | 21 | 0 |
'''simple docstring'''
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __magic_name__ ( unittest.TestCase):
UpperCamelCase__ = JukeboxTokenizer
UpperCamelCase__ = {
'''artist''': '''Zac Brown Band''',
'''g... | 350 | '''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase ( UpperCAmelCase__ : List[Any] , UpperCAmelCase__ : Op... | 21 | 0 |
'''simple docstring'''
import random
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : float , UpperCAmelCase__ : bool = False ) -> dict:
lowercase_ : dict = {i: [] for i in range(UpperCAmelCase__ )}
# if probability is greater or... | 351 | '''simple docstring'''
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import x... | 21 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils impo... | 352 | '''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def lowerCamelCase ( UpperCAmelCase__ : float , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> float:
lowercase_ : List[Any] = x
lowercase_ : Any = ... | 21 | 0 |
'''simple docstring'''
from manim import *
class __magic_name__ ( _UpperCAmelCase):
def SCREAMING_SNAKE_CASE_ ( self : Optional[Any] ):
lowercase_ : List[Any] = Rectangle(height=0.5 , width=0.5 )
lowercase_ : Optional[Any] ... | 353 | '''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __magic_name__ ( _UpperCAmelCase):
UpperCamelCase__... | 21 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : int = {"ctrl": "https://huggingface.co/ctrl/resolve/main/config.json"}
class __magic_name__ ( _Uppe... | 354 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowercase : Union[str, Any] = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise Optional... | 21 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_d... | 355 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowercase : Union[str, Any] = {
"configuration_encodec": [
"ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EncodecConfig",
... | 21 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids... | 356 | '''simple docstring'''
import os
import numpy
import onnx
def lowerCamelCase ( UpperCAmelCase__ : Optional[int] , UpperCAmelCase__ : str ) -> Tuple:
lowercase_ : Tuple = a.name
lowercase_ : Tuple = b.name
lowercase_ : Any ... | 21 | 0 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
Autoencode... | 357 | '''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
... | 21 | 0 |
'''simple docstring'''
import re
def lowerCamelCase ( UpperCAmelCase__ : str ) -> bool:
lowercase_ : Any = re.compile(
R"""^(?:0|94|\+94|0{2}94)""" R"""7(0|1|2|4|5|6|7|8)""" R"""(-| |)""" R"""\d{7}$""" )
return bool(re.search(UpperCAmelCase__ ... | 358 | '''simple docstring'''
class __magic_name__ :
def __init__( self : int , lowercase_ : list ):
lowercase_ : Dict = set_counts
lowercase_ : List[Any] = max(lowercase_ )
lowercase_ : str = len(lowercase_ ... | 21 | 0 |
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