code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ : str = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Deber... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
SCREAMING_SNAKE_CASE_ : Optional[i... | 685 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_uti... | 685 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 685 | 1 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigT... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 | 1 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase__ : List[str] = {'''processing_wav2vec2_with_lm''': ['''Wav2Vec2ProcessorWithLM''']}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
UpperCamelCa... | 685 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 | 1 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __Upp... | 685 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCam... | 685 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoi... | 685 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 1 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 1 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_test,
n... | 685 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 1 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __UpperCAmelCase ( lowerCamelCase_ : str , lowerCamelCas... | 685 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 1 |
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIFIER,
RequestCounter,... | 685 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __v... | 685 | 1 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
UpperCamelCase__ : Dict = '''<<<<<<< This should probably be modified because it mentions: '''
UpperCamelCase__ : ... | 685 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : list[int] ) -> list[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = len(lowerCamelCase_ )
for i in range(lowerCamelCase_ ):
for j in range(i + 1 , lowerCamelCase_ ):
... | 685 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(lowerCamelCase_ : float , ... | 685 | 1 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def __UpperCAmelCase ( lowerCamelCase_ : str , lowerCamelCase_ : List[str] , lowerCamelCase_ : int , lowerCamelCase_ : str ) -> Dict:
"""simple docstrin... | 685 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 685 | 1 |
UpperCamelCase__ : str = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
UpperCamelCase__ : List[Any] = ['''a''', '''b''', '''c''', '''d''', '''e''']
def __UpperCAmelCase ( lowerCamelCase_ : Optional[int] , l... | 685 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRob... | 685 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : Optional[int] = logging.get_logger(__name__)
UpperCamelCase__ : List[Any] = {
'''andrea... | 685 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def __... | 685 | 1 |
UpperCamelCase__ : Optional[Any] = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
UpperCamelCase__ : str = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def __UpperCAmelCase ( lowerCamelCase_ : dict[int, list[int]] , lowerCamelCase_ : int , ... | 685 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase__ : Any = 3_00 # TEMPERATURE (unit = K)
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , ) ... | 685 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
UpperCamelCase__ : Optional[int] = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''albert-large-... | 685 |
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ :
def __init__( self ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = [
[],
... | 685 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
UpperCamelCase__ : Dict = logging.getLogger(__name__)
@dataclass
class lowerCAmelCase_ ( lowerCamelCase_ ... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 10_00 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , lowerCamelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 685 | 1 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase_ ( lowerCamelCase_ ):
__a : List[Any] = (PNDMScheduler,)
__a : Union[str, Any] = (("num_inference_steps", ... | 685 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 | 1 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('''hub/hopper-medium-v2/unet/hor32''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/unet/hor128''', exist_ok=True)
os.makedirs('''hub/hopper-medium-v2/value_function''', exist_ok=True)
def __UpperCAmelCase ( ... | 685 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
UpperCamelCase__ : Union[str, Any] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', ''... | 685 | 1 |
from typing import Any
import numpy as np
def __UpperCAmelCase ( lowerCamelCase_ : np.ndarray ) -> bool:
"""simple docstring"""
return np.array_equal(lowerCamelCase_ , matrix.conjugate().T )
def __UpperCAmelCase ( lowerCamelCase_ :... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
SCREAMING_SNAKE_CASE_ : List[Any] = str... | 685 |
import qiskit
def __UpperCAmelCase ( lowerCamelCase_ : int = 2 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ : Optional[int] = q... | 685 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcessor, ResN... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
SCREAMING_SNAKE_CASE_ : Optional[i... | 685 | 1 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
... | 685 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 685 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def __UpperCAmelCase ( ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = Argumen... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 685 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
UpperCamelCase__ : List[str] = r'''
[`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and
can be used to control the model ... | 685 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCam... | 685 | 1 |
from string import ascii_lowercase, ascii_uppercase
def __UpperCAmelCase ( lowerCamelCase_ : str ) -> str:
"""simple docstring"""
if not sentence:
return ""
SCREAMING_SNAKE_CASE_ : Optional[int] = dict(zip(lowerCamelCase_ , lowe... | 685 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 1 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Any = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase__ : Optional[Any] = {
'''facebook/esm-1b''... | 685 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : str ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function' )
SCREAMING_SNAKE_CASE_ : D... | 685 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 1 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings('''ignore''', category=UserWarning, module='''torch.optim.lr_scheduler''')
class lowerCAmelCase_ ... | 685 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 1 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
UpperCamelCase__ : Any = logging.getLogger()
@unittest.skip("Temporarily disable the doc ... | 685 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __v... | 685 | 1 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_tensor
from diffuser... | 685 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 1 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
UpperCamelCase__ : List[Any] = logging.get_logger(__name__)... | 685 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(lowerCamelCase_ : float , ... | 685 | 1 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutput... | 685 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 685 | 1 |
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ :
def __init__( self ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = [
[],
... | 685 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRob... | 685 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : str = {
'''configuration_trajectory_transformer''': [
'''TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TrajectoryTransformerCon... | 685 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def __... | 685 | 1 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase__ : Any = 3_00 # TEMPERATURE (unit = K)
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , ) ... | 685 | 1 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ : int = logging.get_logger(__name__)
UpperCamelCase__ : Optiona... | 685 |
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ :
def __init__( self ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = [
[],
... | 685 | 1 |
# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 10_00 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , lowerCamelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 685 | 1 |
import qiskit
def __UpperCAmelCase ( lowerCamelCase_ : int = 2 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ : Optional[int] = q... | 685 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
UpperCamelCase__ : Union[str, Any] = logging.get_logger(__name__)... | 685 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
UpperCamelCase__ : Union[str, Any] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', ''... | 685 | 1 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _in... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 | 1 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging
... | 685 |
import qiskit
def __UpperCAmelCase ( lowerCamelCase_ : int = 2 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ : Optional[int] = q... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : str ) -> str:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[int] = ''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
SCREAMING_SNAKE_CASE_ : Optional[i... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 685 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mode... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 | 1 |
from collections.abc import Callable
class lowerCAmelCase_ :
def __init__( self ,snake_case__ = None ):
# Stores actual heap items.
SCREAMING_SNAKE_CASE_ : list = []
# Stores indexes of each item for supporting updates and deletion.
SCREA... | 685 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 | 1 |
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
UpperCamelCase__ : Optional[Any] = [
'''word_embeddin... | 685 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCam... | 685 | 1 |
UpperCamelCase__ : Optional[int] = range(2, 20 + 1)
UpperCamelCase__ : Dict = [10**k for k in range(ks[-1] + 1)]
UpperCamelCase__ : dict[int, dict[int, list[list[int]]]] = {}
def __UpperCAmelCase ( lowerCamelCase_ : Dict , lowerCamelCase_ : ... | 685 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Tuple = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV... | 685 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 1 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_... | 685 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 1 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase_ ( lowerCamelCase_ , unittest.TestCase ):
__a : Dict = ... | 685 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 1 |
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 GenerationTesterMixin
from ...test_co... | 685 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __v... | 685 | 1 |
UpperCamelCase__ : Any = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def __UpperCAmelCase ( lowerCamelCase_ : Optional[Any] , lowerCamelCase_ : str , ... | 685 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 1 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(lowerCamelCase_ : float , ... | 685 | 1 |
import copy
import random
from transformers import CLIPTokenizer
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**snake_case__ ):
super().__init__(*snake_case__ ,**snake_case__ )
SCREAMING_SNAKE_CASE_ : int ... | 685 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 685 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def __UpperCAmelCase ( lowerCamelCase_ : Optional[Any] ) -> str:
"""simple docstring"""
if (
(cp >= 0x4e_00 and cp <= 0x9f_ff)
or (cp >= ... | 685 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRob... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 10_00 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = -1
SCREAMING_SNAKE_CASE_ : Optional[Any] = 0
for a in range(1 , n // 3 ):
# Solving the two e... | 685 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def __... | 685 | 1 |
import colorsys
from PIL import Image # type: ignore
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : int ) -> float:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] ... | 685 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase__ : Any = 3_00 # TEMPERATURE (unit = K)
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , ) ... | 685 | 1 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
UpperCamelCase__ : Optional[int] = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Sea... | 685 |
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ :
def __init__( self ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = [
[],
... | 685 | 1 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def __UpperCAmelCase... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 10_00 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , lowerCamelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 685 | 1 |
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from transformers import Aut... | 685 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 | 1 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class lowerCAmelCase_ ( unittest.TestCase , lowerCamelCase_ ):
def snake_case ( self ):
SCREAMING_SNAKE_CASE_ : List[Any] = load_tool('text-classi... | 685 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
UpperCamelCase__ : Union[str, Any] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', ''... | 685 | 1 |
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 __UpperCAmelCase ( lowerCamelCase_ : ... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 | 1 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 |
import qiskit
def __UpperCAmelCase ( lowerCamelCase_ : int = 2 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ : Optional[int] = q... | 685 | 1 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCamelCase__ : List[Any] = 20_48
UpperCamelCase__ : Optional[Any] = 40_96
UpperCamelCase__ : Dict = 42
UpperCamelCase__ : Any = os.environ.pop('''PROCESS_TRAIN''', '''false''')
UpperCamelC... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
SCREAMING_SNAKE_CASE_ : Optional[i... | 685 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ : List[Any] = {
'''configuration_xlm_r... | 685 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 685 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_determ... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 | 1 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 | 1 |
from scipy.stats import pearsonr
import datasets
UpperCamelCase__ : Any = '''
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption t... | 685 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCam... | 685 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils imp... | 685 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 1 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since... | 685 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : Any = ... | 685 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 1 |
UpperCamelCase__ : Any = 8.31_44_62 # Unit - J mol-1 K-1
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float ) -> float:
"""simple docstring"""
if moles < 0 or kelvin < 0 or... | 685 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 1 |
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
fr... | 685 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __v... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 1 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, 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
from ...t... | 685 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(lowerCamelCase_ : float , ... | 685 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCamelCase__ : List[st... | 685 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 685 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.... | 685 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaTokenizerFast,
XLMRob... | 685 | 1 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoToken... | 685 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('dataset_size' , [None, 4_00 * 2**20, 6_00 * 2**20] )
@pytest.mark.parametrize('input_in_memory_max_size' , ['default', 0, 1_00 * 2**20, 9_00 * 2**20] )
def __... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 1_00 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = n * (n + 1) * (2 * n + 1) / 6
SCREAMING_SNAKE_CASE_ : Union[str, Any] = (n * (n + 1) / 2) ** 2
return int(sq... | 685 |
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCamelCase__ : Any = 3_00 # TEMPERATURE (unit = K)
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , ) ... | 685 | 1 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
UpperCamelCase__ : str = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**snake_case__ ):
... | 685 |
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ ( lowerCamelCase_ ):
pass
class lowerCAmelCase_ :
def __init__( self ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = [
[],
... | 685 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int = 10_00 ) -> int:
"""simple docstring"""
return sum(e for e in range(3 , lowerCamelCase_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 685 | 1 |
from __future__ import annotations
from collections.abc import Generator
def __UpperCAmelCase ( ) -> Generator[int, None, None]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : dict[int, int] = {}
SCREAMING_SNAKE_CASE_ : Any = 2
whil... | 685 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 | 1 |
from __future__ import annotations
from collections import namedtuple
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float ) -> tuple:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : ... | 685 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
UpperCamelCase__ : Union[str, Any] = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', ''... | 685 | 1 |
import cmath
import math
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float ) -> complex:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : A... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE_ : Tuple = 0
... | 685 | 1 |
from math import factorial
UpperCamelCase__ : Optional[Any] = {str(d): factorial(d) for d in range(10)}
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> int:
"""simple docstring"""
return sum(DIGIT_FACTORIAL[d] for d in str(lowerCamelCase_ ) ... | 685 |
import qiskit
def __UpperCAmelCase ( lowerCamelCase_ : int = 2 ) -> qiskit.result.counts.Counts:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE_ : Optional[int] = q... | 685 | 1 |
from __future__ import annotations
UpperCamelCase__ : List[Any] = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCamelCase_ , lowerCamelCase_ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
SCREAMING_SNAKE_CASE_ : Optional[i... | 685 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between check... | 685 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : Dict = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''',
... | 685 | 1 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ : Dict = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowerCamelCase_ ):
def __init__( self ,*snake_case__ ,**snake_case__ ... | 685 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int ) -> Tuple:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(lowerCamelCase_ , int(b / 2 ) ) * actual_power(lowerCamelCas... | 685 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCamelCase__ : Tuple = logging.get_logger(__name__)
UpperCamelCase__ : Dict = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggingface.co/CarlCochet/traje... | 685 |
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fro... | 685 | 1 |
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's easier to use for tuning th... | 685 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
UpperCam... | 685 | 1 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase_ ):
__a : Tuple = ["flax"]
def __init__( self ,*snake_case__ ,**snake_case__ ):
requires_backends(self ,['flax'] )
@classmethod
... | 685 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : int=() , lowerCamelCase_ ... | 685 | 1 |
def __UpperCAmelCase ( lowerCamelCase_ : List[str] ) -> Any:
"""simple docstring"""
stooge(lowerCamelCase_ , 0 , len(lowerCamelCase_ ) - 1 )
return arr
def __UpperCAmelCase ( lowerCamelCase_ : Optional[int] , ... | 685 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
UpperCamelCase__ : Tuple = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
UpperCamelCase__ : int = _LazyModule... | 685 | 1 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class lowerCAmelCase_ ( tf.keras.optimizers.schedules.LearningRateSchedu... | 685 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 685 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
de... | 685 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 1 |
from __future__ import annotations
from typing import Any
class lowerCAmelCase_ :
def __init__( self ,snake_case__ ):
SCREAMING_SNAKE_CASE_ : List[Any] = num_of_nodes
SCREAMING_SNAKE_CASE_ : list[list[int]] = []
SCREAMING_SNAKE... | 685 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __v... | 685 | 1 |
from __future__ import annotations
def __UpperCAmelCase ( lowerCamelCase_ : float , lowerCamelCase_ : float , lowerCamelCase_ : float , ) -> tuple[str, float]:
"""simple docstring"""
if (stress, tangential_force, area).count(0 ... | 685 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Dict = logging.get_logger(__name__)
UpperCamelCase__ : Optional[int] = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
... | 685 | 1 |
import numpy as np
from transformers import Pipeline
def __UpperCAmelCase ( lowerCamelCase_ : Optional[Any] ) -> Optional[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = np.max(lowerCamelCase_ , axis=-1 , keep... | 685 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __UpperCAmelCase ( lowerCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
def is_in_circle(lowerCamelCase_ : float , ... | 685 | 1 |
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