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 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
import numpy as np
from transformers import AlbertConfig, 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... | 646 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def __UpperCamelCase ( _A : Sequence[float] , _A : bool = False ) -> float:
"""simple docstring"""
if not arr:
return 0
lowerCAmelCase : Union[str, Any] = 0 if allow_empty_subarray... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Any = {
'k... | 646 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 1 |
'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeature... | 646 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_F... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 1 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto ... | 646 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _A : Optional[int] ) -> List[str]:
"""simple docstring"""
if collection == []:
return []
# get some information about the collection
lowerCAmelCase : Tuple = len(_A )
lowerCAmelCase : Any ... | 646 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( _A : int , _A : int ) -> list[list[int]]:
"""simple docstring"""
lowerCAmelCase : list[list[int]] = []
create_all_state(1 , _A , _A , [] , ... | 646 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 1 |
'''simple docstring'''
from queue import PriorityQueue
from typing import Any
import numpy as np
def __UpperCamelCase ( _A : dict , _A : str , _A : set , _A : set , _A : dict , _A : dict , _A : PriorityQueue , _A : ... | 646 |
'''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 Confi... | 646 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 1 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowerCAmelCase : List[str] = 300 # TEMPERATURE (unit = K)
def __UpperCamelCase ( _A : float , _A : float , _A : float , ) -> float:
"""simpl... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 1 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase : List[str] = []
lowerCAmelCase : Optional[Any] = 2
lowerCAmelCase : Dict = int(math.sqrt(_A ... | 646 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
_lowerCAmelCase : List[Any] = 8.988E9 # units = N * m^s * C^-2
def __UpperCamelCase ( _A : float , _A : float , _A : float , _A : float ) -> dict[str, float]:
"""simple docstrin... | 646 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 1 |
'''simple docstring'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __UpperCamelCase ( _A : str = "isbn/0140328726" ) -> dict:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = olid.str... | 646 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowerCAmelCase ( nn.Module ):
_lowerCamelCase : int
_lowerCamelCase : int
_l... | 646 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 1 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
_low... | 646 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 1 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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... | 646 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 646 | 1 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import... | 646 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 1 |
'''simple docstring'''
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
def __UpperCamelCase ( _A : List[Any... | 646 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _A : str ) -> bool:
"""simple docstring"""
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
lowerCAmelCase : List[Any] = sorted(string.lowe... | 646 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 1 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
def __init__( self , snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__=0.2 , snake_case__=0.2 ):
lowerCAmelCas... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : List[Any] = logging.get_logger(__name__)
_lowerCAmelCa... | 646 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
_lowerCAmel... | 646 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase : Tuple = {
'configuration_encodec': [
'ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP',
'EncodecConfig',
],
... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 1 |
'''simple docstring'''
from math import ceil, sqrt
def __UpperCamelCase ( _A : int = 1_00_00_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : Optional[Any] = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
... | 646 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 1 |
'''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 Confi... | 646 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, ... | 646 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 1 |
'''simple docstring'''
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 1 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class lowerCAmelCase ( yaml.SafeLoader ):
def lowercase ( self , snake_case__ ):
lowerCAmelCase : Union[str, Any] = [self.con... | 646 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : int = {
'configuration_upernet': ['UperNetConfig'],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()... | 646 |
'''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 Confi... | 646 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 646 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
if not isinstance(_A , _A ):
raise ValueError('multiplicative_persistence() only accepts integral values' )
if num < 0:
raise ValueError('multiplicative_persistence() does... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( _A : list[int | str] ) -> None:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 , [0 for i in range(len(_A ) )] )
def __UpperCamelCase ( _A : ... | 646 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
_lowerCAmelCase : Tuple = logging.getLogger(... | 646 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 1 |
'''simple docstring'''
import re
def __UpperCamelCase ( _A : str ) -> bool:
"""simple docstring"""
lowerCAmelCase : Tuple = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(_A , _A ):
return match.string == phone
re... | 646 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 1 |
'''simple docstring'''
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 646 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 1 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@requir... | 646 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCAmelCase : Any = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokenization_tra... | 646 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 646 | 1 |
'''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def __UpperCamelCase ( _A : List[str] , _A : Optional[int]=10_00 ) -> Any:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
lowe... | 646 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase : Dict = {'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAE... | 646 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils... | 646 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 1 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 1 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __UpperCamelCase ( _A : Optional[int] , _A : ... | 646 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 1 |
'''simple docstring'''
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
_lowerCAmelCase : int = 0b10_11_00_11_11_10_11_00_10_01_00_... | 646 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cache... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 1 |
'''simple docstring'''
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
_lowerCAmelCase : Union[str, Any] = logging.g... | 646 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 1 |
'''simple docstring'''
import argparse
import struct
import unittest
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
# Initialize hash values
lowerCAmelCase : int = [
0X6a_09e_667,
0Xb... | 646 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : int = {
'configuration_blenderbot': [
'BL... | 646 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 1 |
'''simple docstring'''
_lowerCAmelCase : str = 6_5521
def __UpperCamelCase ( _A : str ) -> int:
"""simple docstring"""
lowerCAmelCase : List[str] = 1
lowerCAmelCase : Union[str, Any] = 0
for plain_chr in plain_text:
lowerCAme... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 1 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def __UpperCamelCase ( _A : Tuple ) -> List[Any]:
"""simple docstring"""
lowerCAmelCase , lowerCAmelCase : int = img.shape[0], img.shape[1]
# converting each pixel'... | 646 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 646 |
'''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 Confi... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_tens... | 646 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 1 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 1 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 646 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 1 |
'''simple docstring'''
import unittest
from transformers import MPNetConfig, 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
... | 646 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .... | 646 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 1 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_att... | 646 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowerCAmelCase ( unittest.TestCase ):
_lowerCamelCase ... | 646 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Tuple = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Condi... | 646 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 1 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_va... | 646 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 1 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : int = {
'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json',
#... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 1 |
'''simple docstring'''
from string import ascii_uppercase
_lowerCAmelCase : List[str] = {char: i for i, char in enumerate(ascii_uppercase)}
_lowerCAmelCase : List[Any] = dict(enumerate(ascii_uppercase))
def __UpperCamelCase ( _A : str , _A : str ) -> str:
... | 646 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 1 |
'''simple docstring'''
import enum
import shutil
import sys
_lowerCAmelCase , _lowerCAmelCase : Tuple = shutil.get_terminal_size()
_lowerCAmelCase : List[Any] = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class lowerCAmelCase ( enum.Enum ):
_lowerCamelCase :... | 646 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( _A : Callable[[int | float], int | float] , _A : int | float , _A : int | float , _A : int = 1_00 , ) -> float:
"""simple d... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 1 |
'''simple docstring'''
from math import factorial
def __UpperCamelCase ( _A : int = 20 ) -> int:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
lowerCAme... | 646 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 1 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_lowerCAmelCase : Any = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title... | 646 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 1 |
'''simple docstring'''
from math import sqrt
def __UpperCamelCase ( _A : int = 1_00_00_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : int = 0
lowerCAmelCase : int = 0
lowerCAmelCase : int
while num_cuboids <= limit:
ma... | 646 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 1 |
'''simple docstring'''
from decimal import Decimal, getcontext
from math import ceil, factorial
def __UpperCamelCase ( _A : int ) -> str:
"""simple docstring"""
if not isinstance(_A , _A ):
raise TypeError('Undefined for non-integers' )
elif precision < 1:
r... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
_lowerCAmelCase : Tuple = TypeVar('T')
_lowerCAmelCase : Optional[int] = TypeVar('U')
class lowerCAmelCase ( Generic[T, U] ):
def __init__( ... | 646 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 1 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
_lowerCAmelCa... | 646 |
'''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 Confi... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_lowerCAmelCase : List[Any] = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNot... | 646 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase : Any = {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig'... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase ( a ):
_lowerCamelCas... | 646 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 1 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 1 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[Any] = len(snake_case__ )
lowerCAmelCase : Tuple = [0] * len_array
if len_array > 0:
lowerCAmelCase : Optional[int] ... | 646 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 1 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCAmelCase : List[str] = {
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
... | 646 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _A : int , _A : int ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def __UpperCamelCase ( ) -> None:
"""simple docstring"""
assert and_gate(0 , ... | 646 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Toke... | 646 | 1 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
_lowerCAmelCase : Optional[int] = '\\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 ... | 646 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_... | 646 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 1 |
'''simple docstring'''
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathl... | 646 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
lowerCAmelCase : int = int(number**0.5 )
return number == sq * sq
de... | 646 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( _A : list[int] , _A : int ) -> int:
"""simple docstring"""
if len(_A ) < k or k < 0:
raise ValueError('Invalid Input' )
lowerCAmelCase : Optional[Any] = s... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( _A : list[float] ) -> bool:
"""simple docstring"""
if len(_A ) < 2:
raise ValueError('Monogons and Digons are not polygons in the Euclidean space' )
if any(i <= 0 for i in nums ):
... | 646 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
_lowerCAmelCase : str = logging.get_logger(__name... | 646 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 1 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from ... | 646 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 1 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
if num < 0:
return False
lowerCAmelCase : int = num
lowerCAmelCase : int = 0
while num > 0:
lowerCAmelCase : List[str] = r... | 646 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 1 |
'''simple docstring'''
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
lowerCAmelCase : Tuple = prime_factors(_A )
if is_square_free(_A ):... | 646 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
_lowerCAmelCase : Tuple = TypeVar('KT')
_lowerCAmelCase : Optional[int] = TypeVar('VT')
class lowerCAmelCase ( Generic[KT, VT] ):
def __init__( self , ... | 646 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 646 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 1 |
'''simple docstring'''
from collections import namedtuple
_lowerCAmelCase : Tuple = namedtuple('from_to', 'from_ to')
_lowerCAmelCase : List[Any] = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 1000),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 2_6_4.1_... | 646 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : Optional[int] = {
'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
't... | 646 |
'''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 Confi... | 646 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : str = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase ( a... | 646 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.