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 argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
__lowerCamel... | 656 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowerCamelCase : str = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
... | 656 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNe... | 656 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
snake_case_ : Any = {
... | 656 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from... | 656 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__lowerCamelCase : Dict = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINE... | 656 | 1 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__lowerCamelCase : List[Any] = argparse.ArgumentParser()... | 656 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(__magic_name__ ,__magic_name__ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 ... | 656 | 1 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __UpperCAmelCase ( __magic_name__ ,__magic_name__=False )-> Dict:
"""simple docstring"""
snake_case_ : ... | 656 |
'''simple docstring'''
# Copyright 2021 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/l... | 656 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_atte... | 656 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : str = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 a... | 656 | 1 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import da... | 656 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 656 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : List[str] = {'''configurat... | 656 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
__lowerCamelCase : ... | 656 | 1 |
'''simple docstring'''
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
... | 656 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from data... | 656 | 1 |
'''simple docstring'''
from collections import deque
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowerCAmelCase__ :str , lowerCAmelCase__ :int , lowerCAmelCase__ :int ) -> None:
... | 656 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokenize... | 656 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
... | 656 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b ,2 ... | 656 | 1 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
__lowerCamelCase : Tuple = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
... | 656 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__=None ,**__magic_name__ )-> Optional[Any]:
"""simple docstring"""
snake_case_ : int = ... | 656 | 1 |
'''simple docstring'''
__lowerCamelCase : int = {str(digit): digit**5 for digit in range(10)}
def __UpperCAmelCase ( __magic_name__ )-> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(__magic_name__ ) ... | 656 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrFor... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> bool:
"""simple docstring"""
snake_case_ : Union[str, Any] = get_failure_array(__magic_name__ )
# 2) Step through... | 656 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.ima... | 656 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
__lowerCamelCase : List[str] = logging.get_logger(__name__)
class A_ (a_ ):
"""simple docstring"""
... | 656 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, n... | 656 | 1 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : str = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 a... | 656 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, ... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> bool:
"""simple docstring"""
return credit_card_number.startswith(("34", "35", "37", "4", "5", "6") )
def __UpperCAmelCase ( __magic_name__ )-> bool:
"""simple docs... | 656 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( __magic_name__ ,__magic_name__=() ,__magic_name__=... | 656 | 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_configu... | 656 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Dict ) -> List[str]:
'''simple docstring'''
... | 656 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils imp... | 656 |
'''simple docstring'''
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 im... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def __UpperCAmelCase ( __magic_name__ )-> str:
"""simple docstring"""
return "".join(sorted(__magic_name__ ) )
def __UpperCA... | 656 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A_ (unittest.TestCase ):
"""simple docstrin... | 656 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowerCamelCase : List[str] = {'''configuration_deit''': ['... | 656 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowerCamelCase : Any ... | 656 | 1 |
'''simple docstring'''
# Copyright 2021 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/l... | 656 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : int = {
'''microsoft/cvt-13''': '''https://huggingface.co/micr... | 656 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProce... | 656 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowerCamelCase : str = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> int:
"""simple docstring"""
return int(input_a == input_a == 0 )
def __UpperCAmelCase ( )-> None:
"""simple docstring"""
print("Truth Table... | 656 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
snake_case_ : Any = {
... | 656 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
Ad... | 656 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__lowerCamelCase : Dict = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINE... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ = 10**12 )-> int:
"""simple docstring"""
snake_case_ : Dict = 1
snake_case_ : str = 0
snake_case_ : Dict = 1
snake_case_ : Union[str, A... | 656 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(__magic_name__ ,__magic_name__ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 ... | 656 | 1 |
'''simple docstring'''
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
__lowerCamelCase : ... | 656 |
'''simple docstring'''
# Copyright 2021 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/l... | 656 | 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
f... | 656 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : str = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 a... | 656 | 1 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def __UpperCAmelCase ( )-> Dict:
"""simple docstring"""
snake_case_ : Optional[int] = HfArgumentParser(__magic_name__ )
snak... | 656 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 656 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
__lowerCamelCase : str = logging.get_logger(__name__)
class A_ (a_ ):
"""simple docstring"""
... | 656 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
__lowerCamelCase : ... | 656 | 1 |
'''simple docstring'''
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
... | 656 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from data... | 656 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A_ (a_ ):
"""simple docst... | 656 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokenize... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list[int]:
"""simple docstring"""
if num <= 0:
raise ValueError("Input must be a positive integer" )
snake_case_ : Union[str, Any] = [True] * (num + 1)
snake_... | 656 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b ,2 ... | 656 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils imp... | 656 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__=None ,**__magic_name__ )-> Optional[Any]:
"""simple docstring"""
snake_case_ : int = ... | 656 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCamelCase : Any = logging.get_logger(__name__)
__lowerCam... | 656 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrFor... | 656 | 1 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class A_ (tf.keras.layers.Layer ... | 656 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.ima... | 656 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
__lowerCamelCase : Optional[Any] = {'''configuration_beit'... | 656 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, n... | 656 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A_ (metaclass=a_ ):
"""simple docstring"""
a__ = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self :Any , *lowerCAmelCase... | 656 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, ... | 656 | 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_... | 656 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( __magic_name__ ,__magic_name__=() ,__magic_name__=... | 656 | 1 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class A_ :
"""simple docstring"""
... | 656 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Dict ) -> List[str]:
'''simple docstring'''
... | 656 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
re... | 656 |
'''simple docstring'''
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 im... | 656 | 1 |
'''simple docstring'''
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .uti... | 656 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A_ (unittest.TestCase ):
"""simple docstrin... | 656 | 1 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
__lowerCamelCase : int = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_at... | 656 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowerCamelCase : Any ... | 656 | 1 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[Any] = logging.get_logger(__name__)
__lowerCamelCase : Tuple = {
'''xlnet-base-cased''': '''https:... | 656 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : int = {
'''microsoft/cvt-13''': '''https://huggingface.co/micr... | 656 | 1 |
'''simple docstring'''
import math
def __UpperCAmelCase ( __magic_name__ = 100 )-> int:
"""simple docstring"""
snake_case_ : Union[str, Any] = sum(i * i for i in range(1 ,n + 1 ) )
snake_case_ : int = int(math.p... | 656 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowerCamelCase : str = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
... | 656 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokenize... | 656 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
snake_case_ : Any = {
... | 656 | 1 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
__lowerCamelCase : ... | 656 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__lowerCamelCase : Dict = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINE... | 656 | 1 |
'''simple docstring'''
import copy
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
from ..auto import CONFIG_MAPPING
__lower... | 656 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(__magic_name__ ,__magic_name__ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 ... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
__lowerCamelCase : Optional[Any] = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', ''... | 656 |
'''simple docstring'''
# Copyright 2021 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/l... | 656 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class A_ (a_ ):
"""simple docstring"""
def __init__( self :Optional[Any] ) -> List[Any]:
'''simple docstring'''
... | 656 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : str = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 a... | 656 | 1 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
__lowerCamelCase : Any ... | 656 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 656 | 1 |
'''simple docstring'''
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class A_ (a_ ):
"""simple docstring"""
a__ = CustomTokenizer
pass
| 656 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
__lowerCamelCase : ... | 656 | 1 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def __UpperCAmelCase ( __magic_name__="ro" ,__magic_name__="en" ,__magic_name__="wmt16" ,__magic_name__=None )-> None:
"""simple docstring"""
try:
import ... | 656 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from data... | 656 | 1 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class A_ :
"""simple docstring"""
def __init__( self :Optional[int] , lowerCAmelCase__ :List[Any] ) -> Optional[int]:
'''si... | 656 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokenize... | 656 | 1 |
'''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrin... | 656 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b ,2 ... | 656 | 1 |
'''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
__lowe... | 656 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__=None ,**__magic_name__ )-> Optional[Any]:
"""simple docstring"""
snake_case_ : int = ... | 656 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Dict = {
'''facebook/s2t-small-librispeech-asr''': (
... | 656 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrFor... | 656 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
__lowerCamelCase : Union[str, Any] = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''go... | 656 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.ima... | 656 | 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__)
__... | 656 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, n... | 656 | 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 : List[Any] = {... | 656 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, ... | 656 | 1 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early... | 656 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( __magic_name__ ,__magic_name__=() ,__magic_name__=... | 656 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 656 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Dict ) -> List[str]:
'''simple docstring'''
... | 656 | 1 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A_ (unittest.TestCase ):
"""simple docstrin... | 656 |
'''simple docstring'''
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 im... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> List[Any]:
"""simple docstring"""
snake_case_ : Optional[int] = [0 for i in range(r + 1 )]
# nc0 = 1
snake_case_ : Tuple = 1
for i... | 656 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A_ (unittest.TestCase ):
"""simple docstrin... | 656 | 1 |
'''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
__lowerCamelCase : Optional[int] = datasets.logging.get_logger(__name__)
__lowerCamelCase : Optional[Any] = '''\
@inproceedings{rei-EtAl:2020:WMT,
author ... | 656 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowerCamelCase : Any ... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> Optional[int]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__magic_name__ ,int(b / 2 ) ) * actual_power(__mag... | 656 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : int = {
'''microsoft/cvt-13''': '''https://huggingface.co/micr... | 656 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__lowerCamelCase : Any = {'''tokenization_byt5''': ['''ByT5Tokenizer''']}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
__lowerCam... | 656 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowerCamelCase : str = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class A_ :
"""simple docstring"""
def __init__( self :Union[str, Any] , lowerCAmelCase__ :int , lowerCAmelCase__ :int , lowerCAm... | 656 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
snake_case_ : Any = {
... | 656 | 1 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__lowerCamelCase : List[Any] = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Stat... | 656 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__lowerCamelCase : Dict = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINE... | 656 | 1 |
'''simple docstring'''
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 im... | 656 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(__magic_name__ ,__magic_name__ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 ... | 656 | 1 |
'''simple docstring'''
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
__lowerCamelCase : List[str] ... | 656 |
'''simple docstring'''
# Copyright 2021 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/l... | 656 | 1 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
__lowerCamelCas... | 656 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : str = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 a... | 656 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__lowerCamelCase : List[Any] = {
'''configurati... | 656 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 656 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_dev... | 656 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
__lowerCamelCase : ... | 656 | 1 |
'''simple docstring'''
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__lowerCamelCase : Dict = (
... | 656 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from data... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> None:
"""simple docstring"""
snake_case_ : List[Any] = len(__magic_name__ )
print("The following activities are selected:" )
# The first activ... | 656 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokenize... | 656 | 1 |
'''simple docstring'''
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_D... | 656 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b ,2 ... | 656 | 1 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set... | 656 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__=None ,**__magic_name__ )-> Optional[Any]:
"""simple docstring"""
snake_case_ : int = ... | 656 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : Dict = logging.get_lo... | 656 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrFor... | 656 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_comm... | 656 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.ima... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> int:
"""simple docstring"""
def count_of_possible_combinations(__magic_name__ ) -> int:
if target < 0:
return 0
if target == 0:
... | 656 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, n... | 656 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import... | 656 |
'''simple docstring'''
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, ... | 656 | 1 |
'''simple docstring'''
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTeste... | 656 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __UpperCAmelCase ( __magic_name__ ,__magic_name__=() ,__magic_name__=... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class A_ :
"""simple docstring"""
def __init__( self :str , lowerCAmelCase__ :list[tuple[float, float]] ) -> str:
... | 656 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Dict ) -> List[str]:
'''simple docstring'''
... | 656 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ ,__magic_name__ ,__magic_name__ )-> int:
"""simple docstring"""
if depth < 0:
raise ValueErro... | 656 |
'''simple docstring'''
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 im... | 656 | 1 |
'''simple docstring'''
__lowerCamelCase : dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609_344,
"knot": 1.852,
}
__lowerCamelCase : dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277_777_778,
"mph": 0.621_371_192,
... | 656 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class A_ (unittest.TestCase ):
"""simple docstrin... | 656 | 1 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class A_ (a_ ):
"""s... | 656 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__lowerCamelCase : Any ... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers" )
snake_case_ : str = st... | 656 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : int = {
'''microsoft/cvt-13''': '''https://huggingface.co/micr... | 656 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=a_ )
class A_ (a_ ):
"""simple docstring""... | 656 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__lowerCamelCase : str = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
... | 656 | 1 |
'''simple docstring'''
# 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
#
# ht... | 656 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
snake_case_ : Any = {
... | 656 | 1 |
'''simple docstring'''
__lowerCamelCase : dict[str, float] = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 1000000,
"gigajoule": 1000000000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 3600000,
"newtonmeter": 1.0,
"calorie... | 656 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__lowerCamelCase : Dict = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINE... | 656 | 1 |
'''simple docstring'''
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
... | 656 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ )-> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(__magic_name__ ,__magic_name__ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 ... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ = 100_0000 )-> int:
"""simple docstring"""
snake_case_ : Any = set(range(3 ,__magic_name__ ,2 ) )
primes.add(2 )
for p in range(3 ,__magic_name__ ,... | 656 |
'''simple docstring'''
# Copyright 2021 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/l... | 656 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> bool:
"""simple docstring"""
snake_case_ : List[Any] = len(__magic_name__ )
snake_case_ : List[str] = len(__magic_name__ )
snake_... | 656 |
'''simple docstring'''
from scipy.stats import spearmanr
import datasets
__lowerCamelCase : str = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 a... | 656 | 1 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ... | 656 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 656 | 1 |
'''simple docstring'''
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()
__lowerCamelCas... | 656 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# 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
__lowerCamelCase : ... | 656 | 1 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
d... | 656 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from data... | 656 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class A_ (a_ ):
"""simple docstring"""
a__ = '''MCTCTFeatureExtractor'''
a__ = '''AutoTokenizer'''
... | 656 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokenize... | 656 | 1 |
'''simple docstring'''
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
__lowerCamelCase : Any = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version... | 656 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> float:
"""simple docstring"""
return math.sqrt(sum(pow(a - b ,2 ... | 656 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@... | 656 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__=None ,**__magic_name__ )-> Optional[Any]:
"""simple docstring"""
snake_case_ : int = ... | 656 | 1 |
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