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'''
from functools import reduce
__lowerCamelCase : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12... | 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 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 |
'''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'''
__lowerCamelCase : Union[str, Any] = 256
# Modulus to hash a string
__lowerCamelCase : Optional[int] = 1000003
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> bool:
"""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'''
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 |
'''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 flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class A_ (nn.Module ):
"""simple docstring"""
... | 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'''
__lowerCamelCase : Any = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,... | 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
def __UpperCAmelCase ( __magic_name__ )-> bool:
"""simple docstring"""
if len(__magic_name__ ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
... | 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 collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
... | 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'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ ,__magic_name__ )-> bool:
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is not... | 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'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class ... | 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 OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Any = {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig... | 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 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_sentencepiec... | 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'''
from __future__ import annotations
from collections import namedtuple
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ )-> tuple:
"""simple docstring"""
snake_case_ : Optional[Any] = namedt... | 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'''
from __future__ import annotations
from random import choice
def __UpperCAmelCase ( __magic_name__ )-> Dict:
"""simple docstring"""
return choice(__magic_name__ )
def __UpperCAmelCase ( __magic_name__ ,__magic_name... | 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 argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class A_ (pl.LightningModule ):
"""simple docstring"""
def __ini... | 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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : str = {
... | 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 os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
__lowerCamelCase : str = 3
def __UpperCAmelCase ( __magic_name__ )-> int:
"""simple docstring"""
pri... | 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 Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 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 math
import tensorflow as tf
from packaging import version
def __UpperCAmelCase ( __magic_name__ )-> str:
"""simple docstring"""
snake_case_ : Any = tf.convert_to_tensor(__magic_name__ )
snake_case_ ... | 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 unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class A_ (unittest.TestCase ):
"""simple docstring"""
a__ = JukeboxTokenizer
a__ = {
... | 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 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 t... | 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 functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Any = logging.get_logger(__name__)
__lowerCamelCase : Any = {
'''microsoft/unispeech-... | 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 . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AN... | 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
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
__lowerCamelCase : Union[str, Any] = 0
__lowerCamelCase : List[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, ... | 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 argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( __magic_name__ ,__magic_... | 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'''
def __UpperCAmelCase ( __magic_name__ = 200_0000 )-> int:
"""simple docstring"""
snake_case_ : int = [0 for i in range(n + 1 )]
snake_case_ : List[Any] = 1
snake_case_ : Optional[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'''
from __future__ import annotations
__lowerCamelCase : List[Any] = [True] * 1000001
__lowerCamelCase : List[Any] = 2
while i * i <= 1000000:
if seive[i]:
for j in range(i * i, 1000001, i):
__lowerCamelCase : Tup... | 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 tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
__lowerCamelCase ... | 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 math
import random
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ = False )-> float:
"""simple docstring"""
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
... | 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 argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisual... | 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 inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import Con... | 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'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __UpperCAmelCase ( __magic_name__ = "isbn/0140328726" )-> dict:
"""simple docstring"""
snake_case_ : Optional[Any] = ... | 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 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 |
'''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 socket
def __UpperCAmelCase ( )-> Optional[int]:
"""simple docstring"""
snake_case_ : Dict = socket.socket(socket.AF_INET ,socket.SOCK_STREAM )
snake_case_ : Union[str, Any] = socket.gethostn... | 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 requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transfor... | 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 json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
__lowerCamelCase : int ... | 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 torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A_ (a_ ):
"""simple docstring"""
a__ = (DDIMParallelScheduler,)
a__ = (('''eta''', 0.0), (''... | 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 os
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
snake_case_ : Any = os.path.dirname(os.path.realpath(__magic_name__ ) )
snake_case_ : List[Any] = os.path.join(__magic_name__ ,"... | 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 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 |
'''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 os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
__lowerCamelCase : str = {
'''sample_size''': 32,
'''in_channels''': 3,
'''o... | 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 __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__lowerCamelCase : Dict = 10
def __UpperCAmelCase ( __magic_na... | 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 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 |
'''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 os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__lowerCa... | 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
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__lowerCamelCase : Optional[Any] = False
... | 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 : List[str] = logging.get_logger(__name__)
__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'''
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 |
'''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 gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
Bit... | 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 ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
__lowerCamelCase : List[str] = {
# See all MEGATRON_BERT models at https://hu... | 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'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
__lowerCamelCase : List[str] = {
"studio-ousia/luke-base": "https://huggingface.co/st... | 700 |
'''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 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> List[Any]:
"""simple docstring"""
return 1 if input_a == input_a else 0
def __UpperCAmelCase ( )-> Union[str, Any]:
"""simple docstring"""
asser... | 701 |
'''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 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokeniz... | 702 |
'''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 | 0 |
'''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is... | 703 |
'''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 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : Optional[Any] = {'''configuration_xl... | 704 |
'''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 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 705 |
'''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 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__lowerCamelCase )
class A_ (__lowerCamelCase ):
... | 706 |
'''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 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str:
"""simple docstring"""
snake_case_ : list[list[str]] = [[] for _ in range(__magic_name__ )]
snake_case_ : Dict = key - 1
if key <= ... | 707 |
'''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 | 0 |
'''simple docstring'''
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import... | 708 |
'''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 | 0 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
... | 709 |
'''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 | 0 |
'''simple docstring'''
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate(
'''stable diffusion controlnet''',
'''0.22.0''',
'''Importing `FlaxStableDiffusionControlNetPipeline` from di... | 710 |
'''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 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__lowerCamelCase : Optional[int] = {
'configuration_efficientformer... | 711 |
'''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 | 0 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...te... | 712 |
'''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 | 0 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
__lowerCamelCase : Optional[int] = logging.get_logger(__name__)
__lower... | 713 |
'''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 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase : List[Any] = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioC... | 714 |
'''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 | 0 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class A_ (__lowerCAmelCase ):
... | 715 |
'''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 | 0 |
'''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, InputExa... | 716 |
'''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 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
__lowerCamelCase : Optional[int] = logging.get_logger(__name__)
__lowerCamelCase : int = {
'''Intel/dpt-large''': '''ht... | 717 |
'''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 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowerCamelCase : str = logging.get_logger(__name__)
__lowerCamelCase : Optional[Any] = {
"speechbrain/m-ctc-t-large": "https://huggingface.co... | 718 |
'''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 | 0 |
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> int:
"""simple docstring"""
return int(input_a == input_a == 0 )
def __UpperCAmelCase ( )-> None:
"""simple docstring"""
print("Truth Table of NOR Gate:" )
print(... | 719 |
'''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 | 0 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.f... | 720 |
'''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 | 0 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str:
"""simple docstring"""
snake_case_ : Union[str, Any] = int(__UpperCamelCase )
assert noofclu... | 721 |
'''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 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ (unittest.Te... | 700 |
'''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 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu,... | 701 |
'''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 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
... | 702 |
'''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 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, ge... | 703 |
'''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 | 0 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class A_ (unittest.TestCase ):
"""simple doc... | 704 |
'''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 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase : Tuple = {'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}
try:
... | 705 |
'''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 | 0 |
'''simple docstring'''
from __future__ import annotations
import queue
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowerCAmelCase__ :Optional[Any] ) -> Any:
'''simple docstring'''
... | 706 |
'''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 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : Optional[Any] = {... | 707 |
'''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 | 0 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__lowerCamelCase : List[Any] ... | 708 |
'''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 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transform... | 709 |
'''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 | 0 |
'''simple docstring'''
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> Optional[int]:
""... | 710 |
'''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 | 0 |
'''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 ImageProcessingSavingT... | 711 |
'''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 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : int = logging.get_logger(__name__)
__lowerCamelCase : int = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/confi... | 712 |
'''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 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> str:
"""simple docstring"""
return "\n".join(
F'''{number} * {i} = {number * i}''' for i in range(1 ,number_of_terms + 1 ) )
if __name__ == "__main__"... | 713 |
'''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 | 0 |
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,
biogpt,
bit... | 714 |
'''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 | 0 |
def __UpperCAmelCase ( __magic_name__ )-> Union[str, Any]:
"""simple docstring"""
return sum(i for i in range(1 ,number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a Perfect numb... | 715 |
'''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 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class ... | 716 |
'''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 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
from collections.abc import Callable
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ ,__magic_name__ ,__magic_name__ = 100 ,)-> str:
"""simple docstring"""
snake_case_ : int = x_... | 717 |
'''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 | 0 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_util... | 718 |
'''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 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ )-> List[str]:
"""simple docstring"""
snake_case_ : Li... | 719 |
'''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 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 720 |
'''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 | 0 |
'''simple docstring'''
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __UpperCAmelCase ( __magic_name__ ,__magic_name__ = True ,__magic_name__ = math.inf ,__magic_name__ = -math.inf ,__magic_name__ = math.inf ,__magic_name__ = -math.... | 721 |
'''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 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__lowerCamelCase : int = False... | 700 |
'''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 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( )-> int:
"""simple docstring"""
return 1
def __UpperCAmelCase ( __magic_name__ )-> int:
"""simple docstring"""
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __Up... | 701 |
'''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 | 0 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
__lowerCamelCase : Any = parse(importlib.metadata.version('''torch'''))
def __UpperCAmelCase ( __magic_name__ ... | 702 |
'''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 | 0 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import ... | 703 |
'''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 | 0 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
__lowerCamelCase : int = logging.get_logger(__name__)
class A_ (_UpperCAmelCase ):
"""simple docstring"""
def __init__( self ... | 704 |
'''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 | 0 |
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTest... | 705 |
'''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 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_d... | 706 |
'''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 | 0 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from numpy import array
def __UpperCAmelCase ( __magic_name__ )-> list[list[float]]:
"""simple docstring"""
snake_case_ : Dict = Decimal
# Check if th... | 707 |
'''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 | 0 |
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