code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__A : int = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402
# This i... | 57 |
"""simple docstring"""
__A : Dict = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__A : L... | 57 | 1 |
"""simple docstring"""
from math import sqrt
def __SCREAMING_SNAKE_CASE ( lowercase__ = 1_000_000 ):
"""simple docstring"""
A = 0
A = 0
A = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 57 |
"""simple docstring"""
import numpy as np
import datasets
__A : Optional[int] = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 57 | 1 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch... | 57 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configurati... | 57 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__A : Union[str, Any] = get_logger(__name__)
class __UpperCamelCase ( enum.Enum ):
SCREAMING_SNAKE_CASE = "all_c... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( ):
"""simple docstring"""
A = []
A = 1
while len(lowercase__ ) < 1e6:
constant.append(str(lowercase__ ) )
i += 1
A = "".join(lowercase__ )
return (
int(cons... | 57 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase_... | 57 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
__A : List[str] = version.parse(version.parse(torch.__version__).base_version) < version.parse('1.11')
def __SCREAMING_S... | 57 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ = 600_851_475_143 ):
"""simple docstring"""
try:
A = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor,... | 57 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAv... | 57 | 1 |
"""simple docstring"""
from ... import PretrainedConfig
__A : Dict = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __UpperCamelCase ( _A ):
SCREAMING_SNAKE_CASE = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
... | 57 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 57 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 57 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 57 | 1 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils ... | 57 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonem... | 57 | 1 |
"""simple docstring"""
import operator as op
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
A = []
A = lambda lowercase__ , lowercase__ : int(x / y ) # noqa: E731 integer division operation
A = {
"^": op.pow,
... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : str = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise Option... | 57 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def __SCREAMING_SNAKE_CASE ( lowercase_... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str):
A , A = text, pattern
A , A = len(__SCREAMING_SNAKE_C... | 57 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : int = {
'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}
class ... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcess... | 57 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__A : Dict = logging.getLogg... | 57 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 57 | 1 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
__A : Tuple = 'src/transformers'
# Matches is_xxx_available()
__A : Dict = re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
__A : Dict = re.compile(R'^_impor... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Tuple , __SCREAMING_SNAKE_CASE : int = 0):
A = key
def SCREAMING_SNAKE_CASE__ (self : str , __SCREAMING_SNAKE_CASE : str , __SCREAMING_... | 57 | 1 |
"""simple docstring"""
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def __SCREAMING_SNAKE_CASE ( ... | 57 |
"""simple docstring"""
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase :
def __init__(self : Tuple):
A = [
[],
[],
[],
]
def SCREAMING_SNAKE_CA... | 57 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 57 |
"""simple docstring"""
__A : Optional[Any] = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-doc-builder>=0.3.0',
... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
if n == 1 or not isinstance(lowercase__ , lowercase__ ):
return 0
elif n == 2:
return 1
else:
A = [0, 1]
for i in range(2 ... | 57 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__=False ):
"""simple docstring"""
A = OmegaConf.load(lowercase__ )
if... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
A = False
while is_sorted is False: # Until all the indices are traversed keep looping
A = True
for i in range(0 , len(lowercase__ ) - 1 , ... | 57 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 57 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
if is_torch_available():
import torch
from transformers import AutoModelForImageClassification
if is_vision_availa... | 57 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Union[str, Any] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de... | 57 | 1 |
"""simple docstring"""
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __UpperCamelCase ( pl.LightningModule ):
def __init__(self : Dict , __SCREAMING_SNAKE_CASE... | 57 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for test... | 57 | 1 |
"""simple docstring"""
import sys
from collections import defaultdict
class __UpperCamelCase :
def __init__(self : Optional[Any]):
A = []
def SCREAMING_SNAKE_CASE__ (self : int , __SCREAMING_SNAKE_CASE : str):
return self.node_position[vertex]
de... | 57 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 57 | 1 |
"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # ... | 57 |
"""simple docstring"""
__A : Dict = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__A : L... | 57 | 1 |
"""simple docstring"""
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase ( _A ):
SCREAMING_SNAKE_CASE = (DDPMParallelScheduler,)
def SCREAMING_SNAKE_CASE__ (self : Union[str, Any] ... | 57 |
"""simple docstring"""
import numpy as np
import datasets
__A : Optional[int] = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 57 | 1 |
"""simple docstring"""
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__ , lowercase__ ):
"""simple docstring"""
A = np.array(lowercase__ )
if arr.shape[0] != arr.shape[1]:
raise ValueError("Th... | 57 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 57 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 57 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__A : Union[str, Any] = get_logger(__name__)
class __UpperCamelCase ( enum.Enum ):
SCREAMING_SNAKE_CASE = "all_c... | 57 | 1 |
"""simple docstring"""
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import... | 57 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase_... | 57 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A : Any = logging.get_logger(__name__)
__A : Optional[Any] = {
'distilbert-base-uncase... | 57 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ = 600_851_475_143 ):
"""simple docstring"""
try:
A = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 57 | 1 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Optional[int] = logging.get_logger(__name__)
__A : int = {
'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/config.json',
'xlnet-la... | 57 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAv... | 57 | 1 |
"""simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__ , lowercase__ = 1 , lowercase__ = 1 , lowercase__ = 1.0e4 , lowercase__ = False , lowercase_... | 57 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 57 | 1 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, 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 .tokeniza... | 57 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 57 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__A : Any = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 57 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonem... | 57 | 1 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
__A : Optional[Any] = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
__A : Dict = '\nArgs:\n pre... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : str = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise Option... | 57 | 1 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def __SCREAMING_SNAKE_CASE ( lowercase__ ... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str):
A , A = text, pattern
A , A = len(__SCREAMING_SNAKE_C... | 57 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils ... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcess... | 57 | 1 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __UpperCamelCase :
pass
| 57 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 57 | 1 |
"""simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __UpperCamelCase ( nn.Module ):
def __init__(self : Any , __SCREAMING_SNAKE_CASE : int = 1_6 , __SCREAMING_SNAK... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Tuple , __SCREAMING_SNAKE_CASE : int = 0):
A = key
def SCREAMING_SNAKE_CASE__ (self : str , __SCREAMING_SNAKE_CASE : str , __SCREAMING_... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
__A : List[str] = '2020.9.26'
__A : Any = 'xcodz-dot, cclaus, dhruvmanila'
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , l... | 57 |
"""simple docstring"""
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase :
def __init__(self : Tuple):
A = [
[],
[],
[],
]
def SCREAMING_SNAKE_CA... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
return "".join(chr(ord(lowercase__ ) - 32 ) if "a" <= char <= "z" else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 57 |
"""simple docstring"""
__A : Optional[Any] = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-doc-builder>=0.3.0',
... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
assert (
isinstance(lowercase__ , lowercase__ ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, your input {number_of_steps}"""
if n... | 57 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__=False ):
"""simple docstring"""
A = OmegaConf.load(lowercase__ )
if... | 57 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__A : Tuple = 'examples/'
__A : Dict = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"... | 57 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 57 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( _A ):
SCREAMING_SNAKE_CASE = ["image_processor", "tokenizer"]
SCREAMING_SNAKE_CASE = "CLIPImageProcesso... | 57 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Union[str, Any] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de... | 57 | 1 |
"""simple docstring"""
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
class __UpperCamelCase ( _A ):
S... | 57 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for test... | 57 | 1 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonem... | 57 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 57 | 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,
)
__A : str = {
'configuration_blenderbot_small': [
'BLENDER... | 57 |
"""simple docstring"""
__A : Dict = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__A : L... | 57 | 1 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
__A : Optional[Any] = re.compile(R'([A-Z]+)([A-Z][a-z])')
__A : Optional[int] = re.compile(R'([a-z\d])([A-Z])')
__A : Optional[Any] = re.compile(R'(?<!_)_(?!_)')
__A : Optional[Any] = re.compi... | 57 |
"""simple docstring"""
import numpy as np
import datasets
__A : Optional[int] = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 57 | 1 |
"""simple docstring"""
from manim import *
class __UpperCamelCase ( _A ):
def SCREAMING_SNAKE_CASE__ (self : Optional[int]):
A = Rectangle(height=0.5 , width=0.5)
A = Rectangle(height=0.4_6 , width=0.4_6).set_stroke(width=0)
A ... | 57 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 57 | 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,
)
__A : Tuple = {
'configuration_blenderbot': [
'BLENDERBOT_... | 57 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__A : Union[str, Any] = get_logger(__name__)
class __UpperCamelCase ( enum.Enum ):
SCREAMING_SNAKE_CASE = "all_c... | 57 | 1 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class __UpperCamelCase ( _A ):
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : Tu... | 57 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase_... | 57 | 1 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__A : str = argparse.ArgumentParser()
parser.add_argument('--dump_path', default=None, ty... | 57 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ = 600_851_475_143 ):
"""simple docstring"""
try:
A = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 57 | 1 |
"""simple docstring"""
import numpy as np
import datasets
__A : Optional[int] = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 57 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAv... | 57 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
__A : List[str] = {
'configuration_speech_to_text': ['SPEECH_... | 57 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 57 | 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 PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
fro... | 57 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 57 | 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
__A : Optional[int] = 'http://www... | 57 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonem... | 57 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
__A : int = {
'sample_size': 32,
'in_channels': 3,
'out_channels': 3,
'layers_per_block': 2,
'num_class_embed... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : str = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise Option... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
A = 0.00
A = 0
for resistor in resistors:
if resistor <= 0:
A = F"""Resistor at index {index} has a negative ... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str):
A , A = text, pattern
A , A = len(__SCREAMING_SNAKE_C... | 57 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcess... | 57 | 1 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 57 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 57 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
__A : Union[str, Any] = logging.getLogger(__name__)
@dataclass
class __UpperCamelCase ( ... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Tuple , __SCREAMING_SNAKE_CASE : int = 0):
A = key
def SCREAMING_SNAKE_CASE__ (self : str , __SCREAMING_SNAKE_CASE : str , __SCREAMING_... | 57 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 57 |
"""simple docstring"""
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase :
def __init__(self : Tuple):
A = [
[],
[],
[],
]
def SCREAMING_SNAKE_CA... | 57 | 1 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ... | 57 |
"""simple docstring"""
__A : Optional[Any] = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-doc-builder>=0.3.0',
... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ , ):
"""simple docstring"""
A = [redshift, radiation_density, matter_density, dark_energy]
if any(p < ... | 57 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__=False ):
"""simple docstring"""
A = OmegaConf.load(lowercase__ )
if... | 57 | 1 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 57 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 57 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( _A ):
SCREAMING_SNAKE_CASE = ["image_processor", "tokenizer"]
SCREAMING_SNAKE_CASE = "CLIPImageProcesso... | 57 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Union[str, Any] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de... | 57 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_... | 57 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for test... | 57 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAv... | 57 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
__A : Optional[Any] = [8, 5, 9, 7]
__A : Optional[int] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
__A : Any = [
[3, 2, 1, 4],
[0, 2... | 57 |
"""simple docstring"""
__A : Dict = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__A : L... | 57 | 1 |
"""simple docstring"""
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase :
def __init__(self : Tuple):
A = [
[],
[],
[],
]
def SCREAMING_SNAKE_CA... | 57 |
"""simple docstring"""
import numpy as np
import datasets
__A : Optional[int] = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 57 | 1 |
"""simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
class __UpperCamelCase ( _A ):
SCREAMING_SNAKE_... | 57 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 57 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 57 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__A : Union[str, Any] = get_logger(__name__)
class __UpperCamelCase ( enum.Enum ):
SCREAMING_SNAKE_CASE = "all_c... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import tempfile
import unittest
from transformers import CONFIG_MAPPING, AutoConfig, BertConfig, GPTaConfig, TaConfig, TapasConfig, is_tf_available
from transformers.testing_utils import (
DUMMY_UNKNOWN_IDENTIFIER,
SMALL_MODEL_IDENTIF... | 57 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase_... | 57 | 1 |
"""simple docstring"""
import os
def __SCREAMING_SNAKE_CASE ( ):
"""simple docstring"""
with open(os.path.dirname(lowercase__ ) + "/p022_names.txt" ) as file:
A = str(file.readlines()[0] )
A = names.replace("\"" , "" ).split("," )
... | 57 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ = 600_851_475_143 ):
"""simple docstring"""
try:
A = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 57 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=_A ):
SCREAMING_SNAKE_CASE = ["torch"]
def __init__(self : Optional[Any] , *__SCREAMING_SNAKE_CASE : str , **__SCREAMING_SNAKE_CASE : Any):
... | 57 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAv... | 57 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 57 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str):
A , A = text, pattern
A , A = len(__SCREAMING_SNAKE_C... | 57 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 57 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class ... | 57 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonem... | 57 | 1 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class __UpperCamelCase :
def __init__(self : Any , __SCREAMING_SNAKE_CASE : Optional[Any]):
A = str(id_)
A = None
A = None
A = []
A ... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : str = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise Option... | 57 | 1 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_att... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str):
A , A = text, pattern
A , A = len(__SCREAMING_SNAKE_C... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
A = sum(lowercase__ ) / len(lowercase__ ) # Calculate the average
ret... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcess... | 57 | 1 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
A = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __SCREAMING_SNAKE_CASE ... | 57 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 57 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Tuple , __SCREAMING_SNAKE_CASE : int = 0):
A = key
def SCREAMING_SNAKE_CASE__ (self : str , __SCREAMING_SNAKE_CASE : str , __SCREAMING_... | 57 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_uti... | 57 |
"""simple docstring"""
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase ( _A ):
pass
class __UpperCamelCase :
def __init__(self : Tuple):
A = [
[],
[],
[],
]
def SCREAMING_SNAKE_CA... | 57 | 1 |
"""simple docstring"""
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
__A : str = {
'tiny.en': 'https://openaipublic.azureedge.net/main/whisper/... | 57 |
"""simple docstring"""
__A : Optional[Any] = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-doc-builder>=0.3.0',
... | 57 | 1 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won... | 57 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase__=False ):
"""simple docstring"""
A = OmegaConf.load(lowercase__ )
if... | 57 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase ( _A ):
SCR... | 57 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 57 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is... | 57 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Union[str, Any] = {
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Tuple , __SCREAMING_SNAKE_CASE : int = 0):
A = key
def SCREAMING_SNAKE_CASE__ (self : str , __SCREAMING_SNAKE_CASE : str , __SCREAMING_... | 57 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for test... | 57 | 1 |
"""simple docstring"""
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def __SCREAMING_SNAKE_CASE ( lowercase__ = True , *lowercase__ , **lowercase__ ):
"""simple docstring"""
... | 57 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 57 | 1 |
"""simple docstring"""
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
fr... | 57 |
"""simple docstring"""
__A : Dict = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__A : L... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__A : Dict = TypeVar('KT')
__A : Tuple = TypeVar('VT')
class __UpperCamelCase ( Generic[KT, VT] ):
def __init__(self : Tuple , __SCRE... | 57 |
"""simple docstring"""
import numpy as np
import datasets
__A : Optional[int] = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.\... | 57 | 1 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 57 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 57 | 1 |
"""simple docstring"""
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classe... | 57 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__A : Union[str, Any] = get_logger(__name__)
class __UpperCamelCase ( enum.Enum ):
SCREAMING_SNAKE_CASE = "all_c... | 57 | 1 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 57 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def __SCREAMING_SNAKE_CASE ( lowercase__ , lowercase_... | 57 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached... | 57 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ = 600_851_475_143 ):
"""simple docstring"""
try:
A = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 57 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__A : Optional[int] = '\\n@inproceedings{snover-etal-2006-study,\n title = "A Study of Translation Edit Rate with Targeted Human Annotation",\n author = "Snover, Matthew and\n... | 57 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAv... | 57 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration... | 57 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 57 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__A : str = True
except (ImportError, ModuleNotFoundError):
__A : Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', quiet=True)
def __SCREAMING_SNAKE_... | 57 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as s... | 57 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : Tuple = {'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP', ... | 57 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonem... | 57 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__A : Union[str, Any] = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of... | 57 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : str = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise Option... | 57 | 1 |
"""simple docstring"""
from math import sqrt
def __SCREAMING_SNAKE_CASE ( lowercase__ ):
"""simple docstring"""
A = 0
for i in range(1 , int(sqrt(lowercase__ ) + 1 ) ):
if n % i == 0 and i != sqrt(lowercase__ ):
total += i + n... | 57 |
"""simple docstring"""
from __future__ import annotations
class __UpperCamelCase :
def __init__(self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str):
A , A = text, pattern
A , A = len(__SCREAMING_SNAKE_C... | 57 | 1 |
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