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 json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
... | 296 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_5_0_0_0_0_0 ) ->int:
A__ : defaultdict = defaultdict(UpperCAmelCase__ )
A__ : Any = 2
while 2... | 296 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
A_ = logging.get_logger(__name__) # pylint: disable=invalid-name
def _lo... | 296 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any], UpperCAmelCase__ : Optional[Any] ) ->List[str]:
for e in env_keys:
A__ : List[Any] = int(os.environ.get(UpperCAme... | 296 | 1 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import six # no... | 296 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 | 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_ = logging.get_logger(__name__)
A_ = {
'''andreasmadsen/efficient_mlm_m0.40''': ... | 296 |
"""simple docstring"""
from typing import Any, Dict, List, Union
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 ..image_utils import load_image
if is_torch_avai... | 296 | 1 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 296 |
"""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 ..auto import CONFIG_MAPPING
A_ = logging.get_logger(__name__)... | 296 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import gcd
def _lowerCAmelCase ( UpperCAmelCase__ : int, UpperCAmelCase__ : int = 2, UpperCAmelCase__ : int = 1, UpperCAmelCase__ : int = 3, ) ->int | None:
# A value less than 2 can c... | 296 |
"""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/LICENS... | 296 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
A_ = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig'''],
}
try:
if not is_torch_ava... | 296 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class ... | 296 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipelin... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
"""simple docstring"""
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def _lowerCAmelCase ( UpperCAmelCase__ : List[str] ) ->str:
A__ : str = {}
A__ : List[Any] = job["""star... | 296 |
"""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
A_ = logging.get_logge... | 296 | 1 |
"""simple docstring"""
import operator as op
A_ = '''scaler.pt'''
A_ = '''pytorch_model'''
A_ = '''random_states'''
A_ = '''optimizer'''
A_ = '''scheduler'''
A_ = '''pytorch_model.bin'''
A_ = '''pytorch_model.bin.index.json'''
A_ ... | 296 |
"""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.ut... | 296 | 1 |
"""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 datasets.table import table... | 296 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A_ ... | 296 | 1 |
"""simple docstring"""
import math
A_ = 10
A_ = 7
A_ = BALLS_PER_COLOUR * NUM_COLOURS
def _lowerCAmelCase ( UpperCAmelCase__ : int = 2_0 ) ->str:
A__ : List[Any] = math.comb(UpperCAmelCase__, UpperCAmelCase__ )
A... | 296 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
A_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase ):
def __init__( self : Union[str, Any] , ... | 296 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
A_ = object()
# For specifying empty leaf dict `{}`
A_ = object()
def _lowerCAm... | 296 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE ( U... | 296 |
"""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... | 296 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test impo... | 296 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
A_ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel... | 296 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json''',
# See all GPTNeoX mode... | 296 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
A_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase ):
def __init__( self : Optional[int] , snake_case : List[str]=None , ... | 296 | 1 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
A_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase ):
def __init__( self : Optional[int] , snake_case : List[str]=None , ... | 296 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from ... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_0_0_0_0_0_0 ) ->int:
A__ : List[str] = limit + 1
A__ : Tuple = [0] * limit
for first_term in range(1, UpperCAmelCase__ ):
for n in range(Uppe... | 296 |
"""simple docstring"""
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : List[str] ):
'''simple docstring'''
A__ : Optional[int] = (0, 0)
A__ : Dict = None
A__ ... | 296 | 1 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
A_ = logging.get_logger(__name__)
A_ = OrderedDict(
[
... | 296 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import... | 296 | 1 |
"""simple docstring"""
A_ = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
A_ = [... | 296 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _lowerCAmelCase ( UpperCAmelCase__ : Sequence[float], UpperCAmelCase__ : int, UpperCAmelCase__ :... | 296 | 1 |
"""simple docstring"""
import os
def _lowerCAmelCase ( UpperCAmelCase__ : Union[str, Any] ) ->Any:
A__ : Any = len(grid[0] )
A__ : Optional[Any] = len(UpperCAmelCase__ )
A__ : str = 0
A__ : L... | 296 |
"""simple docstring"""
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : Dict , snake_case : int ):
'''simple docstring'''
A__ : List[Any] = order
# a_{0} ... a_{k}
... | 296 | 1 |
"""simple docstring"""
# limitations under the License.
# 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .ut... | 296 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 296 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timeste... | 296 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_5_0_0_0_0_0 ) ->int:
A__ : defaultdict = defaultdict(UpperCAmelCase__ )
A__ : Any = 2
while 2... | 296 | 1 |
"""simple docstring"""
import os
A_ = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def _lowerCAmelCase ( UpperCAmelCase__ : str ) ->int:
A__ : Optional[int] = 0
A__ : Optional[Any]... | 296 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any], UpperCAmelCase__ : Optional[Any] ) ->List[str]:
for e in env_keys:
A__ : List[Any] = int(os.environ.get(UpperCAme... | 296 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
A_ = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNetC... | 296 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 | 1 |
"""simple docstring"""
from math import ceil, sqrt
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_0_0_0_0_0_0 ) ->int:
A__ : List[Any] = 0
for outer_width in range(3, (limit // 4) + 2 ):
if outer_width**2 > limit:
... | 296 |
"""simple docstring"""
from typing import Any, Dict, List, Union
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 ..image_utils import load_image
if is_torch_avai... | 296 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 |
"""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 ..auto import CONFIG_MAPPING
A_ = logging.get_logger(__name__)... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( ) ->List[Any]:
for n in range(1, 1_0_0_0_0_0_0 ):
yield n * (n + 1) // 2
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any] ) ->str:
A__ : Union[str, Any] = 1
A... | 296 |
"""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/LICENS... | 296 | 1 |
"""simple docstring"""
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def _lowerCAmelCase ( UpperCAmelCase__ : int, UpperCAmelCase__ : int, UpperCAmelC... | 296 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class ... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( ) ->int:
return [
a * b * (1_0_0_0 - a - b)
for a in range(1, 9_9_9 )
for b in range(UpperCAmelCase__, 9_9_9 )
if (a * a + b * b == (1_0_0_0 - a - b) ** 2)
][0]
if __name__ == "__main__"... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfi... | 296 |
"""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
A_ = logging.get_logge... | 296 | 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
A_ = logging.get_logge... | 296 |
"""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.ut... | 296 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_v... | 296 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A_ ... | 296 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cac... | 296 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 | 1 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_... | 296 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
A_ = object()
# For specifying empty leaf dict `{}`
A_ = object()
def _lowerCAm... | 296 | 1 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingface.co/snap-research/efficientformer-l... | 296 |
"""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... | 296 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mode... | 296 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
A_ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel... | 296 | 1 |
"""simple docstring"""
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CH... | 296 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
A_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase ):
def __init__( self : Optional[int] , snake_case : List[str]=None , ... | 296 | 1 |
"""simple docstring"""
from PIL import Image
def _lowerCAmelCase ( UpperCAmelCase__ : Image, UpperCAmelCase__ : float ) ->Image:
def brightness(UpperCAmelCase__ : int ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 2... | 296 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from ... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_0**1_2 ) ->int:
A__ : int = 1
A__ : Union[str, Any] = 0
A__ : List[str] = 1
A__ : Any = 1
while numera... | 296 |
"""simple docstring"""
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : List[str] ):
'''simple docstring'''
A__ : Optional[int] = (0, 0)
A__ : Dict = None
A__ ... | 296 | 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_ = logging.getLogger(__name__)
@dataclass
class __SCREAMING_SNAKE_CASE ( UpperCame... | 296 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import... | 296 | 1 |
"""simple docstring"""
from collections.abc import Callable
class __SCREAMING_SNAKE_CASE :
def __init__( self : List[Any] , snake_case : Callable | None = None ):
'''simple docstring'''
A__ : list = []
#... | 296 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _lowerCAmelCase ( UpperCAmelCase__ : Sequence[float], UpperCAmelCase__ : int, UpperCAmelCase__ :... | 296 | 1 |
"""simple docstring"""
import math
from collections.abc import Callable
def _lowerCAmelCase ( UpperCAmelCase__ : Callable[[float], float], UpperCAmelCase__ : float, UpperCAmelCase__ : float ) ->float:
A__ : float = xa
A__ : float ... | 296 |
"""simple docstring"""
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : Dict , snake_case : int ):
'''simple docstring'''
A__ : List[Any] = order
# a_{0} ... a_{k}
... | 296 | 1 |
"""simple docstring"""
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
A_ = TypeVar('''T''')
class __SCREAMING_SNAKE_CASE ( Generic[T] ... | 296 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 296 | 1 |
"""simple docstring"""
from math import factorial, radians
def _lowerCAmelCase ( UpperCAmelCase__ : float, UpperCAmelCase__ : int = 1_8, UpperCAmelCase__ : int = 1_0 ) ->float:
A__ : Optional[Any] = angle_in_degrees - ((angle_in_degrees // 3... | 296 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_5_0_0_0_0_0 ) ->int:
A__ : defaultdict = defaultdict(UpperCAmelCase__ )
A__ : Any = 2
while 2... | 296 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from... | 296 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any], UpperCAmelCase__ : Optional[Any] ) ->List[str]:
for e in env_keys:
A__ : List[Any] = int(os.environ.get(UpperCAme... | 296 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ =... | 296 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 | 1 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkp... | 296 |
"""simple docstring"""
from typing import Any, Dict, List, Union
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 ..image_utils import load_image
if is_torch_avai... | 296 | 1 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 |
"""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 ..auto import CONFIG_MAPPING
A_ = logging.get_logger(__name__)... | 296 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def _lowerCAmelCase ( UpperCAmelCase__ : ... | 296 |
"""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/LICENS... | 296 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}
class ... | 296 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class ... | 296 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_on... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
"""simple docstring"""
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
A_ = TypeVar('''KEY''')
A_ = TypeVar('''VAL''')
@dataclass(frozen=UpperCamelCase , slots=UpperCamelCase )
class __S... | 296 |
"""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
A_ = logging.get_logge... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : list[list] ) ->list[list]:
A__ : Tuple = current_set.copy()
for row_index, row in enumerate(UpperCAmelCase__ ):
A__ : Union[str, Any] = row[0]
f... | 296 |
"""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.ut... | 296 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( UpperCAmelCase__ : Dict, UpperCAmelCase__ : Union[str, Any], UpperCAmelCase__ : Optional[Any], UpperCAmelCase__ : List[Any] ) ->List[str]: # noqa: E741
while r - l > 1:
... | 296 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A_ ... | 296 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BigBirdPegasusConfig''',
... | 296 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 | 1 |
"""simple docstring"""
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, Aut... | 296 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
A_ = object()
# For specifying empty leaf dict `{}`
A_ = object()
def _lowerCAm... | 296 | 1 |
"""simple docstring"""
from torch import nn
def _lowerCAmelCase ( UpperCAmelCase__ : Optional[int] ) ->Any:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
retu... | 296 |
"""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... | 296 | 1 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
A_ = re.compile(r'''([A-Z]+)([A-Z][a-z])''')
A_ = re.compile(r'''([a-z\d])([A-Z])''')
A_ = re.compile(r'''(?<!_)_(?!_)''')
A_ = re.compile(r'''(_{2,})''')
A_ = r'''^\w+(\.\... | 296 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
A_ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel... | 296 | 1 |
"""simple docstring"""
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
A_ = HfApi()
A_ = {}
# fmt: off
A_ = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.1743, -3.7467,
1.2342, -2.2485, 0.4636, 0... | 296 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
A_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase ):
def __init__( self : Optional[int] , snake_case : List[str]=None , ... | 296 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _lowerCAmelCase ( ) ->str:
A__ : str = ArgumentParser("""Diffusers CLI tool""", usage="""diffusers-cli <command> [<args>]""" )
A__ : List[str] ... | 296 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from ... | 296 | 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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
... | 296 |
"""simple docstring"""
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : List[str] ):
'''simple docstring'''
A__ : Optional[int] = (0, 0)
A__ : Dict = None
A__ ... | 296 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=UpperCamelCase ):
snake_case_ = ['note_seq']
def __init__( self : Tuple , *snake_case : Union[str, Any] , **snake_case : ... | 296 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import... | 296 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( UpperCAmelCase__ : str, UpperCAmelCase__ : str ) ->bool:
A__ : List[str] = get_failure_array(UpperCAmelCase__ )
# 2) Step through text searching for pattern
... | 296 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _lowerCAmelCase ( UpperCAmelCase__ : Sequence[float], UpperCAmelCase__ : int, UpperCAmelCase__ :... | 296 | 1 |
"""simple docstring"""
A_ = 6_5521
def _lowerCAmelCase ( UpperCAmelCase__ : str ) ->int:
A__ : List[Any] = 1
A__ : str = 0
for plain_chr in plain_text:
A__ : int = (a + ord(UpperCA... | 296 |
"""simple docstring"""
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : Dict , snake_case : int ):
'''simple docstring'''
A__ : List[Any] = order
# a_{0} ... a_{k}
... | 296 | 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_ = logging.get_logger(__name__)
A_ = {
'''xlm-roberta-base''': '''https://huggin... | 296 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 296 | 1 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTra... | 296 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_5_0_0_0_0_0 ) ->int:
A__ : defaultdict = defaultdict(UpperCAmelCase__ )
A__ : Any = 2
while 2... | 296 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_to... | 296 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any], UpperCAmelCase__ : Optional[Any] ) ->List[str]:
for e in env_keys:
A__ : List[Any] = int(os.environ.get(UpperCAme... | 296 | 1 |
"""simple docstring"""
import os
import sys
A_ = os.path.join(os.path.dirname(__file__), '''src''')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceCl... | 296 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 | 1 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _lowerCAmelCase ( ) ->Dict:
with offline(OfflineSimulationMo... | 296 |
"""simple docstring"""
from typing import Any, Dict, List, Union
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 ..image_utils import load_image
if is_torch_avai... | 296 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt models at https://hugg... | 296 |
"""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 ..auto import CONFIG_MAPPING
A_ = logging.get_logger(__name__)... | 296 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 296 |
"""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/LICENS... | 296 | 1 |
"""simple docstring"""
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
A_ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6:... | 296 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class ... | 296 | 1 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __SCREAMING_S... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
"""simple docstring"""
import unittest
from transformers import DonutProcessor
A_ = '''naver-clova-ix/donut-base'''
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
def _UpperCamelCase ( self : Union[str, Any] ):
'''simple docstring''... | 296 |
"""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
A_ = logging.get_logge... | 296 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
A_ = datasets.utils.logging.get_logger(__name__)
@dataclass
class __SC... | 296 |
"""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.ut... | 296 | 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_ = {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 296 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A_ ... | 296 | 1 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.util... | 296 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_0 ) ->str:
if not isinstance(UpperCAmelCase__, UpperCAmelCase__ ) or n < 0:
raise ValueError("""Invalid input""" )
A__ : Union[str, Any] = 1_0**n
A__ : Opt... | 296 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
A_ = object()
# For specifying empty leaf dict `{}`
A_ = object()
def _lowerCAm... | 296 | 1 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _lowerCAmelCase ( UpperCAmelCase__ : int ) ->datetime:
A__ : List[str] = year % 1_9
A__ : Any = year % 4
A__ : str = year %... | 296 |
"""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... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int ) ->bool:
if not isinstance(UpperCAmelCase__, UpperCAmelCase__ ):
A__ : List[str] = f'Input value of [number={number}] must be an integer'
raise TypeError(UpperCAme... | 296 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
A_ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel... | 296 | 1 |
"""simple docstring"""
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
A_ = logging.get_logger(__name__)
A_ = {
'''post_extract_proj''': '''feature_proje... | 296 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
A_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( UpperCamelCase ):
def __init__( self : Optional[int] , snake_case : List[str]=None , ... | 296 | 1 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
A_ = object()
# For specifying empty leaf dict `{}`
A_ = object()
def _lowerCAm... | 296 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from ... | 296 | 1 |
"""simple docstring"""
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def _lowerCAmelCase (... | 296 |
"""simple docstring"""
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : List[str] ):
'''simple docstring'''
A__ : Optional[int] = (0, 0)
A__ : Dict = None
A__ ... | 296 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.ut... | 296 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import... | 296 | 1 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class ... | 296 |
"""simple docstring"""
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _lowerCAmelCase ( UpperCAmelCase__ : Sequence[float], UpperCAmelCase__ : int, UpperCAmelCase__ :... | 296 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class __SCREAMING_SNAKE_CASE ( UpperCame... | 296 |
"""simple docstring"""
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
def __init__( self : Dict , snake_case : int ):
'''simple docstring'''
A__ : List[Any] = order
# a_{0} ... a_{k}
... | 296 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
fr... | 296 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test... | 296 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 296 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_5_0_0_0_0_0 ) ->int:
A__ : defaultdict = defaultdict(UpperCAmelCase__ )
A__ : Any = 2
while 2... | 296 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTI... | 296 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any], UpperCAmelCase__ : Optional[Any] ) ->List[str]:
for e in env_keys:
A__ : List[Any] = int(os.environ.get(UpperCAme... | 296 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A_ = logging.get_logger(__name__)... | 296 |
"""simple docstring"""
import cva
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self : Union[str, Any] , snake_case : float , snake_case : int ):
'''simple docstring'''
if k in (0.04, 0.06):
... | 296 | 1 |
"""simple docstring"""
from math import asin, atan, cos, radians, sin, sqrt, tan
A_ = 6378137.0
A_ = 6356752.314245
A_ = 637_8137
def _lowerCAmelCase ( UpperCAmelCase__ : float, UpperCAmelCase__ : float, UpperCAmelCase__ : float, UpperC... | 296 |
"""simple docstring"""
from typing import Any, Dict, List, Union
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 ..image_utils import load_image
if is_torch_avai... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : list ) ->bool:
if not isinstance(UpperCAmelCase__, UpperCAmelCase__ ):
raise ValueError("""Input series is not valid, valid series - [2, 4, 6]""" )
if len(UpperCAmelCase__ ) == 0:
r... | 296 |
"""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 ..auto import CONFIG_MAPPING
A_ = logging.get_logger(__name__)... | 296 | 1 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
snake_case_ = JukeboxTokenizer
snake_case_ = {
'artis... | 296 |
"""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/LICENS... | 296 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A_ = logging.get_logger(__name__)
A_ = {
'''shi-labs/nat-mini-in1k-224''': ''... | 296 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class ... | 296 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_0_0_0_0_0_0 ) ->int:
A__ : int = set(range(3, UpperCAmelCase__, 2 ) )
primes.add(2 )
for p in range(3, UpperCAmelCase__, 2 ):
if p not in primes:
... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
"""simple docstring"""
import random
class __SCREAMING_SNAKE_CASE :
@staticmethod
def _UpperCamelCase ( snake_case : str ):
'''simple docstring'''
A__ : int = [ord(snake_case ) for i in text]
A__... | 296 |
"""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
A_ = logging.get_logge... | 296 | 1 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
A_ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel... | 296 |
"""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.ut... | 296 | 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_ = {
'''configuration_speech_to_text''': ['''SPEECH_TO... | 296 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A_ ... | 296 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''edbeeching/decision-transformer-gym-hopper-medium''': (
'''https://huggingface.co/edbeeching/decision-transformer-gym-hopper-... | 296 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
A_ = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 296 | 1 |
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