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"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}
... | 100 |
"""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
_a = logging.get_logger(__name__)
_a ... | 100 | 1 |
"""simple docstring"""
_a = """Tobias Carryer"""
from time import time
class _UpperCAmelCase:
def __init__( self , __a , __a , __a , __a=int(time())) -> int: # noqa: B008
'''simple docstring'''
_UpperCamelCase =... | 100 |
"""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 = {
"""facebook/xlm-rober... | 100 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smarta... | 100 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 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 = {
"""bert-base-uncased"... | 100 |
"""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_comm... | 100 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_a ... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class _UpperCAmelCase( lowerCamelCase ):
def __init__( self , __a="" , __a="train") -> Optional[int]:
'''simple docstring'''
... | 100 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 100 | 1 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def lowerCamelCase__ ( __snake_case = "AAPL" ) -> str:
"""simple docstring"""
_UpperCamelCase = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
_UpperCam... | 100 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead.""... | 100 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransfo... | 100 |
"""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 = {
"""bert-base-uncased"... | 100 | 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 Ac... | 100 |
"""simple docstring"""
import numpy
class _UpperCAmelCase:
def __init__( self , __a , __a) -> None:
'''simple docstring'''
_UpperCamelCase = input_array
# Random initial weights are assigned where first argument is the
... | 100 | 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_comm... | 100 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...s... | 100 |
"""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
fr... | 100 | 1 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_a = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONF... | 100 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ... | 100 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case ) -> list:
"""simple docstring"""
for i in range(len(__snake_case ) - 1, 0, -1 ):
_UpperCamelCase = False
for j in range(__snake_case, 0, -1 ... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""BridgeTower/bridgetower-base""": """https://huggingface.co/Bridge... | 100 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Optional[int]:
"""simple docstring"""
if len(__snake_case ) <= 1 or n <= 1:
return
insert_next(__snake_case, ... | 100 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_a = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
... | 100 |
"""simple docstring"""
class _UpperCAmelCase:
def __init__( self , __a , __a , __a) -> List[Any]:
'''simple docstring'''
_UpperCamelCase = name
_UpperCamelCase = value
_UpperCamelCase = weight
def __r... | 100 | 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 lowerCamelCase__ ( __snake_case = True, *__snake_case, **__snake_case ) -> str:
"""simple... | 100 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 4_00_00_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = [0, 1]
_UpperCamelCase = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
... | 100 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_a = namedtuple(
"""_TestComma... | 100 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 100 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case, __snake_case ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
_UpperCamelCase = s... | 100 | 1 |
"""simple docstring"""
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_a = """src/transformers"""
_a ... | 100 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.... | 100 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_avail... | 100 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase__ ( __snake_case ) -> None:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase ... | 100 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_a = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
... | 100 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
# See all BioGPT mo... | 100 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ... | 100 |
"""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
_a = logging.get_logger(__name__)
_a ... | 100 | 1 |
"""simple docstring"""
import json
import sys
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Union[str, Any]:
"""simple docstring"""
with open(__snake_case, encoding='''utf-8''' ) as f:
_UpperCamelCase = json.lo... | 100 |
"""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 = {
"""facebook/xlm-rober... | 100 | 1 |
"""simple docstring"""
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'''kwargs, expected''', [
({'''num_shards''': 0, '''max_num_jobs''': 1}, []),
({'''num_shards''': 10... | 100 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 1 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext... | 100 |
"""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_comm... | 100 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase( metaclass=lowerCamelCase ):
lowercase__ = ['keras_nlp']
def __init__( self , *__a , **__a) -> Tuple:
'''simple docstring'''
requires... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case, __snake_case ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
_UpperCamelCase = s... | 100 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 100 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a = logging.get_logger(__name__)
_a = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.j... | 100 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead.""... | 100 | 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/licens... | 100 |
"""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 = {
"""bert-base-uncased"... | 100 | 1 |
"""simple docstring"""
import warnings
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
_a = logging.get_logger(__name__)
... | 100 |
"""simple docstring"""
import numpy
class _UpperCAmelCase:
def __init__( self , __a , __a) -> None:
'''simple docstring'''
_UpperCamelCase = input_array
# Random initial weights are assigned where first argument is the
... | 100 | 1 |
"""simple docstring"""
from PIL import Image
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Image:
"""simple docstring"""
def brightness(__snake_case ) -> float:
return 1_28 + level + (c - 1_28)
if not -255.0 <= level ... | 100 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMi... | 100 |
"""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
fr... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 1_00_00_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = 1
_UpperCamelCase = 1
_UpperCamelCase = {1: 1}
for inputa in range(2, __snake_case ... | 100 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_a = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONF... | 100 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
res... | 100 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 100 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
_a = {
"""sample_size""": 32,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_p... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 100 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Optional[int]:
"""simple docstring"""
if len(__snake_case ) <= 1 or n <= 1:
return
insert_next(__snake_case, ... | 100 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a = logging.get_log... | 100 |
"""simple docstring"""
class _UpperCAmelCase:
def __init__( self , __a , __a , __a) -> List[Any]:
'''simple docstring'''
_UpperCamelCase = name
_UpperCamelCase = value
_UpperCamelCase = weight
def __r... | 100 | 1 |
"""simple docstring"""
_a = """0.18.2"""
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_vers... | 100 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 100 | 1 |
"""simple docstring"""
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _U... | 100 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_a = namedtuple(
"""_TestComma... | 100 | 1 |
"""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 ... | 100 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case, __snake_case ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
_UpperCamelCase = s... | 100 | 1 |
"""simple docstring"""
from sklearn.metrics import fa_score
import datasets
_a = """
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
"""
_a = """
Args:
pred... | 100 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.... | 100 | 1 |
"""simple docstring"""
# Copyright 2023 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/LI... | 100 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase__ ( __snake_case ) -> None:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase ... | 100 | 1 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def lowerCamelCase__ ( __snake_case="ro", __snake_case="en", __snake_case="wmt16", __snake_case=None ) -> None:
"""simple docstring"""
try:
impo... | 100 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
# See all BioGPT mo... | 100 | 1 |
"""simple docstring"""
import os
import re
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 logging
_a = logging.get_logger(__name__... | 100 |
"""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
_a = logging.get_logger(__name__)
_a ... | 100 | 1 |
"""simple docstring"""
from math import pow
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case, __snake_case, __snake_case, ) -> tuple[int, int]:
"""simple docstring"""
if current_sum == needed_sum:
# If the sum o... | 100 |
"""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 = {
"""facebook/xlm-rober... | 100 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_a = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Chin... | 100 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
i... | 100 |
"""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_comm... | 100 | 1 |
"""simple docstring"""
from manim import *
class _UpperCAmelCase( lowerCamelCase ):
def UpperCAmelCase ( self) -> Any:
'''simple docstring'''
_UpperCamelCase = Rectangle(height=0.5 , width=0.5)
_UpperCamelCase ... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.... | 100 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 100 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( __snake_case ) -> list[int]:
"""simple docstring"""
_UpperCamelCase = [True] * limit
_UpperCamelCase = False
_UpperCamelCase = Fal... | 100 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead.""... | 100 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
... | 100 |
"""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 = {
"""bert-base-uncased"... | 100 | 1 |
"""simple docstring"""
import torch
def lowerCamelCase__ ( ) -> Tuple:
"""simple docstring"""
if torch.cuda.is_available():
_UpperCamelCase = torch.cuda.device_count()
else:
_UpperCamelCase = 0
print(F''... | 100 |
"""simple docstring"""
import numpy
class _UpperCAmelCase:
def __init__( self , __a , __a) -> None:
'''simple docstring'''
_UpperCamelCase = input_array
# Random initial weights are assigned where first argument is the
... | 100 | 1 |
"""simple docstring"""
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_a = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH AH QH""",... | 100 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 | 1 |
"""simple docstring"""
from typing import Dict
from .base import GenericTensor, Pipeline
class _UpperCAmelCase( lowerCamelCase ):
def UpperCAmelCase ( self , __a=None , __a=None , __a=None , **__a) -> Tuple:
'''simple docstri... | 100 |
"""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
fr... | 100 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 100 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_a = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONF... | 100 | 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 ... | 100 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 100 | 1 |
"""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
fr... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase )
class _UpperCAmelCase( lowerCamelCase ):
low... | 100 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Optional[int]:
"""simple docstring"""
if len(__snake_case ) <= 1 or n <= 1:
return
insert_next(__snake_case, ... | 100 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,
... | 100 |
"""simple docstring"""
class _UpperCAmelCase:
def __init__( self , __a , __a , __a) -> List[Any]:
'''simple docstring'''
_UpperCamelCase = name
_UpperCamelCase = value
_UpperCamelCase = weight
def __r... | 100 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_availabl... | 100 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 100 | 1 |
"""simple docstring"""
_a = [0, 2, 4, 6, 8]
_a = [1, 3, 5, 7, 9]
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case, __snake_case ) -> int:
"""simple docstring"""
if remaining_length == 0:
... | 100 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_a = namedtuple(
"""_TestComma... | 100 | 1 |
"""simple docstring"""
from __future__ import annotations
_a = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
_a = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def lowerCamelCase__ ( __snake_case ) -> list[float]:
... | 100 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case, __snake_case ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
_UpperCamelCase = s... | 100 | 1 |
"""simple docstring"""
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case=10_24, __snake_case=10_24,... | 100 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.... | 100 | 1 |
"""simple docstring"""
import requests
_a = """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def lowerCamelCase__ ( __snake_case ) -> None:
"""simple docstring"""
_UpperCamelCase = requests.get(_NEWS_AP... | 100 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase__ ( __snake_case ) -> None:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase ... | 100 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""google/vivit-b-16x2-kinetics400""": (
"""https://huggingface.co/google/vivit-b-16x2-kinetics400/resolve/main... | 100 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
# See all BioGPT mo... | 100 | 1 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common im... | 100 |
"""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
_a = logging.get_logger(__name__)
_a ... | 100 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def lowerCamelCase__ ( __snake_case = 1_50_00_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = defaultdict(__snake_case )
_UpperCamelCase ... | 100 |
"""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 = {
"""facebook/xlm-rober... | 100 | 1 |
"""simple docstring"""
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _UpperCAmelCase( lowerCamelCase ):
lowercase__ = ['image_processor', 'tokenizer']
lowercase__ = 'AutoImageProcessor'
... | 100 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 1 |
"""simple docstring"""
import math
def lowerCamelCase__ ( __snake_case, __snake_case ) -> int:
"""simple docstring"""
_UpperCamelCase = len(__snake_case )
_UpperCamelCase = int(math.floor(math.sqrt(__snake_case ) ... | 100 |
"""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_comm... | 100 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from tra... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case, __snake_case, __snake_case ) -> np.ndarray:
"""simple docstring"""
... | 100 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case ) -> int:
"""simple docstring"""
def count_of_possible_combinations(__snake_case ) -> int:
if target < 0:
return 0
if targe... | 100 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead.""... | 100 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""tiiuae/falcon-40b""": """https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json""",
"""tiiuae/falcon-... | 100 |
"""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 = {
"""bert-base-uncased"... | 100 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Optional[int]:
"""simple docstring"""
if len(__snake_case ) <= 1 or n <= 1:
return
insert_next(__snake_case, ... | 100 |
"""simple docstring"""
import numpy
class _UpperCAmelCase:
def __init__( self , __a , __a) -> None:
'''simple docstring'''
_UpperCamelCase = input_array
# Random initial weights are assigned where first argument is the
... | 100 | 1 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuratio... | 100 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 | 1 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
def lowerCamelCase__ ( __snake_case, __snake_case ) -> bool:
"""simple docstring"""
return (
num != den and num % 10 == den // 10 and (num // 10) /... | 100 |
"""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
fr... | 100 | 1 |
"""simple docstring"""
_a = {
"""a""": """AAAAA""",
"""b""": """AAAAB""",
"""c""": """AAABA""",
"""d""": """AAABB""",
"""e""": """AABAA""",
"""f""": """AABAB""",
"""g""": """AABBA""",
"""h""": """AABBB""",
"""i""": """ABAAA""",
"""j""": """BBB... | 100 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_a = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONF... | 100 | 1 |
"""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... | 100 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 100 | 1 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorForma... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 10**9 ) -> int:
"""simple docstring"""
_UpperCamelCase = 1
_UpperCamelCase = 2
_UpperCamelCase = 0
_UpperCamelCase = 0
_UpperCamelCas... | 100 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Optional[int]:
"""simple docstring"""
if len(__snake_case ) <= 1 or n <= 1:
return
insert_next(__snake_case, ... | 100 | 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/licens... | 100 |
"""simple docstring"""
class _UpperCAmelCase:
def __init__( self , __a , __a , __a) -> List[Any]:
'''simple docstring'''
_UpperCamelCase = name
_UpperCamelCase = value
_UpperCamelCase = weight
def __r... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 1_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = set()
_UpperCamelCase = 0
_UpperCamelCase = n + 1 # maximum limit
for a in range(2, ... | 100 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 100 | 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 = {"""configuration_opt""": ["""OPT_PRETRAIN... | 100 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_a = namedtuple(
"""_TestComma... | 100 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_a = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONF... | 100 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case, __snake_case ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
_UpperCamelCase = s... | 100 | 1 |
"""simple docstring"""
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""vocab_file""": """vo... | 100 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.... | 100 | 1 |
"""simple docstring"""
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm... | 100 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase__ ( __snake_case ) -> None:
"""simple docstring"""
_UpperCamelCase , _UpperCamelCase ... | 100 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfi... | 100 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
"""microsoft/biogpt""": """https://huggingface.co/microsoft/biogpt/resolve/main/config.json""",
# See all BioGPT mo... | 100 | 1 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_a = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) <... | 100 |
"""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
_a = logging.get_logger(__name__)
_a ... | 100 | 1 |
"""simple docstring"""
from math import isqrt, loga
def lowerCamelCase__ ( __snake_case ) -> list[int]:
"""simple docstring"""
_UpperCamelCase = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
i... | 100 |
"""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 = {
"""facebook/xlm-rober... | 100 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case = 2_00_00_00 ) -> int:
"""simple docstring"""
_UpperCamelCase = [0 for i in range(n + 1 )]
_UpperCamelCase = 1
_UpperCamelCase = 1
for i in range(2... | 100 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_a = """\
@inproceedings{popovic-2015-chrf,
title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",
author = \"Popovi{\'c}, Maja\",
... | 100 |
"""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_comm... | 100 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 100 |
"""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/licens... | 100 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCAmelCase( metaclass=lowerCamelCase ):
lowercase__ = ['torch']
def __init__( self , *__a , **__a) -> int:
'''simple docstring'''
requires_backe... | 100 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 100 | 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
_a = logging.get_logger(__name__)
_a ... | 100 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` instead.""... | 100 | 1 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class _UpperCAmelCase( lowerCamelCase ):
lowercase__ = 'SpeechT5FeatureExtractor'
lowercase__ = 'SpeechT5Tokenizer'
def __init__( self , __a , __a) -> int:
... | 100 |
"""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 = {
"""bert-base-uncased"... | 100 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 100 |
"""simple docstring"""
import numpy
class _UpperCAmelCase:
def __init__( self , __a , __a) -> None:
'''simple docstring'''
_UpperCamelCase = input_array
# Random initial weights are assigned where first argument is the
... | 100 | 1 |
"""simple docstring"""
import numpy
class _UpperCAmelCase:
def __init__( self , __a , __a) -> None:
'''simple docstring'''
_UpperCamelCase = input_array
# Random initial weights are assigned where first argument is the
... | 100 |
"""simple docstring"""
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock... | 100 | 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()
... | 100 |
"""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
fr... | 100 | 1 |
"""simple docstring"""
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extra... | 100 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_a = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONF... | 100 | 1 |
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