code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TF... | 256 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def __lowerCamelCase ( ) -> Any:
raise RuntimeError("""CUDA out of memory.""" )
c... | 265 | 0 |
import os
from pathlib import Path
def lowerCAmelCase ( )-> List[Any]:
from torch.utils.cpp_extension import load
lowerCAmelCase_ : Dict = Path(_lowercase ).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
lowerCAmelCase_ : List[str... | 262 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Optional[int] = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""processing_git... | 265 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@... | 133 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
f... | 265 | 0 |
'''simple docstring'''
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the int... | 234 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_... | 265 | 0 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class lowerCamelCase (unittest.TestCase ):
lowerCamelCase__ : List[str] = JukeboxTokenizer
lowerCamelCase__ : ... | 165 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a : List[Any] = """__DUMMY_TRANSFORMERS_USER__"""
a : Tuple = """Dummy User"""
a : Optional[Any] ... | 265 | 0 |
from itertools import count
def a ( snake_case__: List[Any] = 50 ):
'''simple docstring'''
lowercase_ = [1] * min_block_length
for n in count(_lowercase ):
fill_count_functions.append(1 )
for block_length in range(_lowercase ... | 30 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 265 | 0 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images,... | 347 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowercase ) -> Optional[Any]:
return getitem, k
def __lowerCamelCase ( _lowercase , _lowercase ) ... | 265 | 0 |
from bisect import bisect
from itertools import accumulate
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : Tuple , _lowerCamelCase : List[str] , _lowerCamelCase : str , _lowerCamelCase : Tuple) -> int:
'''simple docstring'''
__UpperC... | 232 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizer... | 265 | 0 |
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def a( A : List[str] , A : str , A : List[Any] , A : Dict ) -> Optional[int]:
"""simple docstring"""
a = ... | 227 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils imp... | 265 | 0 |
import heapq
import sys
import numpy as np
lowercase = tuple[int, int]
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self ) -> Union[str, Any]:
snake_case_ = []
snake_case_ = set()
def _UpperCamelCase... | 178 |
'''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/LICENSE-2.0
#... | 265 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json""",
}
class SCREAMING_SNAK... | 24 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stab... | 265 | 0 |
"""simple docstring"""
def lowercase ( a__ : List[Any] ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_UpperCamelCase = 1
_UpperCamelCase = 1
while repunit:
_UpperCamelCase = (10 * repunit + 1) % divisor
... | 256 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_model... | 265 | 0 |
_UpperCAmelCase : List[Any] =frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs""",
]
)
_UpperCAmelCase : Tup... | 262 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, requ... | 265 | 0 |
lowercase_ : Union[str, Any] = range(2, 20 + 1)
lowercase_ : Tuple = [10**k for k in range(ks[-1] + 1)]
lowercase_ : dict[int, dict[int, list[list[int]]]] = {}
def __SCREAMING_SNAKE_CASE ( snake_case_ , snake_case_ , snake_case_ , snake_case_ ):
'''simple do... | 133 |
'''simple docstring'''
from itertools import count
def __lowerCamelCase ( _lowercase = 5_0 ) -> int:
UpperCAmelCase : Any = [1] * min_block_length
for n in count(_lowercase ):
fill_count_functions.append(1 )
for block_length in... | 265 | 0 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if i... | 234 |
'''simple docstring'''
from __future__ import annotations
import math
class UpperCamelCase_ :
def __init__( self , A ) -> None:
UpperCAmelCase : Optional[int] = size
# approximate the overall size of segment tree with given value
UpperCAmelCase :... | 265 | 0 |
"""simple docstring"""
class lowerCamelCase :
def __init__( self : Optional[Any] , __UpperCAmelCase : Union[str, Any] , __UpperCAmelCase : Optional[int] , __UpperCAmelCase : List[str] ) -> str:
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE_... | 165 |
'''simple docstring'''
from PIL import Image
def __lowerCamelCase ( _lowercase , _lowercase ) -> Image:
def brightness(_lowercase ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 255.0:
raise ValueError("""level must b... | 265 | 0 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
# TODO Update this
__a = {
"""facebook/esm-1b""": """https://huggingface.co/facebook/esm-1b/resol... | 30 |
'''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_c... | 265 | 0 |
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Tuple = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
__SC... | 347 |
'''simple docstring'''
def __lowerCamelCase ( _lowercase , _lowercase ) -> int:
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(_lowercase , int(b / 2 ) ) * actual_power(_lowercase , int(b / 2 ) )
else:
retur... | 265 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin, SchedulerOutput
@dataclass
class lowerC... | 232 |
'''simple docstring'''
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a : Any = get_tests_dir("""fixt... | 265 | 0 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prepar... | 227 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultis... | 265 | 0 |
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 UpperCamelCase_ ( snake_case_ , ... | 178 |
'''simple docstring'''
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def __lowerCamelCase ( _lowe... | 265 | 0 |
import os
snake_case_ = {"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}
def lowerCamelCase__ ( snake_case_ : Optional[Any] ) -> int:
__snake_case = 0
__snake_case = 0
while ... | 24 |
'''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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils i... | 265 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.s... | 256 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def __lowerCamelCase ( ) -> Any:
raise RuntimeError("""CUDA out of memory.""" )
c... | 265 | 0 |
import numpy as np
def lowerCAmelCase ( lowerCAmelCase_ )-> np.array:
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod() | 262 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : Optional[int] = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""processing_git... | 265 | 0 |
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
lowercase_ : Union[str, Any] = logging.get_logger(__name__)
lowercase_ : Tuple = {
""... | 133 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
f... | 265 | 0 |
'''simple docstring'''
from math import pi
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 234 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_... | 265 | 0 |
"""simple docstring"""
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
A_ : int = """src/transformers"""
# This is to make ... | 165 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a : List[Any] = """__DUMMY_TRANSFORMERS_USER__"""
a : Tuple = """Dummy User"""
a : Optional[Any] ... | 265 | 0 |
def a ( snake_case__: List[str] , snake_case__: Optional[int] , snake_case__: Optional[Any] ):
'''simple docstring'''
if exponent == 1:
return base
if exponent % 2 == 0:
lowercase_ = _modexpt(_lowercase , exponent // ... | 30 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 265 | 0 |
"""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
__SCREAMING_SNAKE_CASE : List[str] = {1: (1, 1), 2: (2, 1), 3: (3,... | 347 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __lowerCamelCase ( _lowercase ) -> Optional[Any]:
return getitem, k
def __lowerCamelCase ( _lowercase , _lowercase ) ... | 265 | 0 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _SCREAMING_SNAKE_CASE ( *_lowerCamelCase : List[Any] , _lowerCamelCase : Tuple = None , _lowerCamelCase : Dict=True , _lowerCamelCase : Union[str, Any]=2) ->... | 232 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizer... | 265 | 0 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class _lowercase ( unittest.TestCase ):
"""simple docstring"""
def UpperCamelCase_ (self ):
"""simple docstring"""
debug_launcher(t... | 227 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils imp... | 265 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( a_ , a_ , a_=None):
# set ... | 178 |
'''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/LICENSE-2.0
#... | 265 | 0 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ):
A_ : str = (PNDMScheduler,)
A_ : Dict = (('num_inference_steps', 50),)
... | 24 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stab... | 265 | 0 |
"""simple docstring"""
def lowercase ( a__ : Tuple ) -> bool:
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''') )
def lowercase ( a__ : str ) -> bool:
_UpperCamelCase = credit_card_number
_Upp... | 256 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_model... | 265 | 0 |
from math import ceil, sqrt
def lowerCAmelCase ( lowerCAmelCase_ = 1_000_000 )-> int:
lowerCAmelCase_ : Optional[Any] = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
lowerCAmelCase_ : Optio... | 262 |
'''simple docstring'''
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, requ... | 265 | 0 |
import numpy
# List of input, output pairs
lowercase_ : str = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase_ : Any = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_50))
lowercase_ : Tuple = [2, 4, 1, 5]
lowercase_ : ... | 133 |
'''simple docstring'''
from itertools import count
def __lowerCamelCase ( _lowercase = 5_0 ) -> int:
UpperCAmelCase : Any = [1] * min_block_length
for n in count(_lowercase ):
fill_count_functions.append(1 )
for block_length in... | 265 | 0 |
'''simple docstring'''
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_UpperCAmelCase : List[str] = (boundary[1] - boundary[0]) / steps
_UpperCAmelCase : Optiona... | 234 |
'''simple docstring'''
from __future__ import annotations
import math
class UpperCamelCase_ :
def __init__( self , A ) -> None:
UpperCAmelCase : Optional[int] = size
# approximate the overall size of segment tree with given value
UpperCAmelCase :... | 265 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def A ( snake_case__ ):
'''simple docstring'''
if "cls_token" in name:
SCREAMING_SNAKE_C... | 165 |
'''simple docstring'''
from PIL import Image
def __lowerCamelCase ( _lowercase , _lowercase ) -> Image:
def brightness(_lowercase ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 255.0:
raise ValueError("""level must b... | 265 | 0 |
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__a = get_tests_dir('fixtures/spiece.model')
@require_se... | 30 |
'''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_c... | 265 | 0 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if not numbers:
return 0
if not isinstance(__UpperCamelCase , (list, tuple) ) or not all(
isinstance(__UpperCamelCase , __UpperCamelCase ) for number in numbers ):
rai... | 266 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowercase_ = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 266 | 1 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if any(not isinstance(__UpperCamelCase , __UpperCamelCase ) or x < 0 for x in sequence ):
raise TypeError('''Sequence must be list of non-negative integers''' )
for _ in range(len(__Upp... | 266 |
"""simple docstring"""
class snake_case :
'''simple docstring'''
def __init__( self : List[str], _lowerCamelCase : list[int] ):
'''simple docstring'''
__A = len(_lowerCamelCase )
__A = [0] * len_array
if len_array > 0:
__A = ar... | 266 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase_ = {
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Pix2StructConfig',
... | 266 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.convers... | 266 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'facebook/convnextv... | 266 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import ... | 266 | 1 |
"""simple docstring"""
lowercase_ = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com... | 266 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArgu... | 266 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_ = {
'configuration_deberta': ['DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'D... | 266 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 266 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : ArgumentParser ):
'''simple... | 266 |
"""simple docstring"""
import re
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A ... | 266 | 1 |
"""simple docstring"""
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
A_ : str = "M-CLIP"
def __init__( self : Optional[Any], _lowerCamelCase : str=10... | 266 |
"""simple docstring"""
from __future__ import annotations
class snake_case :
'''simple docstring'''
def __init__( self : int, _lowerCamelCase : List[Any]=None ):
'''simple docstring'''
__A = data
__A = None
def __repr__( self : Union[... | 266 | 1 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if num < 0:
return False
__A = num
__A = 0
while num > 0:
__A = rev_num * 1_0 + (num % 1_0)
num //= 1_0
return num_copy == rev_num
if __name__ == "__m... | 266 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, T... | 266 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if not postfix_notation:
return 0
__A = {'''+''', '''-''', '''*''', '''/'''}
__A = []
for token in postfix_n... | 266 |
"""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_torch... | 266 | 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_CHE... | 266 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowercase_ = logging.get_logger(__name__)
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def __init__( self : Optional... | 266 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class snake_case :
'''simple docstring'''
A_ : int
A_ : TreeNode | None = None
A_ : TreeNode | None = None
lowercase_... | 266 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 266 | 1 |
"""simple docstring"""
lowercase_ = [
(1000, 'M'),
(900, 'CM'),
(500, 'D'),
(400, 'CD'),
(100, 'C'),
(90, 'XC'),
(50, 'L'),
(40, 'XL'),
(10, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
def lowerCAmelCase ( __UpperCamelCase ):
... | 266 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class snake_case ( ctypes.Structure ):
'''simple docstring'''
A_ : List[str] = [("... | 266 | 1 |
"""simple docstring"""
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = '▁'
lowercas... | 266 |
"""simple docstring"""
import argparse
import struct
import unittest
class snake_case :
'''simple docstring'''
def __init__( self : Optional[int], _lowerCamelCase : bytes ):
'''simple docstring'''
__A = data
# Initialize hash values
__A = [
... | 266 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class snake_case ( _lowerCAmelCas... | 266 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklea... | 266 | 1 |
"""simple docstring"""
import numpy
# List of input, output pairs
lowercase_ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase_ = (((515, 22, 13), 555), ((61, 35, 49), 150))
lowercase_ = [2, 4, 1, 5... | 266 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia a... | 266 | 1 |
"""simple docstring"""
import torch
from torch import nn
class snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self : List[Any], _lowerCamelCase : Tuple, _lowerCamelCase : int, _lowerCamelCase : List[Any], _lowerCamelCase : ... | 266 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extracti... | 266 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, T... | 266 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A = current_set.copy()
for row_index, row in enumerate(__UpperCamelCase ):
__A = row[0]
for column_index, column in enumerate(__UpperCamelCase ):
if magnitude == 0:... | 266 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import Tensor... | 266 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if not postfix_notation:
return 0
__A = {'''+''', '''-''', '''*''', '''/'''}
__A = []
for token in postfix_n... | 266 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
... | 266 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
imp... | 266 | 1 |
"""simple docstring"""
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
lowercase_ = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/1... | 266 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase ( __UpperCamelCase = 1_0_0_0_0_0_0 , __UpperCamelCase = 1_0 ):
"""simple docstring"""
__A = defaultdict(__UpperCamelCase )
for outer_width in range(3 , ... | 266 | 1 |
"""simple docstring"""
from manim import *
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : List[Any] ):
'''simple docstring'''
__A = Rectangle(height=0.5, width=0.5 )
__A = Rectangle(h... | 266 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class snake_case :
'''simple docstring'''
def __init__( self : Optional[int], _lowerCamelCase : Optional[int]=2, _lowerCa... | 266 | 1 |
"""simple docstring"""
import os
def lowerCAmelCase ( ):
"""simple docstring"""
__A = os.path.join(os.path.dirname(__UpperCamelCase ) , '''num.txt''' )
with open(__UpperCamelCase ) as file_hand:
return str(sum(int(__UpperCamelCase ) for line in file_hand ) )[:1... | 266 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowercase_ = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 266 | 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_vi... | 266 |
"""simple docstring"""
class snake_case :
'''simple docstring'''
def __init__( self : List[str], _lowerCamelCase : list[int] ):
'''simple docstring'''
__A = len(_lowerCamelCase )
__A = [0] * len_array
if len_array > 0:
__A = ar... | 266 | 1 |
"""simple docstring"""
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowercase_ = 0b10_11_00_11_11_10_11_00_10_01_00_00_01... | 266 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.convers... | 266 | 1 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffuse... | 266 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import ... | 266 | 1 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
"""simple docstring"""
__A = BeautifulSoup(requests.get(__UpperCamelCase , params=__UpperCamelCase ).content , '''html.parse... | 266 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArgu... | 266 | 1 |
"""simple docstring"""
import unittest
from knapsack import greedy_knapsack as kp
class snake_case ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Any ):
'''simple docstring'''
__A = [10, 20, 30, 40, 50, 60]
__A ... | 266 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 266 | 1 |
"""simple docstring"""
import re
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A ... | 266 |
"""simple docstring"""
import re
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A ... | 266 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
... | 266 |
"""simple docstring"""
from __future__ import annotations
class snake_case :
'''simple docstring'''
def __init__( self : int, _lowerCamelCase : List[Any]=None ):
'''simple docstring'''
__A = data
__A = None
def __repr__( self : Union[... | 266 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class snake_case ( unittest.Test... | 266 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, T... | 266 | 1 |
"""simple docstring"""
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='''session''' )
def lowerCAmelCase ( ... | 266 |
"""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_torch... | 266 | 1 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_... | 266 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowercase_ = logging.get_logger(__name__)
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def __init__( self : Optional... | 266 | 1 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class snake_case ( ctypes.Structure ):
'''simple docstring'''
A_ : List[str] = [("... | 266 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 266 | 1 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperC... | 266 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class snake_case ( ctypes.Structure ):
'''simple docstring'''
A_ : List[str] = [("... | 266 | 1 |
"""simple docstring"""
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
... | 266 |
"""simple docstring"""
import argparse
import struct
import unittest
class snake_case :
'''simple docstring'''
def __init__( self : Optional[int], _lowerCamelCase : bytes ):
'''simple docstring'''
__A = data
# Initialize hash values
__A = [
... | 266 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTester... | 266 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklea... | 266 | 1 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if n_term == "":
return []
__A = []
for temp in range(int(__UpperCamelCase ) ):
series.append(f'1/{temp + 1}' if series else '''1''' )
return series
if __name__ == "__main__"... | 266 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia a... | 266 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_... | 266 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extracti... | 266 | 1 |
"""simple docstring"""
import warnings
warnings.warn(
'memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '
'`from accelerate import find_executable_batch_size` to avoid this warning.',
FutureWarning,
)
| 266 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A = current_set.copy()
for row_index, row in enumerate(__UpperCamelCase ):
__A = row[0]
for column_index, column in enumerate(__UpperCamelCase ):
if magnitude == 0:... | 266 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
lowercase_ = tuple[int, int]
class snake_case :
'''simple docstring'''
def __init__( self : Optional[Any], _lowerCamelCase : set[int], _lowerCamelCase : ... | 266 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
if not postfix_notation:
return 0
__A = {'''+''', '''-''', '''*''', '''/'''}
__A = []
for token in postfix_n... | 266 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbon... | 266 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
imp... | 266 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=_lowerCAmelCase ):
'''simple docstring'''
A_ : Union[str, Any] = ["speech"]
def __init__( self : Dict, *_lowerCamelCase : Any, **_lowerCamelCase... | 266 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase ( __UpperCamelCase = 1_0_0_0_0_0_0 , __UpperCamelCase = 1_0 ):
"""simple docstring"""
__A = defaultdict(__UpperCamelCase )
for outer_width in range(3 , ... | 266 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extracti... | 266 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class snake_case :
'''simple docstring'''
def __init__( self : Optional[int], _lowerCamelCase : Optional[int]=2, _lowerCa... | 266 | 1 |
"""simple docstring"""
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 266 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowercase_ = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 266 | 1 |
"""simple docstring"""
import enum
import shutil
import sys
lowercase_ , lowercase_ = shutil.get_terminal_size()
lowercase_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class snake_case ( enum.Enum ):
'''simple docstring'''
A_ : int ... | 266 |
"""simple docstring"""
class snake_case :
'''simple docstring'''
def __init__( self : List[str], _lowerCamelCase : list[int] ):
'''simple docstring'''
__A = len(_lowerCamelCase )
__A = [0] * len_array
if len_array > 0:
__A = ar... | 266 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
lowercase_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_pytorc... | 266 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.convers... | 266 | 1 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
A_ : Any = (UnCLIPScheduler,)
def _SCREAMING_SNAKE_CASE ( self : Any, ... | 266 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import ... | 266 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , ):
"""simple docstring"""
__A = len(__UpperCamelCase )
# If ro... | 266 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArgu... | 266 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaP... | 266 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 266 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def __init__( self : List[Any] ):
'''simple docstring'''
# test for the above condition
self.test()
def... | 266 |
"""simple docstring"""
import re
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
__A ... | 266 | 1 |
"""simple docstring"""
import sys
lowercase_ = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'6689664895044524... | 266 |
"""simple docstring"""
from __future__ import annotations
class snake_case :
'''simple docstring'''
def __init__( self : int, _lowerCamelCase : List[Any]=None ):
'''simple docstring'''
__A = data
__A = None
def __repr__( self : Union[... | 266 | 1 |
"""simple docstring"""
import torch
from diffusers import StableDiffusionPipeline
lowercase_ = 'path-to-your-trained-model'
lowercase_ = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
lowercase_ = 'A photo of sks dog in a bucket'
... | 266 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, T... | 266 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def lowerCAmelCase ( __UpperCamelCase )... | 266 |
"""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_torch... | 266 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowercase_ = logging.get_logger(__name__)
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def __init__( self : Optional... | 266 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowercase_ = logging.get_logger(__name__)
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def __init__( self : Optional... | 266 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase_ = {
'configuration_longt5': ['LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LongT5Config', 'LongT5OnnxConfig'],
}
try:
... | 266 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 266 | 1 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
"""simple docstring"""
assert column_title.isupper()
__A = 0
__A = len(__UpperCamelCase ) - 1
__A = 0
while index >= 0:
__A = (ord(column_title[index] ) - 6_4) * pow(2_6 , ... | 266 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class snake_case ( ctypes.Structure ):
'''simple docstring'''
A_ : List[str] = [("... | 266 | 1 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrai... | 266 |
"""simple docstring"""
import argparse
import struct
import unittest
class snake_case :
'''simple docstring'''
def __init__( self : Optional[int], _lowerCamelCase : bytes ):
'''simple docstring'''
__A = data
# Initialize hash values
__A = [
... | 266 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia a... | 266 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklea... | 266 | 1 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCAmelCase ... | 266 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia a... | 266 | 1 |
"""simple docstring"""
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowercase_ = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingua... | 266 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extracti... | 266 | 1 |
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