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 |
|---|---|---|---|---|
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
__lowerCamelCase : Optional[int] = '''src/transformers'''
__lowerCamelCase :... | 18 | from collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self : int,_A : List[Any],_A : Optional[Any],_A : Optional[int],_A : int=None,_A : List[str]=None ):
"""simple docstring"""
... | 18 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
logging.set_... | 18 | def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
while b:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : int = b, a % b
return a
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : ... | 18 | 1 |
__lowerCamelCase : dict[tuple[int, int, int], int] = {}
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed... | 18 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available():... | 18 | import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : str , lowerCAmelCase : str , lowerCAmelCase : Path , lowe... | 18 | 1 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from... | 18 | import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available():... | 18 | 1 |
from __future__ import annotations
from collections.abc import Iterator
class a__ :
def __init__( self : int,_A : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = value
SCREAMING_SNAKE_CASE_ : Node | None ... | 18 | import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Tuple ... | 18 | 1 |
from math import isqrt
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase ) + 1 ) )
def _snake_case ( lowerCAmelCase : int = 1_0**6 ):
"""simple docstring"""
SCREA... | 18 | from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 | 1 |
def _snake_case ( lowerCAmelCase : int = 1_0_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[int] = n * (n + 1) * (2 * n + 1) / 6
SCREAMING_SNAKE_CASE_ : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__m... | 18 | def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = int(lowerCAmelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowerCAmelCase )
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Dict ... | 18 | 1 |
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
__lowerCamelCase : Optional[int] = logging.getLogger(__name__)
if is_torch_tpu_available(che... | 18 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | 1 |
import argparse
import os
import re
import packaging.version
__lowerCamelCase : str = '''examples/'''
__lowerCamelCase : Dict = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(R'''^__ve... | 18 | import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.util... | 18 | 1 |
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_available():
import torch
if... | 18 | from math import factorial, radians
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : int = 1_8 , lowerCAmelCase : int = 1_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 18 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 18 | from collections import defaultdict
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 1
SCREAMING_SNAKE_CASE_ : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase )
if r... | 18 | 1 |
from statistics import mean, stdev
def _snake_case ( lowerCAmelCase : list , lowerCAmelCase : int = 3 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = min(lowerCAmelCase )
SCREAMING_SNAKE_CASE_ : List[str] = max(lowerCAmelCase )
# normalize... | 18 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 18 | 1 |
import os
def _snake_case ( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = os.path.join(os.path.dirname(lowerCAmelCase ) , "num.txt" )
with open(lowerCAmelCase ) as file_hand:
return str(sum(int(lowerCAmelCase ) for line in file_hand ) )[:1_0]
if __name__ ==... | 18 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenizati... | 18 | 1 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class a__ ( unittest.TestCase ):
A = inspect.getfile(accelerate.test_... | 18 | import unittest
from transformers import SqueezeBertConfig, 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 import ModelTesterMixin, ids_tensor, ran... | 18 | 1 |
from __future__ import annotations
__lowerCamelCase : Tuple = '''Muhammad Umer Farooq'''
__lowerCamelCase : int = '''MIT'''
__lowerCamelCase : Union[str, Any] = '''1.0.0'''
__lowerCamelCase : List[Any] = '''Muhammad Umer Farooq'''
__lowerCamelCase : Optional[Any] =... | 18 | import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : Union[str, ... | 18 | 1 |
__lowerCamelCase : Union[str, Any] = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
10: '''a''',
11: '''b''',
12: '''c''',
13: '''d''',
14: '''e''',
15: '''f''',
}
de... | 18 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDConditi... | 18 | 1 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__lowerCamelCase : List[str] = re.compile(R'''\b(a|an|the)\b''', re.UNICODE)
__lowerCamelCase : Dict = None
def _snake_case ( ):
"""simple docstring"""
SCREAMIN... | 18 | from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils_ba... | 18 | 1 |
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class a__ ( A__ ):
def __init__( self : Dict,_A : List[Any],_A : Any ):
"""simple docst... | 18 | from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class a__ ( yaml.SafeLoader ):
def __UpperCamelCase ( self : str,_A : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_... | 18 | 1 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
DistilBert... | 18 | from __future__ import annotations
from math import pi, sqrt
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise ValueErro... | 18 | 1 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
__lowerCamelCase : List[str] = HfApi()
__lowerCamelCase : Union[str, Any] = {}
# fmt: off
__lowerCamelCase : Any = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433, -1.... | 18 | def _snake_case ( lowerCAmelCase : list ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = len(lowerCAmelCase )
for i in range(1 , lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ : int = collection[i]
SCREAMING_SNAKE_CASE_ : Any = 0
SCRE... | 18 | 1 |
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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResampling... | 18 | from collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self : int,_A : List[Any],_A : Optional[Any],_A : Optional[int],_A : int=None,_A : List[str]=None ):
"""simple docstring"""
... | 18 | 1 |
from __future__ import annotations
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : Optional[int] , lowerCAmelCase : Tuple , lowerCAmelCase : Tuple ): # noqa: E741
"""simple docstring"""
while r - l > 1:
SCREAMING_SNAKE_CASE_ : str = ... | 18 | def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
while b:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : int = b, a % b
return a
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : ... | 18 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | 1 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('''Googling.....''')
__lowerCamelCase : Optional[Any] = '''https://www.google.com/search?q=''' + ''' '''.join(sys.argv[1:])
__lowerCamelCase : Optional[... | 18 | import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : str , lowerCAmelCase : str , lowerCAmelCase : Path , lowe... | 18 | 1 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class a__ ( unittest.TestCase ):
@property
def... | 18 | import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available():... | 18 | 1 |
def _snake_case ( lowerCAmelCase : int = 1_0_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = 0
SCREAMING_SNAKE_CASE_ : Tuple = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of... | 18 | import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Tuple ... | 18 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils_ba... | 18 | from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 | 1 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from transformers.testing_... | 18 | def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = int(lowerCAmelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowerCAmelCase )
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Dict ... | 18 | 1 |
import math
import unittest
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
assert isinstance(lowerCAmelCase , lowerCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
return True
elif nu... | 18 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | 1 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( lowerCAmelCas... | 18 | import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.util... | 18 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.dummy... | 18 | from math import factorial, radians
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : int = 1_8 , lowerCAmelCase : int = 1_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 18 | 1 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class a__ ( A__ ):
A = (DPMSolverSinglestepSchedul... | 18 | from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | 1 |
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"files" , [
["full:README.md", "dataset_infos.json"],
["empty:README.md", "dataset_infos.json"],
["dataset_info... | 18 | from collections import defaultdict
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 1
SCREAMING_SNAKE_CASE_ : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase )
if r... | 18 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a__ ( A__ ):
A = ['image_processor', 'tokenizer']
A = 'ChineseCLIPImageProcessor'
A = ('BertTokenizer', 'BertTokenizerFast... | 18 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 18 | 1 |
from __future__ import annotations
import math
__lowerCamelCase : Tuple = '''2020.9.26'''
__lowerCamelCase : Any = '''xcodz-dot, cclaus, dhruvmanila'''
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float , lowerCAmelCase : float , lowerCAme... | 18 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenizati... | 18 | 1 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class a__ ( A__ ):
def __UpperCamelCase ( self : List[Any] ):
"""simple docstring"""
return [
{"col_1": 3, "col_2": "a"},... | 18 | import unittest
from transformers import SqueezeBertConfig, 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 import ModelTesterMixin, ids_tensor, ran... | 18 | 1 |
def _snake_case ( lowerCAmelCase : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = len(lowerCAmelCase )
while cur > 1:
# Find the maximum number in arr
SCREAMING_SNAKE_CASE_ : str = arr.index(max(arr[0:cur] ) )
# Reverse ... | 18 | import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : Union[str, ... | 18 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__lowerCamelCase : Union[str, Any] = log... | 18 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDConditi... | 18 | 1 |
from __future__ import annotations
def _snake_case ( lowerCAmelCase : list[list[int]] ):
"""simple docstring"""
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1 , len(lowerCAmelCase ) ):
matrix[i][0] ... | 18 | from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils_ba... | 18 | 1 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.util... | 18 | from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class a__ ( yaml.SafeLoader ):
def __UpperCamelCase ( self : str,_A : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_... | 18 | 1 |
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,
)
__lowerCamelCase : List[Any] = {
'''configuration_xlm_roberta'... | 18 | from __future__ import annotations
from math import pi, sqrt
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise ValueErro... | 18 | 1 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransformer, ... | 18 | def _snake_case ( lowerCAmelCase : list ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = len(lowerCAmelCase )
for i in range(1 , lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ : int = collection[i]
SCREAMING_SNAKE_CASE_ : Any = 0
SCRE... | 18 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFlip,
... | 18 | from collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self : int,_A : List[Any],_A : Optional[Any],_A : Optional[int],_A : int=None,_A : List[str]=None ):
"""simple docstring"""
... | 18 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureExtractionM... | 18 | def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
while b:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : int = b, a % b
return a
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : ... | 18 | 1 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, NewType, Optional... | 18 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | 1 |
from collections import defaultdict
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 1
SCREAMING_SNAKE_CASE_ : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase )
if r... | 18 | import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : str , lowerCAmelCase : str , lowerCAmelCase : Path , lowe... | 18 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available():... | 18 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load... | 18 | import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Tuple ... | 18 | 1 |
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : str = " " ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = []
SCREAMING_SNAKE_CASE_ : List[str] = 0
for index, char in enumerate(lowerCAmelCase ):
if char == separator:
... | 18 | from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 | 1 |
def _snake_case ( lowerCAmelCase : list ):
"""simple docstring"""
def merge(lowerCAmelCase : list , lowerCAmelCase : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yiel... | 18 | def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = int(lowerCAmelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowerCAmelCase )
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Dict ... | 18 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_d... | 18 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | 1 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_p... | 18 | import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.util... | 18 | 1 |
import random
class a__ :
@staticmethod
def __UpperCamelCase ( _A : str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = [ord(_A ) for i in text]
SCREAMING_SNAKE_CASE_ : Optional[Any] = []
SCREA... | 18 | from math import factorial, radians
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : int = 1_8 , lowerCAmelCase : int = 1_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 18 | 1 |
from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | 1 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_token... | 18 | from collections import defaultdict
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 1
SCREAMING_SNAKE_CASE_ : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase )
if r... | 18 | 1 |
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 TokenizerTesterMixin
__lowerCame... | 18 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 18 | 1 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
__lowerCamelCase : int = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'''
''' Distillation... | 18 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenizati... | 18 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
__lowerCamelCase : Tuple = {
'''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}
try:
i... | 18 | import unittest
from transformers import SqueezeBertConfig, 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 import ModelTesterMixin, ids_tensor, ran... | 18 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : List[Any] = {'''vocab_file''': ... | 18 | import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : Union[str, ... | 18 | 1 |
def _snake_case ( lowerCAmelCase : list ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = len(lowerCAmelCase )
for i in range(1 , lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ : int = collection[i]
SCREAMING_SNAKE_CASE_ : Any = 0
SCRE... | 18 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDConditi... | 18 | 1 |
__lowerCamelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(lowerCAmelCase ) )
def _snake_case ( ):
"""simple docstring"""
... | 18 | from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils_ba... | 18 | 1 |
from __future__ import annotations
__lowerCamelCase : Any = '''#'''
class a__ :
def __init__( self : Optional[int] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : dict = {}
def __UpperCamelCase ( self : ... | 18 | from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class a__ ( yaml.SafeLoader ):
def __UpperCamelCase ( self : str,_A : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_... | 18 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
@requ... | 18 | from __future__ import annotations
from math import pi, sqrt
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise ValueErro... | 18 | 1 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
__lowerCamelCase : Dict = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deformable_detr/cuda/ms_deform_im2col_... | 18 | def _snake_case ( lowerCAmelCase : list ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = len(lowerCAmelCase )
for i in range(1 , lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ : int = collection[i]
SCREAMING_SNAKE_CASE_ : Any = 0
SCRE... | 18 | 1 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
__lowerCamelCase : Dict = logging.get_logger(__name__)
class a__ ( A__ ):
def __init__( self : Optional[Any],*_A : List[Any],**_A : int ):
... | 18 | from collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self : int,_A : List[Any],_A : Optional[Any],_A : Optional[int],_A : int=None,_A : List[str]=None ):
"""simple docstring"""
... | 18 | 1 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : Union[str, ... | 18 | def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
while b:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : int = b, a % b
return a
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : ... | 18 | 1 |
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _snake_case ( lowerCAmelCase : Tuple , lowerCAmelCase : Any , lowerCAmelCase : int , lowerCAmelCase : Any ):
"""simple docstring"""
SCREAMING_SN... | 18 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | 1 |
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_video_inputs
if is_torch_available():
import torch
if... | 18 | import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : str , lowerCAmelCase : str , lowerCAmelCase : Path , lowe... | 18 | 1 |
import math
__lowerCamelCase : List[str] = 10
__lowerCamelCase : str = 7
__lowerCamelCase : Any = BALLS_PER_COLOUR * NUM_COLOURS
def _snake_case ( lowerCAmelCase : int = 2_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = math.... | 18 | import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available():... | 18 | 1 |
from math import factorial
class a__ :
def __init__( self : List[str],_A : Tuple,_A : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = real
if isinstance(_A,_A ):
SCREAMING_SNAKE_... | 18 | import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Tuple ... | 18 | 1 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_early_s... | 18 | from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
__lowerCamelCase : Tuple = {... | 18 | def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = int(lowerCAmelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowerCAmelCase )
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Dict ... | 18 | 1 |
from math import factorial, radians
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : int = 1_8 , lowerCAmelCase : int = 1_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 18 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | 1 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _snake_case ( ):
"""simple docstring"""
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dir... | 18 | import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.util... | 18 | 1 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, logging
from .benchmark_... | 18 | from math import factorial, radians
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : int = 1_8 , lowerCAmelCase : int = 1_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 18 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_bird import Big... | 18 | from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | 1 |
def _snake_case ( lowerCAmelCase : int = 3 , lowerCAmelCase : int = 7 , lowerCAmelCase : int = 1_0_0_0_0_0_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = 0
SCREAMING_SNAKE_CASE_ : List[str] = 1
for current_denominator... | 18 | from collections import defaultdict
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = 1
SCREAMING_SNAKE_CASE_ : Tuple = True
for v in tree[start]:
if v not in visited:
ret += dfs(lowerCAmelCase )
if r... | 18 | 1 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import shard... | 18 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 18 | 1 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configuration_u... | 18 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokenizati... | 18 | 1 |
def _snake_case ( lowerCAmelCase : Tuple ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = 1
SCREAMING_SNAKE_CASE_ : Optional[Any] = 2
while i * i <= n:
SCREAMING_SNAKE_CASE_ : Optional[Any] = 0
while n % i == 0:
n //= i
... | 18 | import unittest
from transformers import SqueezeBertConfig, 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 import ModelTesterMixin, ids_tensor, ran... | 18 | 1 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : str , **lowerCAmelCase : Union[str, Any] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[Any] = Aut... | 18 | import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : Union[str, ... | 18 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
__lowerCamelCase ... | 18 | import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDConditi... | 18 | 1 |
from __future__ import annotations
from math import pi, sqrt
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise ValueErro... | 18 | from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils_ba... | 18 | 1 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
return getitem, k
def _snake_case ( lowerCAmelCase : Optional[Any] , lowerCAmelCase ... | 18 | from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class a__ ( yaml.SafeLoader ):
def __UpperCamelCase ( self : str,_A : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_... | 18 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : List[Any] = logging.get_logger(__name__)
__lowerCamelCase : Dict = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json''',
}
... | 18 | from __future__ import annotations
from math import pi, sqrt
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
raise ValueErro... | 18 | 1 |
class a__ :
def __init__( self : List[str],_A : list ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Union[str, Any] = set_counts
SCREAMING_SNAKE_CASE_ : List[Any] = max(_A )
SCREAMING_SNAKE_CASE_ : str ... | 18 | def _snake_case ( lowerCAmelCase : list ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Dict = len(lowerCAmelCase )
for i in range(1 , lowerCAmelCase ):
SCREAMING_SNAKE_CASE_ : int = collection[i]
SCREAMING_SNAKE_CASE_ : Any = 0
SCRE... | 18 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=A__ )
class a__ ( A__ ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSON seri... | 18 | from collections.abc import Sequence
from queue import Queue
class a__ :
def __init__( self : int,_A : List[Any],_A : Optional[Any],_A : Optional[int],_A : int=None,_A : List[str]=None ):
"""simple docstring"""
... | 18 | 1 |
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
__lowerCamelCase : Optional[Any] = get_tests_dir('''fixtures/spi... | 18 | def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
while b:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : int = b, a % b
return a
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : ... | 18 | 1 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
__lowerC... | 18 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCamelCase : Dict = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}
try... | 18 | 1 |
import math
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : float ):
"""simple docstring"""
if initial_intensity < 0:
raise ValueError("The value of intensity cannot be negative" )
# handling of negative values of initial intensity
if angle < 0 or angle > 3... | 18 | import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : str , lowerCAmelCase : str , lowerCAmelCase : Path , lowe... | 18 | 1 |
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelCase : Optional[int] = logging.get_logger(__name__)
def _snake_case ( lowerCAmelCase : str ):
"""simple ... | 18 | import unittest
import numpy as np
from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
expand_dims,
flatten_dict,
is_flax_available,
is_tf_available,
is_torch_available,
reshape,
squeeze,
transpose,
)
if is_flax_available():... | 18 | 1 |
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
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_configurati... | 18 | import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : List[str] = logging.get_logger(__name__)
__lowerCamelCase : Tuple ... | 18 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer
__low... | 18 | from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, ra... | 18 | 1 |
import re
def _snake_case ( lowerCAmelCase : str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = re.compile(
R"^(?:0|94|\+94|0{2}94)" R"7(0|1|2|4|5|6|7|8)" R"(-| |)" R"\d{7}$" )
return bool(re.search(lowerCAmelCase , lowerCAmelCase ) )
if __name__ ... | 18 | def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Tuple = int(lowerCAmelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowerCAmelCase )
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : Dict ... | 18 | 1 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common im... | 18 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : Union[str, Any] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''ChineseCLIPConfig''... | 18 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUnCLI... | 18 | import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformers.util... | 18 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDConditi... | 18 | from math import factorial, radians
def _snake_case ( lowerCAmelCase : float , lowerCAmelCase : int = 1_8 , lowerCAmelCase : int = 1_0 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 18 | 1 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
__lowerCamelCase : List[Any] = logging.get_logger(__name__)
class a__ ( A__ ):
A = CLIPConfig
... | 18 | from functools import lru_cache
@lru_cache
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest
doct... | 18 | 1 |
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