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 warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''xlnet-base-cased''': '''https://huggingface.co/xlnet-base-cased/resolve/main/config.json''',
'''xlnet-... | 272 | '''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | 1 |
'''simple docstring'''
from collections import defaultdict
class a__:
'''simple docstring'''
def __init__( self , __lowerCAmelCase , __lowerCAmelCase):
"""simple docstring"""
lowerCAmelCase = total # total no of tasks (N)
# DP table will hav... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowercase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNe... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: Tuple ) -> Tuple:
'''simple docstring'''
lowerCAmelCase = [0] * len(_A )
lowerCAmelCase = []
lowerCAmelCase = [1] * len(_A )
for values in graph.values():
for i in values:
indegree[i] += 1
for i in ra... | 272 | '''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 272 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 272 | '''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 272 | 1 |
'''simple docstring'''
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 ):
... | 272 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import ... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: str ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(len(_A ) )]
# initialize interval's left pointer and right pointer
lowerCAmelCase , lowerCAmelCase = 0, 0
for i in range(1 , le... | 272 | '''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class a__( enum.En... | 272 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class a__( lowerCAmelCase__ , unittest.TestCase ):
'''simple docstring'''
... | 272 | '''simple docstring'''
def snake_case__ ( _A: str ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(len(_A ) )]
# initialize interval's left pointer and right pointer
lowerCAmelCase , lowerCAmelCase = 0, 0
for i in range(1 , le... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: int ) -> int:
'''simple docstring'''
if n == 1 or not isinstance(_A , _A ):
return 0
elif n == 2:
return 1
else:
lowerCAmelCase = [0, 1]
for i in range(2 , n + 1 ):
sequence.append(sequence[i - 1]... | 272 | '''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : str = '''EncodecFeatureExtractor'''
Upper... | 272 | 1 |
'''simple docstring'''
class a__:
'''simple docstring'''
def __init__( self):
"""simple docstring"""
lowerCAmelCase = {}
def a_ ( self):
"""simple docstring"""
print(self.vertex)
for i in self.vertex:
print(__lowerCAmelCase... | 272 | '''simple docstring'''
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 ):
... | 272 | 1 |
'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''vocab_file''': '''vocab.json''... | 272 | '''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : int = ['''image_processor''', '''tokenizer''']
UpperCAme... | 272 | '''simple docstring'''
import os
import string
import sys
__lowercase = 1 << 8
__lowercase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 272 | 1 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , __lowerCAmelCase="" , __lowerCAmelCase="train"):
"""simple docstring""... | 272 | '''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 272 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class a__:
'''simple docstring'''
UpperCAmelCase_ : ... | 272 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowercase = logging.get_logger(__name__)
__lowercase = '''T5Config'''
class a__( lowerCAmelCas... | 272 | 1 |
'''simple docstring'''
# Copyright (c) 2021-, NVIDIA CORPORATION. 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
... | 272 | '''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_py... | 272 | 1 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json''',
}
class a__... | 272 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_co... | 272 | 1 |
'''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_tf, ... | 272 | '''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
__lowercase = logging.get_logger(__name__)
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , *__... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: int = 2000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(n + 1 )]
lowerCAmelCase = 1
lowerCAmelCase = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
f... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''Ins... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple docstring'''
while a != 0:
lowerCAmelCase , lowerCAmelCase = b % a, a
return b
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple do... | 272 | '''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
f... | 272 | 1 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | '''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 272 | 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_py... | 272 | '''simple docstring'''
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple docstring'''
while a != 0:
lowerCAmelCase , lowerCAmelCase = b % a, a
return b
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple do... | 272 | 1 |
'''simple docstring'''
from collections import namedtuple
__lowercase = namedtuple('''from_to''', '''from_ to''')
__lowercase = {
'''cubicmeter''': from_to(1, 1),
'''litre''': from_to(0.001, 1_0_0_0),
'''kilolitre''': from_to(1, 1),
'''gallon''': from_to(0.00_454, 264.172),
... | 272 | '''simple docstring'''
import math
import flax.linen as nn
import jax.numpy as jnp
def snake_case__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , )... | 272 | 1 |
'''simple docstring'''
__lowercase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowercase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
__lowercase = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
5: '''Friday''',
6: '''Sat... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}
try:
if not is_to... | 272 | 1 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
__lowercase = logging.get_logger(... | 272 | '''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: list ) -> list:
'''simple docstring'''
lowerCAmelCase = len(_A )
for _ in range(_A ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
if arr[i + 1] < arr[i]:
lowerCAmelCase , lowerCAmelCase = ... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowercase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNe... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: int ) -> list[int]:
'''simple docstring'''
if length <= 0 or not isinstance(_A , _A ):
raise ValueError("""Length must be a positive integer.""" )
return [n * (2 * n - 1) for n in range(_A )]
if __name__ == "__main__":
prin... | 272 | '''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 272 | 1 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
__lowercase = False
__lowercase = True
__lowercase = False
if __name__ == "__main__":
__lowercase ... | 272 | '''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 272 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffusion... | 272 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import ... | 272 | 1 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class a__:
'''simple docstring'''
def __init__( self , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ... | 272 | '''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class a__( enum.En... | 272 | 1 |
'''simple docstring'''
import functools
def snake_case__ ( _A: list[int] , _A: list[int] ) -> int:
'''simple docstring'''
if not isinstance(_A , _A ) or not all(isinstance(_A , _A ) for day in days ):
raise ValueError("""The parameter days should be a lis... | 272 | '''simple docstring'''
def snake_case__ ( _A: str ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(len(_A ) )]
# initialize interval's left pointer and right pointer
lowerCAmelCase , lowerCAmelCase = 0, 0
for i in range(1 , le... | 272 | 1 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def snake_case__ ( _A: int = 1000000 , _A: int = 10 ) -> int:
'''simple docstring'''
lowerCAmelCase = defaultdict(_A )
for outer_width in range(3 , (t_limit // 4) + 2 )... | 272 | '''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : str = '''EncodecFeatureExtractor'''
Upper... | 272 | 1 |
'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowercase = logging.get_logger(__name__)
__lowercase = '''T5Config'''
class a__( lowerCAmelCas... | 272 | '''simple docstring'''
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 ):
... | 272 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
__lowercase = logging.get_logger(__name__)
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , *__... | 272 | '''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: int = 1000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 3
lowerCAmelCase = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __name... | 272 | '''simple docstring'''
import os
import string
import sys
__lowercase = 1 << 8
__lowercase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 272 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase = {
'''configuration_roc_bert''': ['''ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RoCBertConfig'''],
'''tokenizatio... | 272 | '''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 272 | 1 |
'''simple docstring'''
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class a__:
'''simple docstring'''
def __init__( self):
"""simple docstring"""
lowerCAmelCase = """"""
lowerCAmelCase = """"""
lowerCAme... | 272 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowercase = logging.get_logger(__name__)
__lowercase = '''T5Config'''
class a__( lowerCAmelCas... | 272 | 1 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('''Googling.....''')
__lowercase = '''https://www.google.com/search?q=''' + ''' '''.join(sys.argv[1:])
__lowercase ... | 272 | '''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_py... | 272 | 1 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , __lowerCAmelCase ,... | 272 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_co... | 272 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGE... | 272 | '''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
__lowercase = logging.get_logger(__name__)
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , *__... | 272 | 1 |
'''simple docstring'''
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
__lowercase = logging.get_logger(__name__)
class a__( lowerCAmelCase__ ):
'''simple docstring'... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''Ins... | 272 | 1 |
'''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... | 272 | '''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
f... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTester... | 272 | '''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 272 | 1 |
'''simple docstring'''
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_atten... | 272 | '''simple docstring'''
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple docstring'''
while a != 0:
lowerCAmelCase , lowerCAmelCase = b % a, a
return b
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple do... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...tes... | 272 | '''simple docstring'''
import math
import flax.linen as nn
import jax.numpy as jnp
def snake_case__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , )... | 272 | 1 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}
try:
if not is_to... | 272 | 1 |
'''simple docstring'''
import os
import pytest
from attr import dataclass
__lowercase = '''us-east-1''' # defaults region
@dataclass
class a__:
'''simple docstring'''
UpperCAmelCase_ : str
UpperCAmelCase_ : Optional[Any] = '''arn:aws:iam::558105141721:... | 272 | '''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import ... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowercase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNe... | 272 | 1 |
'''simple docstring'''
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state im... | 272 | '''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 272 | 1 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependenc... | 272 | '''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 272 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFe... | 272 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import ... | 272 | 1 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusion... | 272 | '''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class a__( enum.En... | 272 | 1 |
'''simple docstring'''
import qiskit
def snake_case__ ( _A: int , _A: int ) -> qiskit.result.counts.Counts:
'''simple docstring'''
lowerCAmelCase = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
lowerCAmelCase ... | 272 | '''simple docstring'''
def snake_case__ ( _A: str ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(len(_A ) )]
# initialize interval's left pointer and right pointer
lowerCAmelCase , lowerCAmelCase = 0, 0
for i in range(1 , le... | 272 | 1 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
f... | 272 | '''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : str = '''EncodecFeatureExtractor'''
Upper... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( _A: int ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [True] * limit
lowerCAmelCase = False
lowerCAmelCase = False
lowerCAmelCase = True
for i in range(3 ... | 272 | '''simple docstring'''
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 ):
... | 272 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def snake_case__ ( _A: Optional[int] , _A: Union[str, Any] , _A: Dict , _A: Optional[Any] ) -> List[str]:
'''simple docst... | 272 | '''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from... | 272 | '''simple docstring'''
import os
import string
import sys
__lowercase = 1 << 8
__lowercase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 272 | 1 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class a__( lowerCAmelCase__ , lowerCAmelCase__ ):
'''simple docstring'''
@... | 272 | '''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 272 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_o... | 272 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowercase = logging.get_logger(__name__)
__lowercase = '''T5Config'''
class a__( lowerCAmelCas... | 272 | 1 |
'''simple docstring'''
from math import pi
def snake_case__ ( _A: int , _A: int ) -> float:
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(9_0, 1_0))
| 272 | '''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_py... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def snake_case__ ( _A: int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even num... | 272 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_co... | 272 | 1 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
__lowercase = '''
import os
'''
__lowercase = '''
def foo():
import os
return False
'''
__lowercase = '''
def foo():
def bar():
if True:
import... | 272 | '''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
__lowercase = logging.get_logger(__name__)
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , *__... | 272 | 1 |
'''simple docstring'''
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_at... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''Ins... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( _A: list , _A: int ) -> Dict:
'''simple docstring'''
if len(_A ) <= 1 or n <= 1:
return
insert_next(_A , n - 1 )
rec_insertion_sort(_A , n - 1 )
def snake_case__ ... | 272 | '''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
f... | 272 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
... | 272 | '''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 272 | 1 |
'''simple docstring'''
class a__:
'''simple docstring'''
def __init__( self , __lowerCAmelCase , __lowerCAmelCase):
"""simple docstring"""
lowerCAmelCase = name
lowerCAmelCase = val
def __str__( self):
"""simple docstring"""... | 272 | '''simple docstring'''
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple docstring'''
while a != 0:
lowerCAmelCase , lowerCAmelCase = b % a, a
return b
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple do... | 272 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
... | 272 | '''simple docstring'''
import math
import flax.linen as nn
import jax.numpy as jnp
def snake_case__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , )... | 272 | 1 |
'''simple docstring'''
import numpy as np
from PIL import Image
def snake_case__ ( _A: np.ndarray , _A: int , _A: int ) -> np.ndarray:
'''simple docstring'''
lowerCAmelCase = np.array(_A )
if arr.shape[0] != arr.shape[1]:
raise ValueError("""The in... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}
try:
if not is_to... | 272 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__lowercase = logging.getLogger(__name__)
def snake_case__ ( ) -> int:
'''simple docstring'''
lowerCAmelCase = argparse.Arg... | 272 | '''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowercase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNe... | 272 | 1 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowercase = datasets.load_iris()
__lowercase = np.array(data['''data'''])
__lowercase = np.array(data['''target'''])
__lowerc... | 272 | '''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 272 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''facebook/s2t-wav2vec2-large-en-de''': (
'''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/co... | 272 | '''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 272 | 1 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
__lowercase = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evalu... | 272 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import ... | 272 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_imag... | 272 | '''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class a__( enum.En... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( _A: list , _A: int , _A: int , _A: int ) -> list:
'''simple docstring'''
lowerCAmelCase = []
lowerCAmelCase , lowerCAmelCase = input_list[low:mid], ... | 272 | '''simple docstring'''
def snake_case__ ( _A: str ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(len(_A ) )]
# initialize interval's left pointer and right pointer
lowerCAmelCase , lowerCAmelCase = 0, 0
for i in range(1 , le... | 272 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 272 | '''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : str = '''EncodecFeatureExtractor'''
Upper... | 272 | 1 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentP... | 272 | '''simple docstring'''
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 ):
... | 272 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfig... | 272 | '''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | 1 |
'''simple docstring'''
import math
__lowercase = 1_0
__lowercase = 7
__lowercase = BALLS_PER_COLOUR * NUM_COLOURS
def snake_case__ ( _A: int = 20 ) -> str:
'''simple docstring'''
lowerCAmelCase = math.comb(_A , _A )
lowerCAmelCase ... | 272 | '''simple docstring'''
import os
import string
import sys
__lowercase = 1 << 8
__lowercase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 272 | 1 |
'''simple docstring'''
from __future__ import annotations
def snake_case__ ( _A: list[int] , _A: int ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = len(_A ) - 1
while i < j:
if nums[i] + nums[j] == target:
return [... | 272 | '''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 272 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
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_configuration_common import Conf... | 272 | '''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowercase = logging.get_logger(__name__)
__lowercase = '''T5Config'''
class a__( lowerCAmelCas... | 272 | 1 |
'''simple docstring'''
import collections
import os
import re
from pathlib import Path
__lowercase = '''src/transformers'''
# Matches is_xxx_available()
__lowercase = re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
__lowercase = re.compile(R... | 272 | '''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_py... | 272 | 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
from de... | 272 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_co... | 272 | 1 |
'''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | '''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
__lowercase = logging.get_logger(__name__)
class a__( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , *__... | 272 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''Ins... | 272 | 1 |
'''simple docstring'''
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_ut... | 272 | '''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
f... | 272 | 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.activations import gelu_new, gelu_python, get_activation
@require_torch
class a__( unittest.Te... | 272 | '''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_prop... | 272 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_s... | 272 | '''simple docstring'''
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple docstring'''
while a != 0:
lowerCAmelCase , lowerCAmelCase = b % a, a
return b
def snake_case__ ( _A: int , _A: int ) -> int:
'''simple do... | 272 | 1 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def snake_case__ ( _A: List[str] ) -> Any:
'''simple docstring'''
lowerCAmelCase = {}
lowerCAmelCase = job["""started_at"""]
lowerCAmelCase ... | 272 | '''simple docstring'''
import math
import flax.linen as nn
import jax.numpy as jnp
def snake_case__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , )... | 272 | 1 |
'''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
f... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}
try:
if not is_to... | 272 | 1 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import to... | 272 | '''simple docstring'''
from math import sqrt
def snake_case__ ( _A: int = 1000000 ) -> int:
'''simple docstring'''
lowerCAmelCase = 0
lowerCAmelCase = 0
lowerCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides ... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: Dict , _A: Union[str, Any] , _A: Dict , _A: List[str] , _A: Optional[int] , _A: Dict ) -> List[str]:
'''simple docstring'''
if index == r:
for j in range(_A ):
print(data[j] ... | 272 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowercase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNe... | 272 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy ... | 272 | '''simple docstring'''
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch... | 272 | 1 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
__lowercase = logging.get_logger(__name__)
class a... | 272 | '''simple docstring'''
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 272 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowercase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ResNe... | 272 | '''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import ... | 272 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__lowercase = {'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAva... | 272 | '''simple docstring'''
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class a__( enum.En... | 272 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowercase = {
'''configuration_nezha''': ['''NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''NezhaConfig'''],
}
try:
if not is_to... | 272 | '''simple docstring'''
def snake_case__ ( _A: str ) -> list[int]:
'''simple docstring'''
lowerCAmelCase = [0 for i in range(len(_A ) )]
# initialize interval's left pointer and right pointer
lowerCAmelCase , lowerCAmelCase = 0, 0
for i in range(1 , le... | 272 | 1 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def snake_case__ ( _A: Dict ) -> Optional[Any]:
'''simple docstring'''
low... | 272 | '''simple docstring'''
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class a__( lowerCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase_ : str = '''EncodecFeatureExtractor'''
Upper... | 272 | 1 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 272 | '''simple docstring'''
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 ):
... | 272 | 1 |
'''simple docstring'''
def snake_case__ ( _A: list ) -> list:
'''simple docstring'''
lowerCAmelCase = len(_A )
for i in range(1 , _A ):
lowerCAmelCase = collection[i]
lowerCAmelCase = 0
lowerCAmelCase = i - 1
while low <= high:
... | 272 | '''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def snake_case__ ( _A: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
lowerCAmelCase = dict(zip(_A , _A ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) ... | 272 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avai... | 272 | '''simple docstring'''
import os
import string
import sys
__lowercase = 1 << 8
__lowercase = {
'''tab''': ord('''\t'''),
'''newline''': ord('''\r'''),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 272 | 1 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiff... | 0 | '''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 272 | 0 |
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