code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
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
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'fac... | 61 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
snake_case = False
class SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstrin... | 62 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib... | 63 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 0 |
import warnings
from .generation import TFGenerationMixin
class _lowerCamelCase ( UpperCamelCase_ ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transformers v5. Import... | 64 |
'''simple docstring'''
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 ImageProcessingS... | 28 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
__UpperCAmelCase = '\\n\n'
__UpperCAmelCase = '\nPerplexity (PPL) is one of the m... | 65 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 0 |
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> str:
return "".join([hex(SCREAMING_SNAKE_CASE )[2:].zfill(2 ).upper() for byte in list(SCREAMING_SNAKE_CASE )] )
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> bytes:
# Check data validity, following RF... | 66 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"""camembert-base""": """https:... | 67 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 0 |
def lowercase__ ( A_: str ) -> list:
"""simple docstring"""
__UpperCAmelCase =[0] * len(A_ )
for i in range(1 , len(A_ ) ):
# use last results for better performance - dynamic programming
__UpperCAmelCase =... | 68 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 0 |
'''simple docstring'''
import cmath
import math
def __UpperCAmelCase ( _UpperCAmelCase : float , _UpperCAmelCase : float , _UpperCAmelCase : float , _UpperCAmelCase : float ) -> complex:
__snake_case = math.radians(_UpperCAmelCase )
__snake_cas... | 69 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 0 |
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("3.8"):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
lowerCamelCase ... | 70 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import ... | 71 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 0 |
'''simple docstring'''
import os
from pathlib import Path
def UpperCamelCase ( ) -> Any:
'''simple docstring'''
from torch.utils.cpp_extension import load
lowercase =Path(lowercase_ ).resolve().parent.parent.parent / '''kernels''' / '''deformable_detr'''
lowercase =[
... | 72 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 0 |
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 lowerCamelCase__ ... | 73 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 0 |
def a__ ( snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Any = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def a__ ( snake_case = 100 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Dic... | 74 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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 im... | 75 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normal... | 76 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 0 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common... | 77 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int = 10_00 ) -> int:
'''simple docstring'''
return sum(e for e in range(3 , snake_case_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"{solution() = }")
| 78 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class UpperCAmelCase_ ( __lowerCamelCase ... | 79 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __UpperCamelCase :
__snake_case :int
__snake_case :int
class __UpperCamelCase :
def __init__( self : Any ... | 80 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 0 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxMT... | 81 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 0 |
"""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_imag... | 82 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 0 |
"""simple docstring"""
from importlib import import_module
from .logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
class __snake_case :
def __init__( self : str , __lowerCAmelCase : Optional[int] , __lowerCAmelCase : Optional[Any]=None )... | 83 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 0 |
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 TFModelTesterMixin, ids_tensor, random_... | 84 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 0 |
SCREAMING_SNAKE_CASE__ : Union[str, Any] = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0... | 85 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 0 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTok... | 86 |
'''simple docstring'''
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 ImageProcessingS... | 28 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase : Dict = logging.get_logger(__name__)
_lowerCamelCase : ... | 87 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 0 |
"""simple docstring"""
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : int ):
"""simple docstring"""
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""" )
if rate_... | 88 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 0 |
SCREAMING_SNAKE_CASE : List[Any] = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
SCREAMING_SNAKE_CASE : Opt... | 89 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__UpperCAmelCase = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''... | 90 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 0 |
"""simple docstring"""
def _snake_case ( snake_case__ : int , snake_case__ : int ):
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
A = str(bin(snake_case__ ) )[2:] # remove the leading "0b"
A = str(bin(snake_case__ ) )[2:] # remove the leading... | 91 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 0 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common ... | 92 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=a ):
"""simple docstring"""
__magic_name__ :List[Any] = ["""torch""", """scipy"""]
def __init__( self , *__UpperCAmelCase , ... | 93 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'edbeeching/decision-transformer-gym-hopper-medium': (
'https://huggingface.co/edbeeching/de... | 94 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase_ = []
def snake_case ( A__ ,A__ ,A__ ):
for i in range(len(A__ ) ):
if board[row][i] == 1:
return False
for i in range(len(A__ ) ):
if board[i][column] == 1:
return Fa... | 95 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 0 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __A ( nn.Module ):
UpperCAmelCase__ = 42
Uppe... | 96 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 0 |
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 (
IMAGENET_STANDARD_MEAN,... | 97 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : List[str] = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
tr... | 98 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 0 |
from __future__ import annotations
def a (lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
if days_between_payments <= 0:
raise ValueError("""days_between_payments must be > 0""" )
if daily_interest_rate < 0:
raise ValueError("""daily_interest_rate must be >=... | 99 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 0 |
def __snake_case ( lowerCAmelCase_ ) -> int:
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
SCREAMING_SNAKE_CASE__ ... | 100 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 0 |
from collections import deque
class __lowercase :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
"""simple docstring"""
SCREAMIN... | 101 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 0 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ... | 102 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
snake_case = log... | 103 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _lowerCamelCase ( UpperCAmelCase_ : str, UpperCAmelCase_ : dict ) -> str:
"""simple docstring"""
A__ = BeautifulSoup(requests.get(UpperCAmelCase_, pa... | 104 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 0 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
UpperCamelCase__ : Union[str, Any] ... | 105 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :str =logging.get_logger(__name__)
__snake_case :Tuple ={
'facebook/s2t-wav2vec2-large-en-de': (
'https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'
... | 106 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 0 |
'''simple docstring'''
import math
def _SCREAMING_SNAKE_CASE ( __snake_case : int ):
assert isinstance(__snake_case , __snake_case ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
retur... | 107 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 0 |
from __future__ import annotations
from typing import Any
def _SCREAMING_SNAKE_CASE ( __snake_case ) -> None:
create_state_space_tree(__snake_case , [] , 0 )
def _SCREAMING_SNAKE_CASE ( __snake_case , __snake_case , __snake_case ) -> ... | 108 |
'''simple docstring'''
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 ImageProcessingS... | 28 | 0 |
'''simple docstring'''
import math
import random
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase = False ) -> float:
'''simple docstring'''
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
a = 0.02
... | 109 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 0 |
"""simple docstring"""
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCamelCase ( _snake_case ):
UpperCAmelCase__ : Optional[Any] = [
'encoder.version',
'decoder.version',
'mo... | 110 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 0 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
loggi... | 537 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class __lowerCamelCase :
def __init__( self , UpperCAmelCase ):
lowerCamelCase_ = []
self.adlist.append(
{'''value''': '''''', '''next_states''': [], '''fail_state''': ... | 29 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"GroupViTOnnxConfig",
"GroupViTT... | 475 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 0 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('''To use the rich extension, install rich with `pip install rich`''')
| 392 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 0 |
import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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, ids_tensor, random_attention_ma... | 652 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 0 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class lowercase_ ( nn... | 443 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 0 |
from collections.abc import Callable
import numpy as np
def lowercase_ ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowercase = int(np.ceil((x_end - xa) / step_size ) )
... | 639 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 0 |
'''simple docstring'''
from __future__ import annotations
def A ( UpperCamelCase_ : int ) -> Dict:
'''simple docstring'''
lowerCAmelCase__ = 2
lowerCAmelCase__ = []
while i * i <= n:
if n % i:
i += 1
else:
n //... | 48 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 0 |
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... | 604 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER... | 33 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
a_ :Union[str, Any] = get_logger(__name__)
class snake_case__ ( enum.Enum ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = '''all_chec... | 478 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 0 |
def lowercase( UpperCamelCase_ , UpperCamelCase_ ) -> Dict:
'''simple docstring'''
while a != 0:
UpperCamelCase = b % a, a
return b
def lowercase( UpperCamelCase_ , UpperCamelCase_ ) -> List[Any]:
'''simple docstring'''
if gcd(__Uppe... | 537 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 0 |
"""simple docstring"""
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase ( ):
lowerCamelCase_ = 9, 14 # noqa: F841
lowerCamelCase_ = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7... | 29 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
A = logging.get_logger(__name__)
A = {"vocab_file": ... | 475 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 0 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import FlaxAu... | 392 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 0 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
a =50000
a =5000
a , a =os.path.split(__file__)
a =os.path.join(RESULTS_BASEPATH, """results""", RESULTS_FILENAME.replace(""".py""", """.json"""))
@g... | 652 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 0 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : int , UpperCAmelCase_ : int , UpperCAmelCase_ : float = 1 / sqrt(2 ) ) -> Any:
SCREAMING_SNAKE_CASE_ : int =tau * ... | 443 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 0 |
import os
import sys
import unittest
a : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, f... | 639 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase__ : int = {
"configuration_blenderbot_small": [
... | 48 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 0 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand... | 604 |
'''simple docstring'''
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 ImageProcessingS... | 28 | 0 |
import inspect
import unittest
from transformers import MobileViTConfig
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 ConfigTester
f... | 33 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 0 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def lowercase_ ():
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_dirname
from... | 478 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 0 |
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import tensorflow as tf
from tokenize... | 537 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 0 |
"""simple docstring"""
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... | 29 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
A = logging.get_logger(__name__)
A = {
"SenseTime/deformable-detr": "https://huggingface.co/sensetime/deformable-detr/resolve/main/config.json",
# See all D... | 475 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def lowercase ( _lowerCAmelCase ):
UpperCAmelCase__ = {}
UpperCAmelCase__ = job['started_at']
UpperCAmelCase__ = job['completed_at']
UpperCAmelCase__ ... | 392 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 0 |
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokenizer, HfArgume... | 652 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 0 |
import numpy as np
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : np.array ) -> Optional[int]:
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 443 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 0 |
def lowercase_ ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
def get_matched_characters(_UpperCamelCase , _UpperCamelCase ) -> str:
__lowercase = []
__lowercase = min(len(_stra ) , len(_stra ) ) // 2
for i, l in en... | 639 |
'''simple docstring'''
from typing import Dict
from .base import GenericTensor, Pipeline
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase_ ( self, A=None, A=None, A=None, ... | 28 | 0 |
'''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_fast import BertTokenizerFast
from .tokenization_dpr import DPRConte... | 48 |
'''simple docstring'''
from __future__ import annotations
import queue
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CA... | 28 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.ut... | 604 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from trans... | 28 | 0 |
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase = 100_0000 ) -> Dict:
snake_case__ = set(range(3 , __UpperCamelCase , 2 ) )
primes.add(2 )
for p in range(3 , __UpperCamelCase , 2 ):
if p not in primes:
continue
primes.difference_upd... | 33 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCam... | 28 | 0 |
from math import ceil
def lowercase_ (A : int = 1_0_0_1 ):
snake_case__ : Any = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
snake_case__ : str = 2 * i + 1
snake_case__ : Tuple = 2 * i
... | 478 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorT... | 28 | 0 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ImageProcessingSavin... | 537 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def lowercase__( ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : str = 9, 14 ... | 28 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from datasets... | 29 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A = {
"configuration_efficientnet": [
"EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP",
"EfficientNetConfi... | 475 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [i - 1 for i in range(limit + 1 )]
for i in range(2 ,limit + 1 ):
if phi[i] == ... | 28 | 0 |
def lowercase ( _lowerCAmelCase = 1000 ):
return sum(e for e in range(3 , __UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 392 |
'''simple docstring'''
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tok... | 28 | 0 |
a =[
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase__ , lowerCamelCase... | 652 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
... | 28 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokeniza... | 443 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class... | 28 | 0 |
from __future__ import annotations
def lowercase_ ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , ):
'''simple docstring'''
__lowercase = len(__UpperCamelCase )
# If row is equal to the... | 639 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCamelCase_ = logging.get_logger("transformers.models.speecht5")
def lowercase__( __UpperCame... | 28 | 0 |
'''simple docstring'''
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,... | 48 |
'''simple docstring'''
from typing import Any
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = ... | 28 | 0 |
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __lowercase ( _A ):
lowercase = None
lowercase ... | 604 |
'''simple docstring'''
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 ImageProcessingS... | 28 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __magic_name__ (snake_case_ ):
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( self:str , _a:Optional[int]=None , _a:Union[str, Any]=None , _a:int=None , **_a:Optiona... | 33 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableData... | 28 | 0 |
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
... | 478 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_configura... | 28 | 0 |
import itertools
import math
def lowercase( UpperCamelCase_ ) -> Optional[Any]:
'''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 numbers, all multiples of 3 are not primes
... | 537 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
UpperCamelCase_ = logg... | 28 | 0 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device... | 29 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformer... | 28 | 0 |
def __UpperCAmelCase ( __A ) -> Optional[Any]:
'''simple docstring'''
UpperCAmelCase__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def __UpperCAmelCase ( __A ) -> Opti... | 475 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = val
SCREAMING_SNA... | 28 | 0 |
import datasets
from .evaluate import evaluate
snake_case__ : List[Any] = '''\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitl... | 392 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase__( *__UpperCamelCase: Union[str, Any] ,__UpperCamelCase: Optional[Union[Dict, Any]] = None ,__UpperCamelCase: Dict=True... | 28 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a ="""\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] After o... | 652 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_roformer":... | 28 | 0 |
from collections import deque
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : List[Any] ) -> Dict:
SCREAMING_SNAKE_CASE_ : Tuple =len(__UpperCamelCase )
SCREAMING_SNAKE_CASE_ : str =deque()
SCREAMING_SNAKE_CASE_ : int =[False for _ in ra... | 443 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase ,__UpperCamelCase ):
raise TypeError('Input value must be an \'int\' type' )
SCREAMING_SNAKE_CASE : i... | 28 | 0 |
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