code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import GenerationTest... | 334 | """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
... | 44 | 0 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 61 | """simple docstring"""
from __future__ import annotations
_a : List[str] = 10
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : list[int] ) -> list[int]:
_lowerCAmelCase : Optional[int] = 1
_lowerCAmelCase : Union[str, Any] ... | 44 | 0 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLayer,
... | 195 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.... | 44 | 0 |
from math import factorial
class lowercase__ :
'''simple docstring'''
def __init__( self, __magic_name__, __magic_name__ ) -> List[str]:
"""simple docstring"""
UpperCamelCase__ : Dict = real
if is... | 201 | """simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 44 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .te... | 131 | """simple docstring"""
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 8 ,_lowerCamelCase : int | None = None ) -> str:
_lowerCAmelCase : int = np.random.default_rng(seed=_lowerCamelCase )
# Roughly 25% ... | 44 | 0 |
'''simple docstring'''
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/... | 208 | """simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threade... | 44 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils import ... | 20 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : List[Any] = logging.get_logger(__name__)
_a : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-win... | 44 | 0 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __A ( a_ :np.ndarray , a_ :float) -> np.ndarray:
# For applying gaussian function for each element in matrix.
__a : Tuple = math.sqrt(_lowerCamelCase)
... | 160 | """simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __A ( unittest.TestCase ):
def __A ( self ):
... | 44 | 0 |
"""simple docstring"""
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(
"""pipelines_utils""",
"""0.22.0""",
"""Importing `DiffusionPipeline` or `ImagePipelineOutput` from diffusers.pipeline_utils is deprecated. Please import ... | 91 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list ) ->list:
'''simple docstring'''
for i in range(len(_lowerCamelCase ) - 1 , 0 , -1 ):
a : Dict = False
for j in range(_lowerCamelCase , ... | 105 | """simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __A ( SCREA... | 44 | 0 |
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_image, load_numpy, slow, torc... | 214 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 44 | 0 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
AutoT... | 334 | """simple docstring"""
from math import ceil
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ,_lowerCamelCase : Union[str, Any] ) -> int:
_lowerCAmelCase : Dict = list(range(0 ,_lowerCamelCase ) )
_lowerCAmelCase : ... | 44 | 0 |
"""simple docstring"""
_a = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingf... | 61 | """simple docstring"""
_a : List[str] = {
'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',
... | 44 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://huggingface.co... | 195 | """simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 44 | 0 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
... | 201 | """simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
_a : Dict = datasets.utils.logging.get_logger(__name__)
@dataclass
class __A... | 44 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
class _a ( ... | 131 | """simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 44 | 0 |
'''simple docstring'''
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docs... | 208 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> int:
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("""multiplicative_persistence() only accepts integral values""" )
if num < 0:
raise ValueError("""multiplicative_persistence() does... | 20 | """simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from .... | 44 | 0 |
"""simple docstring"""
from collections import defaultdict
class __lowercase :
'''simple docstring'''
def __init__( self , _UpperCAmelCase , _UpperCAmelCase ):
__a : Optional[Any] = total # total no of tasks (N)
... | 160 | """simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Optional[Any] ,_lowerCamelCase : int ) ... | 44 | 0 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
r... | 91 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_a : List[Any] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'token... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impo... | 105 | """simple docstring"""
from scipy.stats import pearsonr
import datasets
_a : str = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the... | 44 | 0 |
import itertools
import string
from collections.abc import Generator, Iterable
def snake_case__ ( SCREAMING_SNAKE_CASE_ : Iterable[str] , SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
lowercase__ : List[Any] = iter(_lowerCamelCase )
while True:
... | 214 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 50 ) -> int:
_lowerCAmelCase : int = [1] * (length + 1)
for row_length in range(3 ,length + 1 ):
for block_length in range(3 ,row_length + 1 ):
for block_start in range(... | 44 | 0 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_v... | 334 | """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
... | 44 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kand... | 61 | """simple docstring"""
from __future__ import annotations
_a : List[str] = 10
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : list[int] ) -> list[int]:
_lowerCAmelCase : Optional[int] = 1
_lowerCAmelCase : Union[str, Any] ... | 44 | 0 |
UpperCAmelCase = tuple[float, float, float]
UpperCAmelCase = tuple[float, float, float]
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = end_pointa[0] - end_pointa[0]
lowercase = end_pointa[1] - end_pointa[1]
lowercase... | 195 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.... | 44 | 0 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNet... | 201 | """simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 44 | 0 |
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import Tok... | 131 | """simple docstring"""
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 8 ,_lowerCamelCase : int | None = None ) -> str:
_lowerCAmelCase : int = np.random.default_rng(seed=_lowerCamelCase )
# Roughly 25% ... | 44 | 0 |
'''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 lowerCamelCase_ :
"""simple docs... | 208 | """simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threade... | 44 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> bool:
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
lowercase : Any = str(_lowerCamelCase )
lowercase : ... | 20 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : List[Any] = logging.get_logger(__name__)
_a : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-win... | 44 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __A ( ) -> Optional[Any]:
__a : Optional[Any] = ArgumentParser('''Diffusers CLI tool''' , usage='''diffusers-cli <command> [<args>]''')
__a ... | 160 | """simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __A ( unittest.TestCase ):
def __A ( self ):
... | 44 | 0 |
"""simple docstring"""
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase_ : Optional[int] = logging.get_logger(__name__)
def _A (__a ... | 91 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 0 |
"""simple docstring"""
from functools import lru_cache
def _SCREAMING_SNAKE_CASE ( _lowercase : int ) ->set:
'''simple docstring'''
a : Optional[int] = 2
a : List[Any] = set()
while i * i <= n:
if n % i:
i += 1... | 105 | """simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __A ( SCREA... | 44 | 0 |
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
snake_case_ = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE__ :
def __init__( self):
lowercase__ ... | 214 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 44 | 0 |
_lowerCamelCase ='0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .l... | 334 | """simple docstring"""
from math import ceil
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ,_lowerCamelCase : Union[str, Any] ) -> int:
_lowerCAmelCase : Dict = list(range(0 ,_lowerCamelCase ) )
_lowerCAmelCase : ... | 44 | 0 |
"""simple docstring"""
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet impo... | 61 | """simple docstring"""
_a : List[str] = {
'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',
... | 44 | 0 |
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE=0 ):
# Format the message.
if name is None:
lowercase = ... | 195 | """simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 44 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __UpperCAmelCase: int | str ) -> bool:
UpperCamelCase__ : Tuple = str(_lowerCamelCase )
return n == n[::-1]
def lowerCAmelCase_ ( __UpperCAmelCase: int = 100_0000 )... | 201 | """simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
_a : Dict = datasets.utils.logging.get_logger(__name__)
@dataclass
class __A... | 44 | 0 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
fro... | 131 | """simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 44 | 0 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
_UpperCamelCase = 6378137.0
_UpperCamelCase = 6356752.314245
_UpperCamelCase = 6378137
def a_ ( _lowerCAmelCase ,_lowerCAmelCase ,_lowerCA... | 208 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokenizer,... | 20 | """simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from .... | 44 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
A = True
except (ImportError, ModuleNotFoundError):
A = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
def... | 160 | """simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Optional[Any] ,_lowerCamelCase : int ) ... | 44 | 0 |
"""simple docstring"""
def _A (__a ) -> Dict:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Any = min(_lowerCamelCase ) # min() finds the minimum value
SCREAMING_SNAKE_CASE_ : Dict = max(_lowerCamelCase ) # max() finds the ... | 91 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_a : List[Any] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'token... | 44 | 0 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
a : str = '\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. an... | 105 | """simple docstring"""
from scipy.stats import pearsonr
import datasets
_a : str = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the... | 44 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {'vocab_file': 'vocab.json', 'merges_f... | 214 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 50 ) -> int:
_lowerCAmelCase : int = [1] * (length + 1)
for row_length in range(3 ,length + 1 ):
for block_length in range(3 ,row_length + 1 ):
for block_start in range(... | 44 | 0 |
def snake_case__ ( lowerCAmelCase_, lowerCAmelCase_, lowerCAmelCase_, lowerCAmelCase_ ):
"""simple docstring"""
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
SCREAMING_SNAKE_CASE =mf_knapsack(i - 1, _lo... | 334 | """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
... | 44 | 0 |
"""simple docstring"""
import numpy as np
class A_ :
'''simple docstring'''
def __init__( self ):
"""simple docstring"""
UpperCAmelCase_ : Optional[Any] = (0, 0)
UpperCAmelCase_ : Optional[Any] = None
UpperCAmelCase_ : int ... | 61 | """simple docstring"""
from __future__ import annotations
_a : List[str] = 10
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : list[int] ) -> list[int]:
_lowerCAmelCase : Optional[int] = 1
_lowerCAmelCase : Union[str, Any] ... | 44 | 0 |
from collections.abc import Sequence
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
return sum(c * (x**i) for i, c in enumerate(_lowerCamelCase ) )
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ... | 195 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.... | 44 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class ... | 201 | """simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 44 | 0 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class _a ( unittest.TestCase):
def UpperCAmelCase__( s... | 131 | """simple docstring"""
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 8 ,_lowerCamelCase : int | None = None ) -> str:
_lowerCAmelCase : int = np.random.default_rng(seed=_lowerCamelCase )
# Roughly 25% ... | 44 | 0 |
'''simple docstring'''
def a_ ( _lowerCAmelCase ,_lowerCAmelCase ) -> bool:
__lowerCamelCase : Optional[int] = len(_lowerCamelCase )
__lowerCamelCase : str = [[False] * (required_sum + 1) for _ in range(arr... | 208 | """simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threade... | 44 | 0 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _snake_case( ) -> str:
lowercase : Optional[Any] = ArgumentParser(
description=(
"""Py... | 20 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : List[Any] = logging.get_logger(__name__)
_a : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-win... | 44 | 0 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configur... | 160 | """simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __A ( unittest.TestCase ):
def __A ( self ):
... | 44 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase_ : List[Any] = logging.get_logger(__name__)
UpperCAmelCase_ : Union[str, Any... | 91 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 0 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
a : Union[str, Any] = pytest.mark.integration... | 105 | """simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __A ( SCREA... | 44 | 0 |
snake_case_ = [
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,
]
snake_case_ = [
999,
976,
952,
928,
... | 214 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 44 | 0 |
def snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
if not isinstance(_lowerCamelCase, _lowerCamelCase ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(_lowerCamelCase ) == 0:
raise ValueError('Input list must... | 334 | """simple docstring"""
from math import ceil
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ,_lowerCamelCase : Union[str, Any] ) -> int:
_lowerCAmelCase : Dict = list(range(0 ,_lowerCamelCase ) )
_lowerCAmelCase : ... | 44 | 0 |
"""simple docstring"""
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def __a ( ):
UpperCAmel... | 61 | """simple docstring"""
_a : List[str] = {
'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',
... | 44 | 0 |
import math
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
if (
not isinstance(_lowerCamelCase , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError('power_factor must be a valid float value between -1 and ... | 195 | """simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 44 | 0 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCAmelCase_ = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation... | 201 | """simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
_a : Dict = datasets.utils.logging.get_logger(__name__)
@dataclass
class __A... | 44 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...utils i... | 131 | """simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 44 | 0 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowerCamelCase_ ( ctypes.Structure ):
"""simple docstring"""
a_ ... | 208 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 | 0 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_... | 20 | """simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from .... | 44 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class __lowercase ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
__lowerCAmelCase = "WhisperFeatureExtractor"
__lowerCAmelCase = "WhisperTokenizer"
... | 160 | """simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Optional[Any] ,_lowerCamelCase : int ) ... | 44 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from fla... | 91 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_a : List[Any] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'token... | 44 | 0 |
"""simple docstring"""
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import Mask... | 105 | """simple docstring"""
from scipy.stats import pearsonr
import datasets
_a : str = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the... | 44 | 0 |
def snake_case__ ( SCREAMING_SNAKE_CASE_ : List[Any]=28_123 ):
'''simple docstring'''
lowercase__ : List[str] = [1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit // i + 1 ... | 214 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 50 ) -> int:
_lowerCAmelCase : int = [1] * (length + 1)
for row_length in range(3 ,length + 1 ):
for block_length in range(3 ,row_length + 1 ):
for block_start in range(... | 44 | 0 |
from __future__ import annotations
def snake_case__ ( lowerCAmelCase_, lowerCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE =[]
create_all_state(1, _lowerCamelCase, _lowerCamelCase, [], _lowerCamelCase )
return result
def ... | 334 | """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
... | 44 | 0 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availa... | 61 | """simple docstring"""
from __future__ import annotations
_a : List[str] = 10
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : list[int] ) -> list[int]:
_lowerCAmelCase : Optional[int] = 1
_lowerCAmelCase : Union[str, Any] ... | 44 | 0 |
from collections import Counter
from timeit import timeit
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE = "" , ):
return sum(c % 2 for c in Counter(input_str.replace(' ' , '' ).lower() ).values() ) < 2
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE = ... | 195 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.... | 44 | 0 |
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase_ ( __UpperCAmelCase: Any , __UpperCAmelCase: List... | 201 | """simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 44 | 0 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 131 | """simple docstring"""
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 8 ,_lowerCamelCase : int | None = None ) -> str:
_lowerCAmelCase : int = np.random.default_rng(seed=_lowerCamelCase )
# Roughly 25% ... | 44 | 0 |
'''simple docstring'''
import re
import subprocess
import sys
_UpperCamelCase = subprocess.check_output('git merge-base main HEAD'.split()).decode('utf-8')
_UpperCamelCase = (
subprocess.check_output(f'''git diff --diff-filter=d --name-only {fork_point_sha}'... | 208 | """simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threade... | 44 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDITIONA... | 20 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : List[Any] = logging.get_logger(__name__)
_a : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-win... | 44 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
'bert-base-uncase... | 160 | """simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __A ( unittest.TestCase ):
def __A ( self ):
... | 44 | 0 |
"""simple docstring"""
def _A (__a = 1_00_00_00 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = 1
SCREAMING_SNAKE_CASE_ : str = 1
SCREAMING_SNAKE_CASE_ : List[str] = {1: 1}
for inputa in range(2 ... | 91 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Dict = {
'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
... | 105 | """simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __A ( SCREA... | 44 | 0 |
from __future__ import annotations
from math import pow, sqrt
def snake_case__ ( SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float ):
'''simple docstring'''
if (resistance, reactance, impedance).count(0 ) != 1:
rai... | 214 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 44 | 0 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class a_ ( SCREAMING_SNAKE_CASE_ ... | 334 | """simple docstring"""
from math import ceil
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ,_lowerCamelCase : Union[str, Any] ) -> int:
_lowerCAmelCase : Dict = list(range(0 ,_lowerCamelCase ) )
_lowerCAmelCase : ... | 44 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_a = {
'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2Vec2Con... | 61 | """simple docstring"""
_a : List[str] = {
'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',
... | 44 | 0 |
from ...configuration_utils import PretrainedConfig
class A_ ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
_UpperCamelCase : Optional[Any] = "bert-generation"
def __init__( self , snake_case=5_0358 , snake_case=1024 , snake_case=24 , snak... | 195 | """simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 44 | 0 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterM... | 201 | """simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
_a : Dict = datasets.utils.logging.get_logger(__name__)
@dataclass
class __A... | 44 | 0 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
lowerCamelCase = 'src/transformers'
lowerCamelCase = 'docs/sourc... | 131 | """simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditional... | 44 | 0 |
'''simple docstring'''
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def a_ (... | 208 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 | 0 |
import itertools
import math
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> bool:
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... | 20 | """simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from .... | 44 | 0 |
"""simple docstring"""
import enum
import shutil
import sys
A = shutil.get_terminal_size()
A = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class __lowercase ( enum.Enum ):
'''simple docstring'''
__lowerCAm... | 160 | """simple docstring"""
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Optional[Any] ,_lowerCamelCase : int ) ... | 44 | 0 |
"""simple docstring"""
def _A (__a ) -> bool:
"""simple docstring"""
if not all(x.isalpha() for x in string ):
raise ValueError('''String must only contain alphabetic characters.''' )
SCREAMING_SNAKE_CASE_ : List[str] = sorted(string... | 91 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_a : List[Any] = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'token... | 44 | 0 |
"""simple docstring"""
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
a : int = logging.get_logger(__name__... | 105 | """simple docstring"""
from scipy.stats import pearsonr
import datasets
_a : str = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the... | 44 | 0 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class SCREAMING_SNAKE_CASE__ (SCREAMING_SNAKE_CASE_ ):
__lowerCamelCase ... | 214 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 50 ) -> int:
_lowerCAmelCase : int = [1] * (length + 1)
for row_length in range(3 ,length + 1 ):
for block_length in range(3 ,row_length + 1 ):
for block_start in range(... | 44 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision_... | 334 | """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
... | 44 | 0 |
"""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_ (SCREAMING_SNAKE_CASE_ ,unittest.TestCase ):
'''simple docstring'''
SC... | 61 | """simple docstring"""
from __future__ import annotations
_a : List[str] = 10
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : list[int] ) -> list[int]:
_lowerCAmelCase : Optional[int] = 1
_lowerCAmelCase : Union[str, Any] ... | 44 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutputWith... | 195 | """simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.... | 44 | 0 |
import os
import pytest
from attr import dataclass
UpperCAmelCase_ = 'us-east-1' # defaults region
@dataclass
class lowercase__ :
'''simple docstring'''
a : str
a : Any = "arn:aws:iam::558105141721:role/sagemaker_execu... | 201 | """simple docstring"""
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 44 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_d... | 131 | """simple docstring"""
import numpy as np
import qiskit
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int = 8 ,_lowerCamelCase : int | None = None ) -> str:
_lowerCAmelCase : int = np.random.default_rng(seed=_lowerCamelCase )
# Roughly 25% ... | 44 | 0 |
'''simple docstring'''
def a_ ( _lowerCAmelCase ,_lowerCAmelCase ) -> bool:
__lowerCamelCase : Union[str, Any] = len(_lowerCamelCase ) + 1
__lowerCamelCase : Any = len(_lowerCamelCase ) + 1
# dp ... | 208 | """simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threade... | 44 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 20 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : List[Any] = logging.get_logger(__name__)
_a : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-win... | 44 | 0 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, 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... | 160 | """simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class __A ( unittest.TestCase ):
def __A ( self ):
... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase_ : List[str] = 10
def _A (__a ) -> list[int]:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[int] = 1
SCREAMING_SNAKE_CASE_ : Union[str, Any] = m... | 91 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 0 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] , _lowercase : list[int] , _lowercase : int ) ->tuple[float, list[float]]:
'''simple docstring'''
... | 105 | """simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __A ( SCREA... | 44 | 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_image_inputs
if is_torch_available():
import to... | 214 | """simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandin... | 44 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
def wrapper(*lowerCAmelCase_, **lowerCAmelCase_ ):
SCREAMI... | 334 | """simple docstring"""
from math import ceil
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ,_lowerCamelCase : Union[str, Any] ) -> int:
_lowerCAmelCase : Dict = list(range(0 ,_lowerCamelCase ) )
_lowerCAmelCase : ... | 44 | 0 |
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