code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto imp... | 41 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
... | 251 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/... | 42 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ... | 251 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__lowercase = get_logger(__name__)
class lowerCamelCase_ ( enum.Enum ):
'''simple docstring'''
a__ : Union[str, Any] = """all_check... | 43 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase__( __UpperCamelCase: Union[d... | 251 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_a : Optional[Any] = TypeVar('T')
class __A ( Generic[T] ):
def __init__( self , a__ ):
_lowerCAmelCase : Optional... | 44 |
'''simple docstring'''
from itertools import product
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = sides_number
SCREAMING_SNAKE_CASE : str = max_face_number * dic... | 251 | 0 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Re... | 45 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Any = 0
SCREAMING_SNAKE_CASE : str = 0
... | 251 | 0 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWaterm... | 46 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] = [int(__UpperCamelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(__UpperCamelCase ) == 4 and all(0 <... | 251 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelCase : List[Any] = {
"facebook/xglm-564M": "https://huggingface.co/facebook/xglm-564M/resolve/main/config.json",
... | 47 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"microsoft/git-base": "https://huggingface... | 251 | 0 |
from __future__ import annotations
def A ( _SCREAMING_SNAKE_CASE ) -> bool:
lowerCamelCase : int = str(_SCREAMING_SNAKE_CASE )
return len(_SCREAMING_SNAKE_CASE ) == 9 and set(_SCREAMING_SNAKE_CASE ) == set("123456789" )
def A ( )... | 48 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"toke... | 251 | 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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
fr... | 49 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase_ = [ord(letter)... | 251 | 0 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
_UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE ( _UpperCAmelC... | 50 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCamelCase_ ... | 251 | 0 |
def A (__A : list[int] , __A : list[int] , __A : int ) -> bool:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__A ) )
def A... | 51 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaske... | 251 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def A_ ( _lowerCAmelCase ) -> Optional[int]:
if "cls_token" in name:
UpperCamelCase : Union[str, Any] = name.replace("cls_toke... | 52 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _... | 251 | 0 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowercase__ ( __lowercase : List[Any] ) -> Optional[int]:
"""simple docstring"""
def wrapper(*__... | 53 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 251 | 0 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 54 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
... | 251 | 0 |
'''simple docstring'''
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
fro... | 55 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
class _a ... | 251 | 0 |
'''simple docstring'''
from maths.prime_factors import prime_factors
def __magic_name__ ( __UpperCAmelCase ) -> int:
'''simple docstring'''
if not isinstance(__UpperCAmelCase, __UpperCAmelCase ):
snake_case_ = F"Input value of [number={number}] must be an integer"... | 56 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_funnel": ["FUNNEL_PRETRAINED_... | 251 | 0 |
"""simple docstring"""
# Imports
import numpy as np
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a=None , __a=None , __a=None , __a=None , __a=None ):
self.set_matricies(red=__a , green=__a , blue=__a , red_edge=... | 57 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase_ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_a... | 251 | 0 |
'''simple docstring'''
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 ... | 58 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 251 | 0 |
from __future__ import annotations
def UpperCamelCase ( __lowerCamelCase : list , __lowerCamelCase : int , __lowerCamelCase : int , __lowerCamelCase : int ):
snake_case : Union[str, Any] = []
snake_case , snake_case ... | 59 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase_ = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from b... | 251 | 0 |
"""simple docstring"""
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.s... | 60 |
'''simple docstring'''
from __future__ import annotations
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [True] * limit
SCREAMING_SNAKE_CASE : List[str] = False
SCREAMING_SNAKE_CA... | 251 | 0 |
"""simple docstring"""
from string import ascii_uppercase
_a = {str(ord(c) - 55): c for c in ascii_uppercase}
def __a ( __lowerCamelCase, __lowerCamelCase ):
if isinstance(__lowerCamelCase, __lowerCamelCase ):
raise TypeError("int() can't convert non-string with explicit b... | 61 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Optional[Any] ... | 251 | 0 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTe... | 62 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' ,[
['full:README.md', 'dataset_infos.json'],
['empty:README... | 251 | 0 |
'''simple docstring'''
from math import factorial
def _lowerCamelCase ( lowercase : int = 20 ) -> int:
_a = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
_a = n // 2
return int(factorial(lowercase ) / (... | 63 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
... | 251 | 0 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def UpperCAmelCase__ (snake_case__ : str , snake_case__ : float | Decimal , snake_case__ : float = 10**-... | 64 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ... | 251 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCas... | 65 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase__( __UpperCamelCase: Union[d... | 251 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__a = {
"configuration_longt5": ["LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP", "LongT5Config", "LongT5OnnxConfig"],
}
try:
if not is_torch_a... | 66 |
'''simple docstring'''
from itertools import product
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = sides_number
SCREAMING_SNAKE_CASE : str = max_face_number * dic... | 251 | 0 |
'''simple docstring'''
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__ , UpperCamelCase__ , Up... | 67 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Any = 0
SCREAMING_SNAKE_CASE : str = 0
... | 251 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
"""xlm-mlm-en-2048""": """https://huggin... | 68 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] = [int(__UpperCamelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(__UpperCamelCase ) == 4 and all(0 <... | 251 | 0 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
__UpperCamelCase = HUGGINGFACE_HUB_CACHE
__UpperCamelCase = '''config.json'''
__UpperCamelCase = '''diffusion_pytorch_model.bin'''
__UpperCamelCase = '''diffusion_fl... | 69 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"microsoft/git-base": "https://huggingface... | 251 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A__ : Tuple ={
'''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpO... | 70 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"toke... | 251 | 0 |
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 import TFModelTesterMixin, floats_... | 71 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase_ = [ord(letter)... | 251 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...t... | 72 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCamelCase_ ... | 251 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ ) -> Optional[int]:
if "cls_token" in name:
__lowerCamelCase : Dict ... | 73 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaske... | 251 | 0 |
"""simple docstring"""
# Function to print upper half of diamond (pyramid)
def _snake_case ( snake_case__ : Dict ):
for i in range(0 , snake_case__ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 , i + 1 ): # pr... | 74 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _... | 251 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
a_ : str = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDep... | 75 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 251 | 0 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 76 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
... | 251 | 0 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .schedulin... | 77 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
class _a ... | 251 | 0 |
"""simple docstring"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_commo... | 78 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_funnel": ["FUNNEL_PRETRAINED_... | 251 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase ) -> int:
'''simple docstring'''
assert isinstance(__lowercase , __lowercase ), F'''The input value of [n={number}] is not an integer'''
if number == 1:
return 2
elif number < 1:... | 79 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase_ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_a... | 251 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : str = {
'configuration_rembert': ['REMB... | 80 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 251 | 0 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..... | 81 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase_ = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from b... | 251 | 0 |
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
_lowerCAmelCase = int(snake_case )
if n_element < 1:
_lowerCAmelCase = ValueError("""a should be a positive number""" )
raise my_error
_lowerCAmelCase = [1]
_lowerCA... | 82 |
'''simple docstring'''
from __future__ import annotations
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [True] * limit
SCREAMING_SNAKE_CASE : List[str] = False
SCREAMING_SNAKE_CA... | 251 | 0 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
fr... | 83 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Optional[Any] ... | 251 | 0 |
"""simple docstring"""
def _snake_case ( lowercase__ : int = 1_0_0_0 ) -> int:
'''simple docstring'''
lowerCAmelCase_ :Optional[Any] = 2**power
lowerCAmelCase_ :List[Any] = str(lowercase__ )
lowerCAmelCase_ :Tuple = list(l... | 84 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' ,[
['full:README.md', 'dataset_infos.json'],
['empty:README... | 251 | 0 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
... | 85 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
... | 251 | 0 |
"""simple docstring"""
from __future__ import annotations
import bisect
def __lowerCAmelCase (_UpperCamelCase , _UpperCamelCase , _UpperCamelCase = 0 , _UpperCamelCase = -1 ):
if hi < 0:
__lowerCAmelCase : Tuple = len(_UpperCamelCase )
while lo < hi:
__l... | 86 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ... | 251 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig''',
... | 87 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase__( __UpperCamelCase: Union[d... | 251 | 0 |
import requests
__lowerCAmelCase : Any = 'https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='
def a__ ( A_ ):
'''simple docstring'''
__magic_name__ = requests.get(_NEWS_API + bbc_news_api_key ).json()
# each article ... | 88 |
'''simple docstring'''
from itertools import product
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = sides_number
SCREAMING_SNAKE_CASE : str = max_face_number * dic... | 251 | 0 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class __magic... | 89 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Any = 0
SCREAMING_SNAKE_CASE : str = 0
... | 251 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__A = logging.get_logger(__name__)
__A = {
"shi-labs/nat-mini-in1k-224": "https://huggingface.... | 90 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] = [int(__UpperCamelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(__UpperCamelCase ) == 4 and all(0 <... | 251 | 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,
normalize,
rescal... | 91 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"microsoft/git-base": "https://huggingface... | 251 | 0 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
FEATU... | 92 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"toke... | 251 | 0 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
assert x is not None
assert y is not None
lowercase_ : Dict = len(__SCREAMI... | 93 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase_ = [ord(letter)... | 251 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.ut... | 94 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCamelCase_ ... | 251 | 0 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def _A ( SCREAMING_SNAKE_CASE : dict ):
... | 95 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaske... | 251 | 0 |
"""simple docstring"""
def _snake_case ( ):
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(lowercase__ , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
pr... | 96 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _... | 251 | 0 |
'''simple docstring'''
from typing import Any
import numpy as np
def a ( __a ) -> bool:
'''simple docstring'''
return np.array_equal(__a , matrix.conjugate().T )
def a ( __a , __a ) -> Any:
'''simple docstring'''
UpperCamelCase__ :Dict ... | 97 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 251 | 0 |
"""simple docstring"""
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
... | 98 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
... | 251 | 0 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowercase : Union[str, Any... | 99 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
class _a ... | 251 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__magic_name__ = {
"configuration_chinese_clip": [
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ChineseCLIPConfig",
... | 100 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_funnel": ["FUNNEL_PRETRAINED_... | 251 | 0 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCamelCase ( lowerCAmelCase__ = 3 ):
'''simple docstring'''
if isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise TypeError('''number... | 101 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase_ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_a... | 251 | 0 |
"""simple docstring"""
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
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... | 102 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 251 | 0 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str] = logging.get_logger(__name__)
A__ : List[Any] = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingface.co/snap-research/efficientformer-... | 103 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase_ = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from b... | 251 | 0 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCAmelCase__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''S... | 104 |
'''simple docstring'''
from __future__ import annotations
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [True] * limit
SCREAMING_SNAKE_CASE : List[str] = False
SCREAMING_SNAKE_CA... | 251 | 0 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[str] = logging.get_logger(__name__)
a : Dict = {
'''facebook/data2vec-base-960h''': '''https://huggingface.co/facebook/data2vec-audio... | 105 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Optional[Any] ... | 251 | 0 |
"""simple docstring"""
from math import pi
def __SCREAMING_SNAKE_CASE ( A_ , A_ ):
return 2 * pi * radius * (angle / 3_60)
if __name__ == "__main__":
print(arc_length(9_0, 1_0))
| 106 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' ,[
['full:README.md', 'dataset_infos.json'],
['empty:README... | 251 | 0 |
# 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
#
# Unless required by... | 107 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
... | 251 | 0 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin... | 108 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ... | 251 | 0 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from tra... | 109 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase__( __UpperCamelCase: Union[d... | 251 | 0 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class __lowerCamelCase ( tf.keras.layers.Layer ):
'''simple... | 241 |
'''simple docstring'''
from itertools import product
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = sides_number
SCREAMING_SNAKE_CASE : str = max_face_number * dic... | 251 | 0 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class UpperCAmelCase :
def __init__(self : Optional[Any] , snake_case__ : str ) -> int:
'''simple docstring'''
snake_case : List[str] = lis... | 59 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Any = 0
SCREAMING_SNAKE_CASE : str = 0
... | 251 | 0 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def a__ ( A_, A_, A_ ):
'''simple docstring'''
... | 88 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] = [int(__UpperCamelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(__UpperCamelCase ) == 4 and all(0 <... | 251 | 0 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
A__ : int ='''\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL t... | 70 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"microsoft/git-base": "https://huggingface... | 251 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase : List[str] = {
'''configuration_instructblip''': [
'''INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InstructBlipConfig''',
'''InstructBlip... | 18 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"toke... | 251 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
snake_case_ = F'''{sampling_rate}'''
snake_case_ = '1'
snake_case_ = 'f32l... | 8 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase_ = [ord(letter)... | 251 | 0 |
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 303 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCamelCase_ ... | 251 | 0 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
lowerCAmelCase__ = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not... | 104 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaske... | 251 | 0 |
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
__... | 259 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _... | 251 | 0 |
_lowercase: Optional[int] = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
_lowercase: Dict = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def a( A : dict[int, list[int]] , A : int , A : list[bool] ) -> Optional[Any]:
"""si... | 227 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorT... | 251 | 0 |
'''simple docstring'''
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
_UpperCamelCase = {
'''E''': 12.70,
'''T''': 9.06,
'''A''': 8.17,
'''O''': 7.51,
'''I''': 6.97,
'''N''': 6.75,
'''S''': 6.33,
'''H''': 6.09,
'''R'''... | 254 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class _a :
'''simple docstring'''
def __init__( self, A ):
'''simple docstring'''
... | 251 | 0 |
"""simple docstring"""
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization... | 241 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
class _a ... | 251 | 0 |
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCAmelCase ( ... | 59 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase_ = {
"configuration_funnel": ["FUNNEL_PRETRAINED_... | 251 | 0 |
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate... | 88 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase_ = {"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_a... | 251 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : Tuple =logging.get_logger(__name__)
A__ : List[str] ={
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve... | 70 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
... | 251 | 0 |
from typing import Any
def _snake_case ( lowerCAmelCase : list , lowerCAmelCase : list , lowerCAmelCase : dict , lowerCAmelCase : dict , lowerCAmelCase : dict , ):
"""simple docstring"""
_validation(
__UpperCamelCase , __UpperCamelCase ,... | 18 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase_ = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from b... | 251 | 0 |
import sys
from collections import defaultdict
class snake_case_ :
'''simple docstring'''
def __init__( self : Any ) ->List[Any]:
snake_case_ = []
def snake_case__( self : str , _UpperCamelCase : str )... | 8 |
'''simple docstring'''
from __future__ import annotations
def lowercase__( __UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = [True] * limit
SCREAMING_SNAKE_CASE : List[str] = False
SCREAMING_SNAKE_CA... | 251 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowercase_ = """src/transformers"""
# Matches is_xxx_available()
lowercase_ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowercase_ = ... | 303 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowercase__( __UpperCamelCase: np.ndarray ):
"""simple docstring"""
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE : Optional[Any] ... | 251 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCAmelCase__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tok... | 104 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' ,[
['full:README.md', 'dataset_infos.json'],
['empty:README... | 251 | 0 |
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_to... | 259 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase_ = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
... | 251 | 0 |
def a( A : int = 50 ) -> int:
"""simple docstring"""
a = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 227 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class _a ( unittest.TestCase ... | 251 | 0 |
'''simple docstring'''
import sys
import turtle
def lowercase_ ( lowerCAmelCase__ : tuple[float, float] , lowerCAmelCase__ : tuple[float, float] ):
"""simple docstring"""
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowercase_ ( ... | 254 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowercase__( __UpperCamelCase: Union[d... | 251 | 0 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPip... | 241 |
'''simple docstring'''
from itertools import product
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Tuple = sides_number
SCREAMING_SNAKE_CASE : str = max_face_number * dic... | 251 | 0 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"""speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json""",
# See all... | 59 |
'''simple docstring'''
class _a :
'''simple docstring'''
def __init__( self ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : Any = 0
SCREAMING_SNAKE_CASE : str = 0
... | 251 | 0 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class UpperCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
... | 88 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Optional[int] = [int(__UpperCamelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(__UpperCamelCase ) == 4 and all(0 <... | 251 | 0 |
'''simple docstring'''
A__ : Any ='''\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.gi... | 70 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"microsoft/git-base": "https://huggingface... | 251 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTester
from ...t... | 18 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCamelCase_ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"toke... | 251 | 0 |
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
snake_case_ = ''
for i in table:
res += inp[i - 1]
return res
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ ):
return data[1:] + data[0]
def __SCREAMIN... | 8 |
'''simple docstring'''
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
UpperCamelCase_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
UpperCamelCase_ = [ord(letter)... | 251 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, to... | 303 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
UpperCamelCase_ ... | 251 | 0 |
'''simple docstring'''
import math
def _A ( A__ ):
"""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
return False
# All pri... | 104 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
UpperCamelCase_ = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaske... | 251 | 0 |
def _A ( SCREAMING_SNAKE_CASE__ : int = 10 , SCREAMING_SNAKE_CASE__ : int = 22 ):
UpperCamelCase :Dict = range(1 , __UpperCamelCase )
UpperCamelCase :str = range(1 , __UpperCamelCase )
return sum(
1 for power in powers fo... | 259 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class _... | 251 | 0 |
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