code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""bilinear""": PIL.Image... | 705 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, 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,
... | 706 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 0 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
A__ : str= (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
A__ : list[int]= [ord(letter) for letter in s... | 707 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteSchedu... | 708 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org... | 20 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
import torch
from ..models.auto import AutoModelForVisualQuestionAnswering, AutoProcessor
from ..utils import requires_backends
from .base import PipelineTool
if TYPE_CHECKING:
from PIL import Image
class __lowerCamelCa... | 709 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 0 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> "list[int]":
"""simple docstring"""
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
UpperCamelCase__ = [0] * (upper_limit + 1)
# ... | 710 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
A__= get_tests_dir("""... | 711 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepar... | 712 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A__ : List[str]= {
"""configuration_roformer""": ["""ROFORMER_PRETRAINED_C... | 713 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
... | 714 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 20 | 0 |
"""simple docstring"""
from PIL import Image
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Image:
"""simple docstring"""
UpperCamelCase__ , UpperCamelCase__ = image.size
UpperCamelCase__ = 0
UpperCamelCase__ = image.load()
fo... | 715 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 | 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__":
A__ : Dict= """%20""".join(argv[1:]) if len(argv) > 1 else quote(... | 716 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 | 0 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) and number_of_steps > 0
), F'number_of_steps needs to be positive integer, your input {number_of_st... | 717 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : str= logging.get_logger(__... | 20 | 0 |
"""simple docstring"""
class __lowerCamelCase :
def __init__( self , snake_case_ , snake_case_ ) -> Union[str, Any]:
UpperCamelCase__ = name
UpperCamelCase__ = val
def __str__( self ) -> Any:
... | 718 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_re... | 20 | 0 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLIComman... | 719 |
"""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_mode... | 20 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first colu... | 720 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
A__ : Optional[Any]= TypeVar("""T""")
A__ : Optional[Any]= TypeVar("""U""")
class __lowerCamelCase ( Generic[T, U] ):
def __init__( ... | 721 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
... | 20 | 0 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('both inputs must be positive integers' )
UpperCamelCase__ = str(bin(... | 700 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00_00_00 ) -> int:
"""simple docstring"""
UpperCamelCase__ = set()
UpperCamelCase__ = int((limit - 24) ** (1 / 2) )
UpperCamelCase__ = set(range(3 , prime... | 20 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = int(number**0.5 )
retur... | 701 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.t... | 20 | 0 |
"""simple docstring"""
A__ : dict[str, float]= {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.6_0_9_3_4_4,
"knot": 1.8_5_2,
}
A__ : dict[str, float]= {
"km/h": 1.0,
"m/s": 0.2_7_7_7_7_7_7_7_8,
"mph": 0.6_2_1_3_7_1_1_9_2,
"knot": 0.5_3_9_9_5_6_8_0_3,
}
... | 702 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = len(SCREAMING_SNAKE_CASE )
for i in range(SCREAMING_SNAKE_CASE ):
for j in range(i + 1 , SCREAMING_SNAKE_CASE ):
... | 20 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[Any]= logging.get_logger(__name__)
A__ : Any= {
"""vinvino02/glpn-kitti""": """https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json""",
#... | 703 |
"""simple docstring"""
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse("""9.1.0"""):
A__ : str= {
"""linear""": PIL.Image.Resampling.BILINEAR,
"""... | 20 | 0 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not numbers:
return 0
if not isinstance(SCREAMING_SNAKE_CASE , (list, tuple) ) or not all(
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CA... | 704 |
"""simple docstring"""
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_ut... | 20 | 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():
fro... | 705 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
A__ : Any= TypeVar("""T""")
class __lowerCamelCase ( Generic[T] ):
def __init__( self , snake_case_ ) -> None:
UpperCamelCase__ = data
... | 20 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
... | 706 |
"""simple docstring"""
A__ : Tuple= """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
UpperCamelCase__ = {'*': op.mul, '/': op.truediv, '+': o... | 20 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
impo... | 707 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
A__ : Any= """src/diffusers"""
# Matches is_xxx_available()
A__ : Tuple= re.c... | 20 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[Any]= logging.get_logger(__name__)
A__ : List[str]= {
"""google/pix2struct-textcaps-base""": (
""... | 708 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org... | 20 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
UpperCamelCase__ = 2
UpperCamelCase__ = []
while i * i <= n:
if n % i:
... | 709 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str]= logging.get_logger(__name__)
class __lowerCamelCase ( _a ):
a : Optional[int] ="""timm_backbone"""
def __init__( self , snak... | 20 | 0 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentenc... | 710 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimensio... | 20 | 0 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 711 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_mo... | 20 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common impo... | 712 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 1_00_00_00 , SCREAMING_SNAKE_CASE = 10 ) -> int:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SN... | 20 | 0 |
import argparse
from collections import defaultdict
import yaml
A__ : Optional[Any]= """docs/source/en/_toctree.yml"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Tuple:
"""simple docstring"""
UpperCamelCase__ = defaultdict(SCREAMING_SNAKE_CA... | 713 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_... | 20 | 0 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 714 |
"""simple docstring"""
import sys
from collections import defaultdict
class __lowerCamelCase :
def __init__( self ) -> Tuple:
UpperCamelCase__ = []
def SCREAMING_SNAKE_CASE__ ( self , snake_case_ ) -> List[str]:
... | 20 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 715 |
"""simple docstring"""
from copy import deepcopy
class __lowerCamelCase :
def __init__( self , snake_case_ = None , snake_case_ = None ) -> None:
if arr is None and size is not None:
UpperCamelCase__ = size
UpperCam... | 20 | 0 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
A__ : List[str]= None
try:
import msvcrt
except ImportError:
A__ : Dict= None
try:
import fcntl
except ImportError:
A__ : Dict= No... | 716 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A__ : Union[str, Any]= logging.getLogger()
@unitte... | 20 | 0 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
"""s... | 717 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__ : str= logging.get_logger(__... | 20 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokeniz... | 718 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_re... | 20 | 0 |
"""simple docstring"""
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTester... | 719 |
"""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_mode... | 20 | 0 |
"""simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dyn... | 720 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def lowerCAmelCase_( SCRE... | 20 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__ : List[str]= lo... | 721 |
"""simple docstring"""
def lowerCAmelCase_( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
UpperCamelCase__ = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def lowerCAmelCase_( SCREAMING_SNAKE_CASE = 50_00 ) -> int:
... | 20 | 0 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithN... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 21 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase : Optional[Any] = {
'''configuration_ro... | 21 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCA... | 21 | 1 |
"""simple docstring"""
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly ... | 21 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_... | 21 | 1 |
"""simple docstring"""
import cmath
import math
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float , __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
snake_case_ : ... | 21 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 21 | 1 |
"""simple docstring"""
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import da... | 21 |
"""simple docstring"""
import math
import tensorflow as tf
from packaging import version
def __lowerCAmelCase ( __UpperCamelCase : List[Any] ):
'''simple docstring'''
snake_case_ : int = tf.convert_to_tensor(__UpperCamelCase )
sna... | 21 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
class _lowerCAmelCase ( ... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
snake_case_ : int = [0] * len(__UpperCamelCase )
snake_case_ : List[str] = []
snake_case_ : Any = [1] *... | 21 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as t... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
snake_case_ : Any = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
... | 21 | 1 |
"""simple docstring"""
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
__lowerCAmelCase : Optional[int] = 4
__lower... | 21 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 21 | 1 |
"""simple docstring"""
from __future__ import annotations
def __lowerCAmelCase ( __UpperCamelCase : list[float] , __UpperCamelCase : Any ):
'''simple docstring'''
print(F'Vertex\tShortest Distance from vertex {src}' )
for i, d in en... | 21 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot... | 21 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 21 |
"""simple docstring"""
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
... | 21 | 1 |
"""simple docstring"""
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
... | 21 |
"""simple docstring"""
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowerCAmelCase : List[str] = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for Gen... | 21 | 1 |
"""simple docstring"""
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : Tuple ... | 21 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attentio... | 21 | 1 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase ... | 21 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__lowerCAmelCase : Optional[int] = argparse.ArgumentParser('''Stable Diffusion script with inte... | 21 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class _lowerCAmelCase :
"""simple ... | 21 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class ... | 21 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
_lowerCamelCase = (IPNDMSc... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : bool = False ):
'''simple docstring'''
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n ... | 21 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase : Optional[Any] = {
'''configuration_wa... | 21 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
def is_in_circle(__UpperCamelCase ... | 21 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
__lowerCAmelCase : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
__lowerCAmelCase ... | 21 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
def __lowerCAmelCase ( __UpperCamelCas... | 21 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
_lowerCamelCase = ['''sentencepiece''']
def __init__( self , *_... | 21 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __lowerCAmelCase ( __UpperCamelCase :... | 21 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
__lowerCAmelCase : List[Any] = {
'''configu... | 21 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTes... | 21 | 1 |
"""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 ... | 21 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_ava... | 21 | 1 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWrit... | 21 |
"""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 ... | 21 | 1 |
"""simple docstring"""
from typing import Any
def __lowerCAmelCase ( __UpperCamelCase : list , __UpperCamelCase : list , __UpperCamelCase : dict , __UpperCamelCase : dict , __UpperCamelCase : dict , ):
'''simple docstring'''
... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
snake_case_ ... | 21 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformer... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 21 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCAmelCase : List[str] = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLM... | 21 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCA... | 21 | 1 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
__lowerCAmelCase : Tuple = logging.get_logger(__name__)
def __lowerCAmelCase ... | 21 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_... | 21 | 1 |
"""simple docstring"""
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCL... | 21 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 21 | 1 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, log... | 21 |
"""simple docstring"""
import math
import tensorflow as tf
from packaging import version
def __lowerCAmelCase ( __UpperCamelCase : List[Any] ):
'''simple docstring'''
snake_case_ : int = tf.convert_to_tensor(__UpperCamelCase )
sna... | 21 | 1 |
"""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
__lowerCAmelCase : List[Any] = datasets.utils.logg... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
snake_case_ : int = [0] * len(__UpperCamelCase )
snake_case_ : List[str] = []
snake_case_ : Any = [1] *... | 21 | 1 |
"""simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
class _low... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
snake_case_ : Any = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
... | 21 | 1 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, requi... | 21 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 21 | 1 |
"""simple docstring"""
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self , _lowercase = "" , _lowercase = False ) -> None:
'''simple docstring'''
snake_case_ : dict[str, RadixNode] ... | 21 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot... | 21 | 1 |
"""simple docstring"""
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
fr... | 21 |
"""simple docstring"""
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
... | 21 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
snake_case_ , snake_case_ : str ... | 21 |
"""simple docstring"""
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowerCAmelCase : List[str] = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for Gen... | 21 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vi... | 21 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attentio... | 21 | 1 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def __lowerCAmelCase ( __UpperCamelCase : Any="ro" , __UpperCamelCase : Union[str, Any]="en" , __UpperCamelCase : Union[str, Any]="wmt16" , __UpperCamelCase : int=None... | 21 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__lowerCAmelCase : Optional[int] = argparse.ArgumentParser('''Stable Diffusion script with inte... | 21 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_ava... | 21 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class ... | 21 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[str] = logging.get_logger(__name__)
__low... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : bool = False ):
'''simple docstring'''
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n ... | 21 | 1 |
"""simple docstring"""
import argparse
import collections
import os
import re
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_table.py
__lowerCAmelCase... | 21 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
def is_in_circle(__UpperCamelCase ... | 21 | 1 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCAmelCase ( SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
_lowe... | 21 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
def __lowerCAmelCase ( __UpperCamelCas... | 21 | 1 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def __lowerCAmelCase ( *__UpperCamelCase : Optional[Any] ):
'''simple docstring'''
if not isinstance(__UpperCam... | 21 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __lowerCAmelCase ( __UpperCamelCase :... | 21 | 1 |
"""simple docstring"""
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaI... | 21 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTes... | 21 | 1 |
"""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.L... | 21 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_ava... | 21 | 1 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int = 1_0_0_0 ):
'''simple docstring'''
return sum(e for e in range(3 , __UpperCamelCase ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F'''{solution(... | 21 |
"""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 ... | 21 | 1 |
"""simple docstring"""
from functools import reduce
__lowerCAmelCase : Optional[Any] = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
snake_case_ ... | 21 | 1 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Im... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 21 | 1 |
"""simple docstring"""
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
... | 21 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCA... | 21 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare... | 21 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_... | 21 | 1 |
"""simple docstring"""
__lowerCAmelCase : Union[str, Any] = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def __lowerCAmelCase ( __UpperCamelCase : ... | 21 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 21 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase : str = logging.get_logger(__name__)
__lowerCA... | 21 |
"""simple docstring"""
import math
import tensorflow as tf
from packaging import version
def __lowerCAmelCase ( __UpperCamelCase : List[Any] ):
'''simple docstring'''
snake_case_ : int = tf.convert_to_tensor(__UpperCamelCase )
sna... | 21 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from typing import Any
class _lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
sna... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : Union[str, Any] ):
'''simple docstring'''
snake_case_ : int = [0] * len(__UpperCamelCase )
snake_case_ : List[str] = []
snake_case_ : Any = [1] *... | 21 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPa... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
snake_case_ : Any = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
... | 21 | 1 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float , __UpperCamelCase : float , __UpperCamelCase : float , __UpperCamelCase : float , ):
'''simple docstring'''
sn... | 21 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_al... | 21 | 1 |
"""simple docstring"""
__lowerCAmelCase : Any = range(2, 20 + 1)
__lowerCAmelCase : Optional[int] = [10**k for k in range(ks[-1] + 1)]
__lowerCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def __lowerCAmelCase ( ... | 21 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot... | 21 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
class _lowerCAmelCase ( SCREAMING_SNAKE_CASE__ ):
... | 21 |
"""simple docstring"""
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
... | 21 | 1 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
__lowerCAmelCase : Any = {
'''RUCAIBox/mvp''': '''... | 21 |
"""simple docstring"""
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__lowerCAmelCase : List[str] = '''\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for Gen... | 21 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
__lowerC... | 21 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attentio... | 21 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
__lowerCAmelCase : int = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full BertForMaskedL... | 21 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__lowerCAmelCase : Optional[int] = argparse.ArgumentParser('''Stable Diffusion script with inte... | 21 | 1 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def __lowerCAmelCase ( __UpperCamelCase : list , __UpperCamelCase : list , __... | 21 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class ... | 21 | 1 |
"""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 c... | 21 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : bool = False ):
'''simple docstring'''
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n ... | 21 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
__lowerCAmelCase : Optional[int] = {
'''facebook/nllb-moe-54B''': '''... | 21 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
def is_in_circle(__UpperCamelCase ... | 21 | 1 |
"""simple docstring"""
import math
def __lowerCAmelCase ( __UpperCamelCase : Optional[int] , __UpperCamelCase : List[str] ):
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.... | 21 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
def __lowerCAmelCase ( __UpperCamelCas... | 21 | 1 |
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