code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
def __lowercase ( snake_case ):
"""simple docstring"""
__magic_name__ :int = len(snake_case )
# We need to create solution object to save path.
__magic_name__ :List[str] = [[0 for _ in range(snake_case )] for _ in range(sn... | 0 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 0 |
import math
def _A ( _lowercase ) -> bool:
"""simple docstring"""
return math.sqrt(_lowercase ) * math.sqrt(_lowercase ) == num
def _A ( _lowercase ) -> bool:
"""simple docstring"""
__UpperCamelCase = 0
__UpperCamelCase = ... | 1 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
... | 2 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 0 |
'''simple docstring'''
def A_( A : int):
if not isinstance(A , A):
UpperCamelCase = f'''Input value of [number={number}] must be an integer'''
raise TypeError(A)
if number < 0:
return False
UpperCamelCase = number... | 3 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 632 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int ):
return str(_UpperCAmelCase ) == str(_UpperCAmelCase )[::-1]
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int ):
return int(_UpperCAmelCase ) + int(str(_UpperCAmelCase )[::-1] )
def _SCREAMING_SNAKE... | 4 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 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,
rescale,
re... | 5 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 0 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
_lowerCamelCase = pytest.mark.integration
@pytest.mark.parametrize("""path""" , ["""paw... | 6 |
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 Image
from transformers import (
AutoTokeni... | 632 | 0 |
"""simple docstring"""
def _snake_case ( _snake_case : int = 1 , _snake_case : int = 10_00 ) -> int:
'''simple docstring'''
_A = 1
_A = 0
for divide_by_number in range(_snake_case , digit + 1 ):
_A = []
... | 7 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 0 |
'''simple docstring'''
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class SCREAMING_SNAKE_CASE (a__ ):... | 8 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageP... | 9 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase_ ( __lowercase ):
UpperCAmelCase = ["image_processor", "tokenizer"]
UpperCAmelCase = "AutoImageProcessor"
UpperCAmelCase = "AutoTokeni... | 10 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 0 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __A ( nn.Module ):
'''simple docstring'''
def __init__(self , A = 16 , A = 88 , A = None , A = 1 , A = 0.0 ... | 11 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 0 |
def UpperCamelCase ( lowercase_ , lowercase_ ) -> bool:
'''simple docstring'''
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 12 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 0 |
'''simple docstring'''
A__ : List[Any] = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager impor... | 13 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 0 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
a__ = datasets.logging.get_logger(__name__)
a__ = '''\
@InProceedings{moosavi2019minimum,
author = {... | 14 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 0 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@requi... | 15 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 0 |
__A : List[str] = range(2, 2_0 + 1)
__A : List[str] = [1_0**k for k in range(ks[-1] + 1)]
__A : dict[int, dict[int, list[list[int]]]] = {}
def __a ( A__ : List[Any] , A__ : Union[str, Any] , A__ : List[Any] , A__ : Any ):
... | 16 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
from u... | 17 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 0 |
'''simple docstring'''
from collections.abc import Generator
from math import sin
def __a(SCREAMING_SNAKE_CASE_ : bytes ):
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE_ ) != 32:
raise ValueError("Input must be of length 32" )
_lowerCAmelCase ... | 18 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 0 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def lowerCamelCase__ ( __snake_case, __snake_case ) -> np.ndarray:
"""simple docstring"""
_UpperCamelCase = math.sqrt(__snake_case )
_UpperCamelCase... | 19 |
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,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_token... | 20 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 0 |
from collections.abc import Sequence
def lowerCAmelCase_ ( lowerCamelCase = None ):
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__magic_name__ : str =nums[0]
for i in range(1 , len(lowerCamelCase ) ... | 21 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 0 |
'''simple docstring'''
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If u... | 22 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 0 |
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCToke... | 23 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from... | 24 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( _a , _a = None , _a = None):
if start is None:
SCREAMING_SNAKE_CASE : List[str] = 0
if end is None:
SCREAMING_SNAKE_CASE : List[Any] = len(_a) - 1
if start >= end:
return
SCREAMING_SNAKE_CASE... | 25 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 632 | 0 |
'''simple docstring'''
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _A ( __lowercase ):
def __init__( self : str , __magic_name__ : Optional[int] , __magic_n... | 26 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 0 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise ValueError('check_bouncy() accepts only integer arguments' )
_A = str(_S... | 27 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 0 |
'''simple docstring'''
UpperCamelCase_ = [
"DownloadConfig",
"DownloadManager",
"DownloadMode",
"StreamingDownloadManager",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import ... | 28 |
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 Image
from transformers import (
AutoTokeni... | 632 | 0 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
"""snap-research/efficientformer-l1-300""": (
"""https://huggingface.co/snap-research/efficientformer-l1... | 29 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 0 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
__a = logging.get_logger(__name__)
class __a( _a ):
"""simple docstring"""
def __init__( self ,*_SCREAMING_SNAKE_CASE ,**_SCREAMING_SNAKE_CASE ) -> None:
... | 30 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 0 |
def UpperCAmelCase_ ( __UpperCAmelCase : int , __UpperCAmelCase : float , __UpperCAmelCase : float ) -> float:
return round(float(moles / volume ) * nfactor )
def UpperCAmelCase_ ( __UpperCAmelCase : float , __UpperCAmelCase : ... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 0 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformers.m... | 32 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 0 |
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> int:
def count_of_possible_combinations(__lowerCAmelCase ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possible_combinations(targe... | 33 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 0 |
"""simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_lo... | 34 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 0 |
from cva import destroyAllWindows, imread, imshow, waitKey
def a ( A__ ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ : Any = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for... | 35 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 0 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class _A ( ctypes.Structure ):
'''simple docstring'''
__lowerCamelCase : Union[str, Any] = [('''size''', ctypes.c_int... | 36 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Any = logging.get_logger(__name__)
UpperCamelCase : Union[str, Any] = {
"""facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/config.json""",
... | 37 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( __magic_name__ : str , __magic_name__ : list[str] ) -> str:
'''simple docstring'''
snake_case__ : List[Any] = """"""
for word_or_phrase in separated:
if not isinstance(__magic_name__ , __magic_nam... | 38 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 0 |
import numpy as np
from PIL import Image
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
snake_case_ = np.array(SCREAMING_SNAKE_CASE__ )
if arr.shape[0] != arr.shape[1]:
raise ValueError('''The i... | 39 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
'''facebook/convnextv2-tiny-1k-224''': '''https... | 40 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 0 |
'''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavin... | 41 |
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,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 0 |
'''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 model through reduction of a normal pre-trained model, but keeping the
# ful... | 42 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from .... | 43 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase__ ( A ):
lowerCAmelCase_ = (PNDMScheduler,)
lowerCAmelCase_ = (('num_inference_steps', 50),)
def lowe... | 44 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 0 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def A ( lowercase__ : Optional[Any] , lowercase__ : str=7 ) -> List[str]:
UpperCamelCase__ :List[Any] = None
if token is not None:
UpperCamelCase__ :Optional[int]... | 45 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 0 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 0 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
SCREAMING_SNAKE_CASE__ = logging.getLogger(__name__)
def UpperCAmelCase__ ( ):
__a : Union[str, Any] = argparse.ArgumentPars... | 47 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 632 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_c... | 48 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_availabl... | 49 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 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 ... | 50 |
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 Image
from transformers import (
AutoTokeni... | 632 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class lowerCAmelCase__ :
'''simple docstring'''
_lowerCamelCase =42
_lowerCamelCase =42
c... | 51 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_ba... | 52 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 0 |
# Function to print upper half of diamond (pyramid)
def a_ ( lowerCAmelCase_ : Optional[int] ):
for i in range(0, lowerCAmelCase_ ):
for _ in range(0, n - i - 1 ): # printing spaces
print(' ', end='' )
for _ in range(0, i + 1 ... | 53 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 0 |
from scipy.stats import spearmanr
import datasets
__lowercase : str ="""
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive correl... | 54 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 55 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Any = logging.get_logger(__name__)
_a : Optional[Any] = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
class _l... | 56 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 0 |
from collections.abc import Sequence
from queue import Queue
class _lowerCAmelCase:
"""simple docstring"""
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase=None , _lowerC... | 57 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def __lowerCAmelCase ( __UpperCamelCase : List[Any] ):
'''simple docstring'''
if ... | 58 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
),
}
... | 59 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 0 |
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_t... | 60 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 0 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCamelCase ( ... | 61 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 0 |
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
if bit_count < 0:
raise ValueError("The given input must be positive" )
# get the generated string sequence
SCREAMING_SNAKE_CASE : Optional[int] = gray_code_sequence_string(lowercase )
#
# c... | 62 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 0 |
def lowerCamelCase__ ( __lowerCamelCase : int ):
__UpperCAmelCase : List[str] = [1]
__UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase : Any = 0, 0, 0
__UpperCAmelCase : Any = ugly_nums[ia] * 2
__UpperCAmelCase : O... | 63 |
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,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 0 |
def A__ ( snake_case_ : str ):
SCREAMING_SNAKE_CASE__: int= hex_num.strip()
if not hex_num:
raise ValueError('''No value was passed to the function''' )
SCREAMING_SNAKE_CASE__: Optional[Any]= hex_num[0] == '''-'''
if is_negative:
SCREAMING_SNAKE_CASE__: Optional[int]= hex_num[1:]
tr... | 64 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class __lowercase :
def __init__( self : int ,A : int ):
'''simple docstring'''
UpperCAmelCase__ : List[str] = num_of_nodes
UpperCA... | 65 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
... | 66 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def SCREAMING_SNAKE_CASE__ ( snake_case__ :Tuple ) -> Tuple:
# This defines a "chinese character" as anything in the CJK Unicode block:
... | 67 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 0 |
import re
import string
import numpy as np
import datasets
__A = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
__A = "\nArgs:\n predictions: List of predicted texts.\n references: Li... | 68 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 0 |
'''simple docstring'''
a : Union[str, Any] = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
a : Tuple = ['''a''', '''b''', '''c''', '''d''', '''e''']
def __UpperCAmelCase ( _UpperCAmelCase : Optional[int] ,... | 69 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 632 | 0 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB... | 70 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 0 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : int | float | str ) -> tuple[int, int]:
"""simple docstring"""
try:
UpperCAmelCase_ : int = float(_SCREAMING_SNAKE_CASE )
except ValueError:
raise ValueError("Please enter a valid numbe... | 71 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase ( lowercase_ : list[int | str] ) -> None:
'''simple docstring'''
create_state_space_tree(lowercase_ , [] , 0 , [0 for i in range(len(lowercase_ ) )] )
def UpperCamelCase ( ... | 72 |
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 Image
from transformers import (
AutoTokeni... | 632 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : List[str] ... | 73 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI... | 74 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 0 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ) -> str:
UpperCAmelCase__ : list[list[str]] = [[] for _ in range(lowerCAmelCase__ )]
UpperCAmelCase__ : Union[str, Any] = key - 1
if key <= 0:
raise Val... | 75 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 0 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers im... | 76 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 0 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A = get_logger(__name__)
A = r"""
Args:
input_ids (`jnp.ndarray` of shape `(batch_size, sequence_le... | 77 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_: Optional[Any] ={
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CON... | 78 |
from manim import *
class _UpperCAmelCase ( A__ ):
def snake_case_ ( self):
A__ = Rectangle(height=0.5 , width=0.5)
A__ = Rectangle(height=0.2_5 , width=0.2_5)
A__ = Rectangle(height=0.4_6 , width=0.4_6).set_... | 632 | 0 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArgume... | 79 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
"iou_prediction_head.layers.... | 632 | 0 |
from __future__ import annotations
from collections.abc import MutableSequence
class __UpperCamelCase :
def __init__( self : Optional[Any] , _lowerCAmelCase : int , _lowerCAmelCase : MutableSequence[float] ) -> None:
"""simple docstring"""
... | 80 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
class _UpperCAmelCase ( A__ ):
UpperCamelCase__ = '''timm_backbone'''
def __init__( self , a__=None , a__=3 , a__=True , ... | 632 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
)
from tr... | 81 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_mctct": ["MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP", "MCTCTConfig"],
"feature_extraction_mctct": ["MCTCTFeatureExtractor"],
"processing_mctct": ["MCTCTP... | 632 | 0 |
"""simple docstring"""
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
UpperCAmelCase_ = f"""{sampling_rate}"""
UpperCAmelCase_ = ... | 82 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to h... | 632 | 0 |
"""simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
lowerCAmelCase__ = '''<<<<<<< This should probably be modified because it mentions: '... | 83 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resol... | 632 | 0 |
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
if not isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = F'''Input value of [number={number}] must be an integer'''
raise TypeError(__SCREAMING_SNAKE_CASE )
if number < 1:
lowercase = F'''I... | 84 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _UpperCAm... | 632 | 0 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
SCREAMING_SNAKE_CASE__ : Any = logging.getLogger(__name__)
def _a ( ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Optiona... | 85 |
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,
MobileNetVaImageProcessor,
load_tf_weights_in_mobilenet_va,... | 632 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokeniz... | 86 |
import re
def lowerCAmelCase__ ( UpperCamelCase_ : str )-> str:
if len(re.findall('''[ATCG]''' , UpperCamelCase_ ) ) != len(UpperCamelCase_ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(dna.maketrans('''ATCG''' , '... | 632 | 0 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_switc... | 87 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
"configuration_layoutlmv2": ["LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP", "LayoutLMv2Config"],
"p... | 632 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""facebook/wav2vec2-base-960h""": """https://huggingface.co/facebook/wav2vec... | 88 |
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase_ : dict , UpperCamelCase_ : str )-> set[str]:
A__ , A__ = set(UpperCamelCase_ ), [start]
while stack:
A__ = stack.pop()
explored.add(Upper... | 632 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
loggin... | 89 |
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, require_multi_gpu
from... | 632 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCAmelCase = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 90 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
ge... | 632 | 0 |
"""simple docstring"""
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr,... | 91 |
from __future__ import annotations
import unittest
from transformers import DebertaVaConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 632 | 0 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def _lowerCAmelCase ( __m... | 92 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, ... | 632 | 0 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__na... | 93 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 632 | 0 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def lowercase_ ( __A : str ) -> List[Any]:
"""simple docstring"""
def decorator(__A : Tuple ):
lowercase : List[Any] =getattr(__A , '''handle_... | 94 |
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 Image
from transformers import (
AutoTokeni... | 632 | 0 |
"""simple docstring"""
def snake_case ( A__ ,A__ ,A__ ,A__ ):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
UpperCAmelCase_ : Optional[int] = mf_knapsack(i - 1 ,A__ ,A__ ,A__ )
else:
UpperCAmelCa... | 95 |
_lowercase = [0, 2, 4, 6, 8]
_lowercase = [1, 3, 5, 7, 9]
def lowerCAmelCase__ ( UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : list[int] , UpperCamelCase_ : int )-> int:
if remaining_length == 0:
... | 632 | 0 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureEx... | 96 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowercase = "2.13.1"
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("3.7"):
raise ImportWarning(
... | 632 | 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,
... | 97 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline,
UNetaDCon... | 632 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.ut... | 98 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> int:
A__ = 0
while number > 0:
... | 632 | 0 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils imp... | 99 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor, r... | 632 | 0 |
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