code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import re
import subprocess
import sys
__magic_name__ : int = subprocess.check_output('''git merge-base main HEAD'''.split()).decode('''utf-8''')
__magic_name__ : Any = subprocess.check_output(F'git diff --name-only {fork_point_sha}'.split()).decode('''utf-8''').spl... | 280 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import requ... | 224 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
snake_case_ : List[str] = {
"""configuration_trocr""": ["""TROCR_PRETRAIN... | 292 |
"""simple docstring"""
def lowercase_ ( _lowercase : list , _lowercase : int , _lowercase : int = 0 , _lowercase : int = 0 ):
'''simple docstring'''
UpperCAmelCase : Tuple = right or len(_lowercase ) - 1
if le... | 292 | 1 |
'''simple docstring'''
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 (
AutoPro... | 5 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_ava... | 512 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.se... | 703 |
'''simple docstring'''
# Copyright 2021 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/licenses/LICENSE-2.0
#
... | 691 | 0 |
'''simple docstring'''
from __future__ import annotations
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self : Dict , __UpperCAmelCase : list[list[int]] ):
'''simple docstring'''
_A = TypeError(
"M... | 330 |
'''simple docstring'''
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
lowerCamelCase_ = {
'''sample_size''': 32,
'''in_channels''': 3,
'''out_channels''': 3,
'''layers_per_block'''... | 330 | 1 |
'''simple docstring'''
import pprint
import requests
__UpperCamelCase : List[str] = "https://zenquotes.io/api"
def __UpperCAmelCase ( ) -> Tuple:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def __UpperCAmelCase ( ) -... | 705 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Tuple = {
"""configuration_blip_2""": [
"""BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 270 | 0 |
from __future__ import annotations
import math
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : Dict , a : int ) -> None:
"""simple docstring"""
SCREAMING_SNAKE_CASE : Dict = size
# approximate the overall size of s... | 25 |
# Copyright 2021 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/licenses/LICENSE-2.0
#
# Unless required by ap... | 68 | 0 |
"""simple docstring"""
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def UpperCamelCase ( _A , _A , _A , _A ) -> Optional[int]:
lowercase : List[Any] = {
"""en""": """Machine learning is great, isn't ... | 348 |
"""simple docstring"""
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap... | 348 | 1 |
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
IMAGENET_STANDARD_MEA... | 243 |
import itertools
import math
def lowerCAmelCase__( lowercase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
re... | 243 | 1 |
"""simple docstring"""
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_lo... | 509 |
"""simple docstring"""
def A_ ( UpperCAmelCase__ , UpperCAmelCase__ ) -> float:
if discount_rate < 0:
raise ValueError('Discount rate cannot be negative' )
if not cash_flows:
raise ValueError('Cash flows list cannot be empty' )
a : List[str... | 509 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Optional[int] = logging.get_logger(__name__)
_UpperCamelCase : List[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/mark... | 284 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy a... | 284 | 1 |
"""simple docstring"""
def snake_case ( UpperCamelCase__ : int , UpperCamelCase__ : int ) -> int:
return int((input_a, input_a).count(0 ) != 0 )
def snake_case ( ) -> None:
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0... | 42 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from... | 42 | 1 |
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , lowercase_ , lowercase_ ) -> np.ndarray:
"""simple docstring"""
A__ = ... | 87 |
def __SCREAMING_SNAKE_CASE ( lowerCAmelCase: int = 100_0000 ) -> int:
_UpperCAmelCase : str = set(range(3 , lowerCAmelCase , 2 ) )
primes.add(2 )
for p in range(3 , lowerCAmelCase , 2 ):
if p not in primes:
continue
primes.diffe... | 300 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : str = 100_0000 ) ->Optional[int]:
'''simple docstring'''
a : Optional[int] = limit + 1
a : Dict = [0] * limit
for first_term in range(1 , _lowercase ):
f... | 708 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __UpperCamelCase ( unittest.TestCase ):
def __a ( self ) -> Optional[Any]:
a : Optional[int] = [
... | 31 | 0 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDim... | 195 |
'''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 BatchEncoding, PreTrainedTokenizer
from ...utils import logging
snake_case_ : Union[str, An... | 195 | 1 |
from random import randint, random
def UpperCamelCase_ ( __a , __a , __a , __a = False , __a = False , __a = 5 , ) -> list:
a__ : Optional[Any] = [[-1] * number_of_cells] # Create a highway without any car
a__ : List[Any... | 702 |
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..utils.dummy_pt_objects... | 151 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase_ = logging.get_logger(__name__)
def lowerCAmelCase (__A):
"""simple docstring"""
... | 11 | """simple docstring"""
def lowerCAmelCase_ (_SCREAMING_SNAKE_CASE :str ) -> int:
assert column_title.isupper()
a_ : int = 0
a_ : Tuple = len(_SCREAMING_SNAKE_CASE ) - 1
a_ : Union[str, Any] = 0
while index >= 0:
... | 473 | 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 TokenizerTesterMixin
_UpperCamelC... | 721 |
'''simple docstring'''
# Copyright 2023 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/l... | 211 | 0 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def a__ ( snake_case , snake_case ):
"""simple docstring"""
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(snake_case , snake_case ) ) ... | 74 | 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,
... | 544 | 0 |
def snake_case_ (__A : int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
try:
__lowerCAmelCase : Dict = int(__A )
except (TypeError, ValueError):
raise TypeError("""Parameter n must be int or castable to int.""" )
if n <= 0:
raise ValueError("""Parameter n ... | 218 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( a_ ):
"""simple docstring... | 218 | 1 |
'''simple docstring'''
import math
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : int , lowerCAmelCase__ : Dict=0 ): # a graph with Node 0,1,...,N-1
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[int] = ... | 578 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_... | 673 | 0 |
from math import factorial
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Optional[Any] , _lowerCAmelCase : Any , _lowerCAmelCase : List[str] ):
__snake_case : Optional[int] = real
if isinstance(_lowerCAmelCase , _lowerCAme... | 713 | from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..... | 390 | 0 |
import numpy as np
UpperCamelCase = [
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class lowerCAmelCase_ :
def __init__( self ):
_lowercase : Any ... | 66 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> List[An... | 66 | 1 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_test,
... | 103 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
req... | 103 | 1 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowercase ( A ):
__magic_name__ : Union[str, Any] = (IPNDMScheduler,)
__magic_name__ : Optional[Any] = ((... | 141 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
requ... | 141 | 1 |
import argparse
from collections import defaultdict
def lowercase ( _a ,_a ,_a ,_a ,_a ) -> Union[str, Any]:
UpperCAmelCase_: Any = f"{file}_{class_name}_{test_name}"
done_test[_id] += 1
with open(_a ,"r" ) as f:
UpperCAmelCase_: Union[s... | 709 |
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, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils import... | 306 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ : Dict = logging.get_logger(__n... | 33 | """simple docstring"""
SCREAMING_SNAKE_CASE__ : Optional[Any] ={
'a': 'AAAAA',
'b': 'AAAAB',
'c': 'AAABA',
'd': 'AAABB',
'e': 'AABAA',
'f': 'AABAB',
'g': 'AABBA',
'h': 'AABBB',
'i': 'ABAAA',
'j': 'BBBAA',
'k': 'ABAAB',
'l': 'ABABA',
'm': 'AB... | 434 | 0 |
from typing import Any
class _UpperCamelCase :
def __init__( self: Any , _SCREAMING_SNAKE_CASE: Tuple ) -> List[str]:
"""simple docstring"""
UpperCamelCase_ = data
UpperCamelCase_ = None
def __repr__(... | 713 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.hugging... | 371 | 0 |
'''simple docstring'''
from maths.prime_factors import prime_factors
def UpperCamelCase__ ( _lowercase : int ) -> int:
if not isinstance(_lowercase , _lowercase ):
__UpperCAmelCase: List[str] = F'''Input value of [number={number}] must be an integer'''
... | 523 | '''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def UpperCamelCase__ ( _lowercase : Dict ) -> str:
for param in module.parameters():
__UpperCAmelCase: int = False
def UpperCamelCase__ ( ) ... | 523 | 1 |
"""simple docstring"""
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,
Stabl... | 558 | """simple docstring"""
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
... | 558 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_UpperCamelCase = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'],
}
try:
if not is_torch_available():
... | 243 | """simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses... | 516 | 0 |
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 import TokenizerTesterMixin
class a_ ( lowerCame... | 701 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
_lowerCamelCase =argparse.ArgumentParser(
description=(
"Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Learned"
" Distillation... | 252 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowerCamelCase : int = False
class A( unittest.TestCase ):
... | 70 | """simple docstring"""
import os
import pytest
from attr import dataclass
SCREAMING_SNAKE_CASE__:List[str] = """us-east-1""" # defaults region
@dataclass
class snake_case__ :
_snake_case : str
_snake_case : Optional[Any] = """arn:aws:iam::558105141721:role... | 528 | 0 |
from __future__ import annotations
from math import pi, sqrt
def _lowerCamelCase ( __A : float , __A : float ) -> tuple:
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance <= 0:
raise... | 186 |
import math
def _lowerCamelCase ( __A : int ) -> int:
if not isinstance(__A , __A ):
_UpperCAmelCase : List[Any] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(__A )
if number < 1:
_Upper... | 186 | 1 |
'''simple docstring'''
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,
)
__A = {
"iou_p... | 325 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCAmelCase = {"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG_ARCHIVE... | 409 | 0 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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... | 707 | """simple docstring"""
from sklearn.metrics import matthews_corrcoef
import datasets
__A = """
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It takes
into acco... | 173 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax imp... | 645 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 645 | 1 |
'''simple docstring'''
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
... | 709 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.tes... | 167 | 0 |
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__ = '''src/diffusers'''
# Matches is_xxx_available()
a__ = re.compile(R'''is\_([a-z_]*)_availab... | 14 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def a_ ( lowerCamelCase : Optional[Any] ):
return choice(lowerCamelCase )
def a_ ( lowerCamelCase : list[int] , lowerCamelCase : int... | 133 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __magic_name__ :
__A : int
__A : TreeNode | None = None
__A : TreeNode | None = None
UpperCAm... | 711 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowerCamelCase () -> tuple[list[int], int]:
lowercase :Any = [randint(-1000 , 1000) for i in range(10)]
... | 475 | 0 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def lowerCamelCase__ ... | 73 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
A : Union[str, Any] = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvN... | 15 | 0 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 440 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class lowercase__ ( ... | 440 | 1 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def SCREAMING_SNAKE_CASE ( *lowerCAmelCase__ : str , lowerCAmelCase__ : Optional[Union[Dict, Any]] = None , lowerCAmelCase__ : List[str... | 125 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae impor... | 125 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class lowerCAmelCase_ ( nn.Module ):
"""simple docstring"""
_lowerCAmelCase :... | 708 | """simple docstring"""
def lowerCAmelCase__ ( _UpperCamelCase : int , _UpperCamelCase : int ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(0 ) == 0 )
def lowerCAmelCase__ ( ) -> None:
... | 104 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( _UpperCAmelCase : list , _UpperCAmelCase : int | None = None , _UpperCAmelCase : int | None = None ) -> List[str]:
"""simple docstring"""
if start is None:
... | 244 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, D... | 478 | 0 |
"""simple docstring"""
import unittest
from transformers import MraConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_... | 713 |
"""simple docstring"""
# Copyright 2021 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/licenses/LICENSE-2.0
... | 215 | 0 |
'''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 Vicuna checkpoints, we... | 588 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int ):
lowercase = abs(lowercase_ )
lowercase = 0
while n > 0:
res += n % 10
n //= 10
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : int ):
... | 588 | 1 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class S... | 62 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'roberta-base': 'https://huggingface.co/roberta-base/resolve/main/confi... | 62 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
fro... | 556 |
import numpy as np
def lowerCAmelCase_ (lowerCAmelCase__: np.ndarray , lowerCAmelCase__: float ):
"""simple docstring"""
return np.where(vector > 0 , lowerCAmelCase__ , (alpha * (np.exp(lowerCAmelCase__ ) - 1)) )
if __name__ == "__main__":
impo... | 556 | 1 |
snake_case = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCamelCase__ ( lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Any = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.sub}
SCREAMING_SNAKE_CASE :... | 716 |
# Copyright 2021 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/licenses/LICENSE-2.0
#
# Unless required by ap... | 488 | 0 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 100 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__A : List[Any] = logging.get_logge... | 716 | """simple docstring"""
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __lowerCAmelCase ( nn.Module):
'''simple docstring'''
def __init__( self : Union[str, Any] , UpperCamelCase__ ... | 595 | 0 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _UpperCamelCase ( unittest.TestCase ):
"""si... | 534 | def UpperCAmelCase ( lowercase , lowercase ):
"""simple docstring"""
__lowercase = word.split()
def justify(lowercase , lowercase , lowercase ) -> str:
__lowercase = max_width - width
__lowercase = len(lo... | 534 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_in... | 327 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingface.co/snap... | 327 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_a : Union[str, Any] = logging.get_logger(__name__)
class _lowercase ( __SCREAMING_SNAKE_CASE ):
def __init__( self : Optional[Any] ... | 56 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
A_ : int = logging.get_logger(__name__)
A_ : Dict = {
"google/bit-50": "https:/... | 38 | 0 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCamelCase_ ) -> datetime:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = year % 19
SCREAMING_SNAKE_CASE__ = year % 4
SCREAMING_SNAKE_CASE__ = year % 7
SCREAMING_SN... | 400 |
import math
from datetime import datetime, timedelta
def _lowercase ( UpperCamelCase_ ) -> datetime:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = year % 19
SCREAMING_SNAKE_CASE__ = year % 4
SCREAMING_SNAKE_CASE__ = year % 7
SCREAMING_SN... | 400 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase__ )
class __UpperCamelCase ( lowerCAmelCase__ ):
"""simple docstring"""
... | 74 |
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
lowercase_ = datasets.utils.logging.get_logger(__name__)
@dataclass
class __UpperCamelCase ( datasets.Bui... | 74 | 1 |
"""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
fro... | 215 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
"""simple docstring"""
def get_matched_characters(__UpperCamelCase , __UpperCamelCase ) -> str:
__A = []
__A = min(len(_stra ) , len(_stra ) ) // 2
for i,... | 215 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowercase_ ( __A : list[int] ) -> list[int]: # This function is recursive
"""simple docstring"""
lowercase : str =len(__A )
# If the array contains only one element, we return it (it's t... | 94 |
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowercase_ ( __A : str ) -> Union[str, Any]:
"""simple docstring"""
return x + 2
class UpperCAmelCase_ ... | 94 | 1 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils impo... | 706 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 69 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
impo... | 385 |
"""simple docstring"""
from math import sqrt
def __lowercase ( _a ):
assert isinstance(_a , _a ) and (
number >= 0
), "'number' must been an int and positive"
snake_case_ : List[str] = True
# 0 and 1 are none primes.
if number <= 1:
... | 123 | 0 |
from __future__ import annotations
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE__ ) <= 1 or n <= 1:
return
insert_next(SCREAMING_SNAKE_CASE__ ,n - 1 ... | 693 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase : int ={
'configuration_poolformer': [
'POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'PoolFormerConfig',
... | 693 | 1 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_SHARD_SIZE
from d... | 479 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_a : List[str] = {
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_t... | 479 | 1 |
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,
require_tokenizers,
require_torch,
)
... | 702 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _SCREAMING_SNAKE_CASE ( snake_case_ : Optional[Any] ):
__magic_name__ = SwinConfig(image_size=192 )
if "base" in model_name:
... | 678 | 0 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""kakaobrain/align-base""": """https://hug... | 411 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""tiiuae/falcon-40b""": """https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json""",
"""tiiuae/falcon-7b""": """https://huggin... | 411 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
UpperCamelCase_ = {
"sample_size": 3_2,
"in_channels": 3,
"out_channels": 3,
"layer... | 508 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfi... | 508 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, g... | 526 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase: str = 'Muhammad Umer Farooq'
lowerCAmelCase: List[str] = 'MIT'
lowerCAmelCase: Tuple = '1.0.0'
lowerCAmelCase: List[Any] = 'Muhammad Umer Farooq'
lowerCAmelCase: Optional[Any] = 'contact@muhammadumerf... | 526 | 1 |
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 A_ ( __a : Optional[Any] , __a : Any , __a : Dict ):
"""simple docstring"... | 351 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transfo... | 351 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : Optional[int] = {
"configuration_conditional_detr": [
"CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 120 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCAmelCase = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''LongT5OnnxConfig'''],
}... | 677 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__lowerCamelCase ... | 461 | '''simple docstring'''
def __a ( __lowerCamelCase : int = 600_851_475_143 ) -> int:
'''simple docstring'''
try:
lowercase_ = int(__lowerCamelCase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
... | 461 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataL... | 141 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def lowerCamelCase_ ( __UpperCamelCase = "" ):
A_ = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
A_ = BeautifulSoup(requests.get(__UpperCamelCase ).text ... | 141 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 721 |
import requests
from bsa import BeautifulSoup
def lowerCamelCase_ ( UpperCamelCase_ = "AAPL" ):
_a : List[str] = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
_a : Any = BeautifulSoup(requests.get(UpperCamelCase_ ).text , '''html.parser''' ... | 249 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ : Optional[int] = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMCon... | 8 | """simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeat... | 363 | 0 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required b... | 421 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATAS... | 421 | 1 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowercase ( enum.E... | 304 |
# Lint as: python3
import itertools
import os
import re
lowercase_ : List[Any] = re.compile(r'''([A-Z]+)([A-Z][a-z])''')
lowercase_ : Tuple = re.compile(r'''([a-z\d])([A-Z])''')
lowercase_ : Dict = re.compile(r'''(?<!_)_(?!_)''')
lowercas... | 304 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
a_ : Union... | 707 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : List[str] = logging.get_logger(__name__)
a_ : Dict = {
"""microsoft/unispeech-large-1500h-cv""": (
... | 445 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Any = {"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFI... | 87 | import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 544 | 0 |
_A = range(2, 20 + 1)
_A = [10**k for k in range(ks[-1] + 1)]
_A = {}
def __SCREAMING_SNAKE_CASE ( UpperCamelCase : Optional[Any] , UpperCamelCase : Tuple , UpperCamelCase : List[str] , UpperCamelCase : str ) -> str:
"""s... | 716 |
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_attention_mask
if is_flax_available():
import jax... | 403 | 0 |
'''simple docstring'''
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_lo... | 11 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_commo... | 11 | 1 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE__ :
def __init__( self : Any , a_ : int ):
"""simple docstring"""
__snake_case = n
__snake_case = [None] * self.n
__snake_case = 0 # index of the first element
... | 680 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCAmelCase ( _UpperCAmelCase : np.ndarray , _UpperCAmelCase : float ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
__snake_case = math.sqrt... | 680 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNo... | 569 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
_lowerCAmelCase = """sshleifer/bart-tiny-random"""
_lowerCA... | 569 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase : str = {"configuration_xlnet"... | 674 | """simple docstring"""
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCAmelCase ( lowerCamelCase__ , lowerCam... | 674 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
A_ = tuple[int, int]
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self: Optional[Any] , UpperCamelCase_: List[Any] , UpperCamelCase_: ... | 391 |
"""simple docstring"""
import random
def _snake_case ( __snake_case : List[Any] , __snake_case : List[Any] , __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = a[left_index]
_lowerCamelCase... | 88 | 0 |
"""simple docstring"""
from collections.abc import Generator
def __UpperCAmelCase ( ) -> Generator[int, None, None]:
lowercase__ , lowercase__ : int = 0, 1
while True:
lowercase__ , lowercase__ : int = b, a + b
yield b
de... | 122 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A ( metaclass=A_ ):
'''simple docstring'''
lowerCAmelCase : Optional[Any] = ["flax", "transformers"]
def __init__( self : Union[str... | 122 | 1 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __a (... | 554 |
"""simple docstring"""
SCREAMING_SNAKE_CASE = {}
def lowerCamelCase__ ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ )-> int:
"""simple docstring"""
# if we are absent twice, or late 3 consecutive days,
# no further prize strin... | 554 | 1 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
Auto... | 202 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def __A(lowerCAmelCase ) -> List[str]:
"""simple docstring"""
if "model" in orig_key:
_UpperCamelCase = orig_key.replace("""model.""" , """""" )
if "norm1" in orig_key:
_UpperCamelCase ... | 202 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SC... | 465 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowercase : Union[str, Any] = {"configuration_ibert": ["IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "IBertConfig", "IBertOnnxConfig"]}
try:
if no... | 564 | 0 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
A_ = TypeVar("T")
def __UpperCAmelCase ( UpperCAmelCase )-> List[Any]:
"""simple docstring"""
return (position - 1) // 2
def ... | 714 | from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __UpperCAmelCase ( UpperCAmelCase )-> bool:
"""simple docstring"""
lowercase = int(number**0.5 )
return number == sq * sq
... | 479 | 0 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
lowerCamelCase__ ... | 612 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
from ... | 612 | 1 |
"""simple docstring"""
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
snake_case_ : List[str] = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH AH ... | 708 |
"""simple docstring"""
def lowercase_ ( _lowercase : str ):
'''simple docstring'''
if not all(x.isalpha() for x in string ):
raise ValueError("String must only contain alphabetic characters." )
UpperCAmelCase : Optional[int] = sorted(string.lower() )
... | 292 | 0 |
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class lowerCamelCase_ :
def __init__( self , __lowerCAmelCase = None ):
"""simple docstring"""
if components is None:
__m... | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase_ ( lowerCamelCase ):
a__ = ['''image_processor''', '''tokenizer''']
a__ = '''ChineseCLIPImageProcessor'''
a__ = ... | 0 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : str = logging.get_logger(__name__)
lowercase : List[Any] = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'... | 710 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
lowercase : List[str] = argparse.ArgumentParser()
parser.add_argument('--dump_path', default=Non... | 94 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE_ ( __A : int ) -> bool:
"""simple docstring"""
a_ : Union[str, Any] = str(__A )
return len(__A ) == 9 and set(__A ) == set('123456789' )
... | 570 |
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE__ ( metaclass=lowercase__ ):
snake_case__ : List[str] = ['''onnx''']
def __init__( self : List[Any] , *SCREAMING_SNAKE_CASE__ : Dict , **SCREAMING_SNAKE_CASE__ : ... | 570 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from... | 715 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 696 | 0 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common imp... | 623 |
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List, Literal, ... | 623 | 1 |
"""simple docstring"""
import logging
from transformers import PretrainedConfig
__lowerCAmelCase : List[str] = logging.getLogger(__name__)
__lowerCAmelCase : Optional[Any] = {
"bertabs-finetuned-cnndm": "https://huggingface.co/remi/bertabs-finetuned-cnndm... | 719 | """simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class a_ :
def __init__( self : Optional[int] , snake_case__ : List[Any]=2 , snake_case__ : Any=3 , ... | 674 | 0 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_v... | 283 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""naver-clova-ix/donut-base""": """https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json""",
# See all Donut ... | 678 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCAmelCase_ (nn.Module ):
"""simple docstring"""
lowerCamelCase : int
lowerCamelCase : int... | 382 |
# Copyright 2021 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/licenses/LICENSE-2.0
#
# Unless required by... | 382 | 1 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( ):
"""simple docstring"""
a_ : Union[str, Any] = []
a_ : Optional[Any] = 1
while len(UpperCamelCase__ ) < 1E6:
constant.append(str(UpperCamelCase__ ... | 442 |
'''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 SCREAMING_SNAKE_CASE ( tf.k... | 442 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import load_numpy, slo... | 718 |
_A : Tuple = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def __lowerCAmelCase ( ) -> None:
__lowerCamelCase: Optional[int] = input("""Enter message: """ )
__lowerCamelCase: Dict = input("""Enter key [alphanumeric]: """ )
__lowerCamelCase: List[Any] =... | 189 | 0 |
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