code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def _lowerCAmelCase ( lowerCAmelCase_ :NDArray[floataa] , lowerCAmelCase_ :NDArray[floataa] , lowerCAmelCase_ :list[int] , lowerCAmelCase_ ... | 159 |
"""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_funnel import FunnelTokenizer
__UpperCamelCase = logging.ge... | 113 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import ViTMAEConfig, ViTMAEForPreTraining, ViTMAEImageProcessor
def _A ( A__ ):
"""simple docstring"""
if "cls_token" in name:
__lowercase = name.replace('''cls_token... | 353 |
'''simple docstring'''
def _A ( A__ = 1000 ):
"""simple docstring"""
__lowercase , __lowercase = 1, 1
__lowercase = 2
while True:
__lowercase = 0
__lowercase = fa + fa
__lowercase , __lowercase = fa, f
index += 1
for _... | 52 | 0 |
"""simple docstring"""
def _snake_case ( UpperCamelCase : int , UpperCamelCase : List[str] , UpperCamelCase : Optional[Any] , UpperCamelCase : Tuple , UpperCamelCase : List[Any] , UpperCamelCase : str ):
if index == r:
for j in range(_a ... | 109 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[Any] = {
'''configuration_distilbert''': [
... | 264 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObje... | 7 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __snake_case ( a ):
UpperCAmelCa... | 7 | 1 |
'''simple docstring'''
from __future__ import annotations
def _a( UpperCamelCase__ : Tuple, UpperCamelCase__ : Optional[int] ):
'''simple docstring'''
if b == 0:
return (1, 0)
(SCREAMING_SNAKE_CASE__) : Optional[int] ... | 152 |
'''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 UpperCamelCase__ ( tf.keras.layers.Layer ):
"... | 323 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 353 |
'''simple docstring'''
def __lowerCamelCase ( _lowercase ) -> int:
UpperCAmelCase : List[str] = 0
while num > 0:
digit_sum += num % 1_0
num //= 1_0
return digit_sum
def __lowerCamelCase ( _lowercase = 1_0_0 ) -> int... | 338 | 0 |
class a__ :
"""simple docstring"""
def __init__( self ) -> None:
'''simple docstring'''
A__ = {} # Mapping from char to TrieNode
A__ = False
def UpperCamelCase ( self , lowercase ) -> None:
'''simple docstring'''
... | 68 |
from collections import deque
from math import floor
from random import random
from time import time
class a__ :
"""simple docstring"""
def __init__( self ) -> Dict:
'''simple docstring'''
A__ = {}
def UpperCamelCase ( self , lowercase ,... | 68 | 1 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test... | 287 |
'''simple docstring'''
from __future__ import annotations
def a__ ( lowercase : list[int], lowercase : list[int], lowercase : int ) -> tuple[float, list[float]]:
"""simple docstring"""
_UpperCamelCase = list(range(len(lowercase ) ) )
_UpperCamelC... | 287 | 1 |
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowerCAmelCase__( lowercase : Optional[Any] , lowercase : Optional[int] , lowercase : Union[str, Any] , lowercase : Union[str, Any]=5 ) -> str:
# Adapted from https:/... | 326 |
from maths.prime_factors import prime_factors
def lowerCAmelCase__( lowercase : int ) -> int:
if not isinstance(lowercase , lowercase ):
__snake_case : Optional[int] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase )
i... | 326 | 1 |
from PIL import Image
def __lowercase ( __lowerCAmelCase : Tuple , __lowerCAmelCase : Optional[int] ):
def brightness(__lowerCAmelCase : List[Any] ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -2_5_5.0 <= level <= 2_5... | 356 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Tuple = logging.get_logger(__name__)
snake_case : List[Any] = {
'''snap-research/efficientformer-l1-300''': (
'''https://huggingface.co/snap-rese... | 109 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
A: str = logging.get_logger(__name__)
A: Tuple = {
"CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
"https://huggingface.co/CarlCochet/trajectory-transformer-halfc... | 109 |
"""simple docstring"""
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
... | 109 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.nump... | 30 | """simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditio... | 30 | 1 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
cl... | 210 |
'''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/licenses/LICENSE-2.0... | 297 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_s... | 369 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'''vocab_file''': '''vocab.... | 184 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 57 |
'''simple docstring'''
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 OptionalDepen... | 174 | 0 |
"""simple docstring"""
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 _snak... | 76 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( UpperCamelCase : str ):
def decorator(UpperCamelCase : Optional[int] ):
UpperCAmelCase : List[Any] = getattr(UpperCamelCase , """handle_key""" ,... | 76 | 1 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__a = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add_argument("--dpm", action="... | 66 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str = "cpu" , lowerCAmelCase__ : Union[str, None] = None ) -> None:
... | 224 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer, DPRQ... | 366 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import f... | 339 | 0 |
"""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 (
AutoProcesso... | 135 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTok... | 135 | 1 |
import json
from typing import Dict, List, Optional, Tuple, Union
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokeniza... | 50 | import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
a_ = datasets.utils.logging.get_logger(__name__)
@dataclas... | 50 | 1 |
'''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/licenses/LICENSE-2.0
#... | 265 |
def A_ ( _lowerCAmelCase ) -> str:
UpperCamelCase : List[Any] = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def A_ ( _lowerCAmelCase ) -> dict[str, str]:
UpperCamelCase : Optional[An... | 52 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import torch
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionUpscalePipeline,
PNDMScheduler,... | 365 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from tra... | 95 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDete... | 7 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common... | 7 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _A ( unittest.TestCase ... | 354 |
'''simple docstring'''
def _a ( _lowerCamelCase ) -> Dict:
"""simple docstring"""
__snake_case : str = 0
__snake_case : Optional[int] = len(_lowerCamelCase )
for i in range(n - 1 ):
for j in range(i... | 13 | 0 |
'''simple docstring'''
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
_UpperCamelCase = '''\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Bu... | 208 | import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowercase__ : Any = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/model... | 338 | 0 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class lowerCAmelCase ( __UpperCamelCase ):
def __init__( self : Any , *UpperCAmelCase : Optional[A... | 45 |
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> bool:
if not isinstance(_UpperCAmelCase , _UpperCAmelCase ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(_UpperCAmelCase ) == 0:
raise ValueError('Input list must be a non empt... | 45 | 1 |
from __future__ import annotations
_lowerCamelCase =[True] * 1_0_0_0_0_0_1
_lowerCamelCase =2
while i * i <= 1_0_0_0_0_0_0:
if seive[i]:
for j in range(i * i, 1_0_0_0_0_0_1, i):
_lowerCamelCase =False
i += 1
def _a ( lowerCamelCase ... | 287 |
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
from transformers.configuration_... | 287 | 1 |
def _a ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> bool:
'''simple docstring'''
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 357 |
def _a ( SCREAMING_SNAKE_CASE__ : int ) -> str:
'''simple docstring'''
if isinstance(SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(S... | 191 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class Upper... | 69 |
"""simple docstring"""
from math import isqrt, loga
def _snake_case ( UpperCamelCase : int ):
UpperCAmelCase : Any = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , UpperCamelCase , UpperCamelCase ... | 109 | 0 |
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):
UpperCAmelCase__ : int
UpperCAmelCase__ : int
... | 363 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_tor... | 29 | 0 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class lowercase__( UpperCAmelCase ):
"""simple docstring"""
a :str = CustomTokenizer
pass
| 30 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__a = {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}
try:
... | 30 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase : List[Any] = {
"configuration_perceiver": ["PERCEIVER_PRETRAINED_CON... | 361 | '''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
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 ... | 21 | 0 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversatio... | 81 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .te... | 184 | 0 |
'''simple docstring'''
from typing import Any
def UpperCAmelCase_ (__a : list , __a : list , __a : dict , __a : dict , __a : dict , ):
"""simple docstring"""
_validation(
__a , __a , __a , __a , __a , ... | 5 |
'''simple docstring'''
import qiskit
def UpperCAmelCase_ (__a : int , __a : int ):
"""simple docstring"""
_a : Any = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
_a : List[Any] = qi... | 5 | 1 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def lowerCamelCase__ ( ):
SCREAMING_SNAKE_CASE : Dict = HfArgumentParser(_a)
SCREAMING_SNAKE_CASE : Optional[int] = parser.parse_args_into_dataclasses()[0]
SCREAMING_SNAKE_CAS... | 76 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase__ ( _a , _a , _a , _a , _a):
SCREAMING_SNAKE_CASE : Dict = int(np.ceil((x_end - xa) / step_size))
SCREAMING_SNAKE_CASE : Tuple = np.zeros((n + 1,))
SCREAMING_SNAKE_CASE... | 76 | 1 |
import math
from collections.abc import Callable
def lowerCAmelCase__ ( _a : Callable[[float], float] , _a : float , _a : float ):
snake_case_ : float = xa
snake_case_ : float = xa
while True:
if x_n == x_na or function(_a )... | 354 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[Any] = logging.ge... | 36 | 0 |
from ...configuration_utils import PretrainedConfig
class A ( A_ ):
UpperCamelCase_ : List[Any] ='''bert-generation'''
def __init__(self , lowerCAmelCase=5_0_3_5_8 , lowerCAmelCase=1_0_2_4 , lowerCAmelCase=2_4 , lowerCAmelCase=1_6 , ... | 295 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
UpperCAmelCase__ = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import word_tokenize
UpperCAmelCase__ =... | 339 | 0 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( UpperCamelCase_ ):
create_state_space_tree(UpperCamelCase_ , [] , 0 , [0 for i in range(len(UpperCamelCase_ ) )] )
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ , ... | 255 |
"""simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class SCREAMING_SNAKE_CAS... | 255 | 1 |
from __future__ import annotations
from typing import Any
class lowerCAmelCase :
def __init__( self : Tuple , UpperCAmelCase : int , UpperCAmelCase : int , UpperCAmelCase : float = 0 ) -> None:
lowerCamelCase__ , lowerCamelCase__ : st... | 50 |
from __future__ import annotations
from typing import Any
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase ) -> None:
create_state_space_tree(_UpperCAmelCase , [] , 0 )
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase )... | 50 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase_ : Any = {
'configuration_pix2struct': [
'PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Pix2StructConfig',
'Pix2Str... | 120 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ : Union[str, Any] = {
'configuration_whisper': ['WHISPER_PRETRA... | 120 | 1 |
'''simple docstring'''
import argparse
import os
import re
__a = "src/transformers"
# Pattern that looks at the indentation in a line.
__a = re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
__a = re.compile(R"^\s*\"([^\"]+)\":")
# Pattern that ... | 35 |
from math import pi
def _A ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 95 | 0 |
from __future__ import annotations
import math
def UpperCamelCase ( snake_case__ : Any ) -> list[int]:
if num <= 0:
UpperCamelCase : str = F"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(__snake_case )
UpperCamelCase ... | 364 |
import re
def UpperCamelCase ( snake_case__ : str ) -> str:
if len(re.findall('[ATCG]' , snake_case__ ) ) != len(snake_case__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name__ == "__main... | 103 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__snake_case = logging.get_logger(__name__)
... | 348 |
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_available, is_vision_available
from ... | 13 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( lowerCamelCase_ : list ):
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0]... | 217 |
'''simple docstring'''
def _lowerCAmelCase ( lowerCamelCase_ : Union[str, Any] ):
__lowercase = 1
__lowercase = 2
while i * i <= n:
__lowercase = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisor... | 217 | 1 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ : str , lowerCAmelCase__ : list[str] ) -> str:
__a = ''''''
for word_or_phrase in separated:
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise Exception('''join(... | 45 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class __lowerCAmelCase :
'''simple docstring'''
... | 45 | 1 |
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,
ftp_get,
... | 369 |
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_lowerCAmelCase : ... | 308 | 0 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase ) -> np.ndarray:
lowerCamelCase__ ... | 41 |
"""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/LI... | 191 | 0 |
import argparse
from collections import defaultdict
import yaml
lowerCamelCase_ = '''docs/source/en/_toctree.yml'''
def __magic_name__ ( __a : Union[str, Any] ):
'''simple docstring'''
UpperCamelCase__ = defaultdict(__a )
for doc in model_doc:... | 368 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 178 | 0 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
UpperCAmelCase_ = {
'E': 12.70,
'T': 9.06,
'A': 8.17,
'O': 7.51,
'I': 6.97,
'N': 6.75,
'S': 6.33,
'H': 6.09,
'R': 5.99,
'D': 4.25,
'L': 4.03,
'C': 2.78,
'U': 2.76,
'M... | 12 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params im... | 29 | 0 |
'''simple docstring'''
import itertools
import string
from collections.abc import Generator, Iterable
def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase ) -> Generator[tuple[str, ...], None, None]:
lowerCamelCase__ : List[Any] = iter(Upper... | 129 |
'''simple docstring'''
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentPar... | 129 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_i... | 33 |
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 21 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case__)
class lowercase ( snake_case__):
"""simple docstring"""
a__ : str = fiel... | 353 |
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTesterMixin
from ...te... | 277 | 0 |
from typing import Any
def UpperCAmelCase_ ( __snake_case , __snake_case , __snake_case , __snake_case , __snake_case , ) -> list:
"""simple docstring"""
_validation(
__snake_case , __snake_case , __snake_case , ... | 5 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 1 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_UpperCAmelCase : List[Any] = HfApi()
_UpperCAmelCase : List[str] = {}
# fmt: off
_UpperCAmelCase : Any = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3... | 359 |
import argparse
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, DistributedTyp... | 110 | 0 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class a__ ( lowerCamelCase_ ):
... | 250 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class UpperCAmelCase_ ( a):
def snake_case__ ( self, __a):
'''simple docstring'''
return 0.0
def A ... | 36 | 0 |
"""simple docstring"""
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin... | 209 |
"""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... | 209 | 1 |
"""simple docstring"""
import heapq
import sys
import numpy as np
_UpperCamelCase: Optional[int] = tuple[int, int]
class a__ :
def __init__( self : str ) -> Tuple:
lowercase : List[str] = []
lowercase ... | 255 |
"""simple docstring"""
from __future__ import annotations
def lowercase__ ( _UpperCAmelCase , _UpperCAmelCase ) -> list[int]:
'''simple docstring'''
lowercase : Tuple = 0
lowercase : int = len(_UpperCAmelCase ) - 1
... | 255 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvailable()
... | 34 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowerCamelCase_ = get_logger(__name__)
class __lowerCamelCase ( enum.Enum ):
lowerCamelCase_ : Dict = 'all_checks'
lowerCamelCas... | 34 | 1 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
... | 120 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils im... | 120 | 1 |
from __future__ import annotations
import math
__lowerCamelCase : Tuple = """2020.9.26"""
__lowerCamelCase : Tuple = """xcodz-dot, cclaus, dhruvmanila"""
def SCREAMING_SNAKE_CASE ( snake_case_ : float , snake_case_ : float , snake_case_ :... | 286 |
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,
... | 286 | 1 |
'''simple docstring'''
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 snak... | 55 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transfor... | 103 | 0 |
"""simple docstring"""
class lowerCamelCase_:
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
_lowerCamelCase = len(lowerCamelCase__ )
_lowerCamelCase = [0] * len_array
if len_array > 0:
_lowerCamelCase ... | 351 |
"""simple docstring"""
import qiskit
def lowerCAmelCase_( lowercase_ : int , lowercase_ : int ) -> qiskit.result.counts.Counts:
_lowerCamelCase = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 73 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
... | 217 |
"""simple docstring"""
__A = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE... | 217 | 1 |
"""simple docstring"""
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
a : List[Any] = WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""... | 150 |
"""simple docstring"""
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_... | 150 | 1 |
def a__ ( snake_case , snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Union[str, Any] = [1]
for i in range(2 , snake_case ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
__SCREAMING_SNAKE_CASE ... | 303 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""uw-madison/mra-base-512-4""": """https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json""",
}
class __UpperCa... | 303 | 1 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Dict = logging.get_logger(__name__)
_lowerCAmelCase : Union[str, Any] = {
"""snap-research/efficientformer-l1-300""": (
... | 298 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( snake_case : Optional[Any] , snake_case : Any )-> Any:
'''simple docstring'''
UpperCAmelCase__ : List[str] = [1]
for i in range(2 , snake_case ):
factorials.append(factoria... | 298 | 1 |
"""simple docstring"""
from collections import defaultdict
class SCREAMING_SNAKE_CASE_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__):
__SCREAMING_SNAKE_CASE = total # total no of tasks (N)
# DP table will have a dimensi... | 100 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def __UpperCAmelCase ( a_ , a_ , a_ , a_ , a_):
snake_case_ = np.array([[... | 178 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_lowerCAmelCase : str = False
try:
_lowerCAmelCase : in... | 70 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
_l... | 70 | 1 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPipeline,
UN... | 129 |
def lowerCAmelCase__ ( lowerCamelCase_ : str):
'''simple docstring'''
lowerCAmelCase__ : Any = [0] * len(lowerCamelCase_)
for i in range(1 ,len(lowerCamelCase_)):
# use last results for better performance - dynamic programming
lowerCAmelCase__ ... | 129 | 1 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def UpperCamelCase ( snake_case__ : int ) -> int:
# A local function to see if a dot lands in the circle.
def is_in_circle(snake_case__ : float , snake_case__ ... | 366 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torc... | 103 | 0 |
"""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... | 113 |
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
logging,
)
logging.set_... | 277 | 0 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
__snake_case = '''\
@misc{chen2021evaluating,
title={Eva... | 354 |
"""simple docstring"""
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def __lowerCAmelCase ( lowercase : Union[str, Any] , lowercase : Optional[int]=False ) -> Union[str, Any]:
"""simple docstrin... | 112 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case_ ( A_ : Tuple, A_ : int, A_ : Dict ):
... | 72 |
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
if exponent == 1:
return base
if exponent % 2 == 0:
lowercase__ = _modexpt(SCREAMING_SNAKE_CASE , exponent // 2 , SCREAMI... | 110 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers im... | 361 |
'''simple docstring'''
import math
from typing import Dict, Iterable, List, Optional, Tuple, 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
from ...image_ut... | 156 | 0 |
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
_a = logging.get_logger(__name__)
_a = ... | 209 |
import numpy as np
from transformers import Pipeline
def lowerCAmelCase__(__snake_case ) -> Tuple:
'''simple docstring'''
lowerCamelCase__ = np.max(__snake_case ,axis=-1 ,keepdims=__snake_case )
lowerCamelCase__ = np.exp(outputs - maxes ... | 209 | 1 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational ... | 346 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __S... | 346 | 1 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
A =logging.get_logger(__name__)
def snake_case_ (_a : ... | 34 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleCh... | 34 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
__UpperCAmelCase = version.parse(version.parse(torch.__version__).base_version) < version.parse('''1.1... | 228 |
'''simple docstring'''
from __future__ import annotations
class a__ :
'''simple docstring'''
def __init__( self , lowerCamelCase_ ) -> None:
lowerCAmelCase__ = order
# a_{0} ... a_{k}
... | 228 | 1 |
"""simple docstring"""
def UpperCAmelCase__ ( _UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase ):
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(_UpperCAmelCase ) )
def ... | 286 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _UpperCAmelCase ( UpperCAmelCase__ , UpperCAmelCase__ ):
'''simple docstring... | 286 | 1 |
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,
PND... | 350 |
a : Tuple = 'Tobias Carryer'
from time import time
class _a :
def __init__(self, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_=int(time() ) ) -> List[Any]: # noqa: B008
UpperCAmelCase_: List[str]... | 82 | 0 |
from bisect import bisect
from itertools import accumulate
def __magic_name__ ( A : List[Any], A : str, A : Union[str, Any], A : Optional[Any] ):
'''simple docstring'''
a = sorted(zip(lowerCamelCase__, lowerCamelCase__ ), key=lambda A : x[0] / x[1], ... | 107 |
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> float:
if discount_rate < 0:
raise ValueError('Discount rate cannot be negative' )
if not cash_flows:
raise ValueError('Cash flows list cannot be empty' )
__lowerCamelCase : int = sum(
cash_... | 73 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full_... | 218 |
import warnings
from .generation import TFGenerationMixin
class UpperCAmelCase__ ( A__ ):
"""simple docstring"""
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transformers v5. Import as `from transf... | 218 | 1 |
"""simple docstring"""
from manim import *
class lowerCAmelCase_ ( lowerCAmelCase ):
"""simple docstring"""
def snake_case ( self ):
"""simple docstring"""
snake_case = Rectangle(height=0.5 , width=0.5 )
snake_... | 150 | """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,
)
... | 150 | 1 |
from itertools import count
def UpperCamelCase ( __lowercase : int = 50 ):
'''simple docstring'''
A_ : Optional[Any] = [1] * min_block_length
for n in count(__lowercase ):
fill_count_functions.append(1 )
for block_length in range(__lower... | 366 | import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_UpperCAmelCase = logging.get_logger(__name__)
class UpperCAmelCase ( __A ):
'''simple docstring'''
def __init__( self , *lowercase , **lowe... | 192 | 0 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class A :
'''simple docstring'''
... | 298 |
'''simple docstring'''
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test... | 298 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_availa... | 292 |
def snake_case (UpperCAmelCase__ ) -> int:
assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F'''The input value of [n={number}] is not an integer'''
if number == 1:
return 2
elif number < 1:
UpperCamelCase_: List[Any] = F'''The input value of [n={number}]... | 292 | 1 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = len(lowerCAmelCase ) + 1
_lowerCAmelCase = len(lowerCAmelCase ) + 1
# dp is a... | 70 |
'''simple docstring'''
from __future__ import annotations
import math
def UpperCamelCase__ ( lowerCAmelCase ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0... | 70 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
_snake_case = ... | 300 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_snake_case = 1.0_5457_1817e-34 # unit of ℏ : J * s
_snake_case = 3e8 # unit of c : m * s^-1
def A ( _lowerCamelCase , _lowerCamelCase ... | 300 | 1 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE__ : list[int] ):
if len(__UpperCamelCase ) == 0:
return array
UpperCamelCase :Optional[Any] = min(__UpperCamelCase ), max(__UpperCamelCase )
# Compute the variables
UpperCam... | 259 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str] = logging.get_logger(__name__)
A__ : int = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}
class __snake_ca... | 103 | 0 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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
#
... | 337 |
'''simple docstring'''
_lowerCamelCase : List[Any] = 'Input must be a string of 8 numbers plus letter'
_lowerCamelCase : str = 'TRWAGMYFPDXBNJZSQVHLCKE'
def __a ( UpperCAmelCase ) ->bool:
"""simple docstring"""
if not isinstance(UpperCAmelCase , ... | 337 | 1 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
__UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, required=... | 67 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'''The `inpainting.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionInpaintPipeline` instead.'''
) | 112 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_... | 360 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ = {
"""configuration_mega""": ["""MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegaConfig""", """M... | 12 | 0 |
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 299 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils impo... | 156 | 0 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
fro... | 357 |
def lowerCAmelCase_ ( _lowercase : int) -> int:
"""simple docstring"""
if not isinstance(_lowercase , _lowercase):
raise TypeError("""only integers accepted as input""")
else:
a__ : Any = str(abs(_lowercase))
... | 266 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase : Tuple = logging.get_logger(__name__)
low... | 291 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 291 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ )-> Tuple:
"""simple docstring"""
create_state_space_tree(_A , [] , 0 )
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ , SCREA... | 353 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_util... | 60 | 0 |
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def __A ( ) -> Tuple:
raise RuntimeError("""CUDA out of memory.""" )
class __lowerCAmelCase... | 228 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Optional[Any] = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"Jukebo... | 228 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ : int ={
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
'''processing_git''': ['''GitProcessor'''... | 262 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql # noqa F40... | 262 | 1 |
import argparse
import json
import subprocess
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : List[Any]):
lowercase__ : List[Any] = []
lowercase__ : Dict = (
f'''curl -H "Accept: application/vnd.github+json" -H "Authorizatio... | 87 |
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... | 82 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeli... | 370 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( UpperCAmelCase : float , UpperCAmelCase : float , UpperCAmelCase : float ):
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError(... | 157 | 0 |
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