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 |
|---|---|---|---|---|
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowerCamelCase = ['''image_processor''', '''tokeniz... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"distilbert-base-unca... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ,lowerCamelCase_ ) -> Union[str, Any]:
A = list_of_points
... | 77 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 | 1 |
"""simple docstring"""
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ,lowerCame... | 77 |
"""simple docstring"""
def _A ( _a : Optional[int] ):
"""simple docstring"""
A = []
A = set({"""(""", """[""", """{"""} )
A = set({""")""", """]""", """}"""} )
A ... | 77 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def _A ( _a : int = 1_5_0_0_0_0_0 ):
"""simple docstring"""
A = defaultdict(_a )
A = 2
while 2 * euclid_m * (eu... | 77 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase ="\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 77 | 1 |
"""simple docstring"""
import pickle
import numpy as np
from matplotlib import pyplot as plt
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ,lowerCamelCase_ ,lowerCamelCase_ ,lowerCamelCase_ ,lowerCamelCase_ ,lowerCamelCase_ ,lower... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ... | 77 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from trans... | 77 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( _a : Callable[[int | float], int | float] , _a : int | float , _a : int | float , _a : int = 1_0_0 , ):
"""simple docs... | 77 | 1 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _A ( _a : List[Any] , _a : List[Any] , _a : Dict , _a : List[str]=1_0_2_4 ):
"""simple... | 77 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( _a : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(_a , 0 ... | 77 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvis... | 77 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
... | 77 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, ... | 77 |
"""simple docstring"""
def _A ( _a : int ):
"""simple docstring"""
A = abs(_a )
A = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def _A ( _a... | 77 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 77 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 | 1 |
"""simple docstring"""
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAmelCase =get_tests_dir(... | 77 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
UpperCAmelCase =generate_large_matrix()
UpperCAmelCase =(
[[4, 3, 2, -1], [3, ... | 77 | 1 |
"""simple docstring"""
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( ... | 77 |
"""simple docstring"""
import pytest
UpperCAmelCase ="__dummy_dataset1__"
UpperCAmelCase ="\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \... | 77 | 1 |
"""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/L... | 77 |
"""simple docstring"""
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> Any:
A = 0
A = 0
A = {}
def UpperCamelCase__ ( self ,lowerCamelCase_ ) ... | 77 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase ={
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftFormerConfig"... | 77 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a ) + 1
A = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 77 | 1 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def _A ( _a : int="ro" , _a : List[Any]="en" , _a : Union[str, Any]="wmt16" , _a : Tuple=None ):
"""simple docstring"""
try:
... | 77 |
"""simple docstring"""
from math import factorial
def _A ( _a : int = 1_0_0 ):
"""simple docstring"""
return sum(map(_a , str(factorial(_a ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the N... | 77 | 1 |
"""simple docstring"""
from collections import Counter
from timeit import timeit
def _A ( _a : str = "" , ):
"""simple docstring"""
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ) <... | 77 |
"""simple docstring"""
from typing import Dict, Iterable, 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,
... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
def _A ( _a : int | float | str , _a : int | float | str ):
"""simple docstring"""
if nth_term == "":
return [""]
A = int(_a )
A ... | 77 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _A ( _a : Callable , _a : float , _a : float , _a : float , _a : float ):
"""simple docstring"""
A = int... | 77 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():... | 77 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 77 | 1 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
f... | 77 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL im... | 77 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"distilbert-base-unca... | 77 |
"""simple docstring"""
import torch
from transformers import AutoModel
class lowerCamelCase__ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self ,lowerCamelCase_="sayef/fsner-bert-base-uncased" ) -> Tuple:
super(lowerCamelCase_ ... | 77 | 1 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( _a : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(_a , 0 ... | 77 |
"""simple docstring"""
import random
def _A ( _a : list , _a : Any ):
"""simple docstring"""
A , A , A = [], [], []
for element in data:
if element < pivot:
less.append(... | 77 | 1 |
"""simple docstring"""
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def _A ( _a : Optional[int] ):
"""simple docstring"""
A = [
... | 77 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 77 | 1 |
"""simple docstring"""
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:%... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"distilbert-base-unca... | 77 | 1 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def _A ( _a : int ):
"""simple docstring"""
A = prime_factors(_a )
if is_square_free(_a ):
... | 77 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 | 1 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> List[Any]:
A = psutil.Process()
A = False
... | 77 |
"""simple docstring"""
def _A ( _a : Optional[int] ):
"""simple docstring"""
A = []
A = set({"""(""", """[""", """{"""} )
A = set({""")""", """]""", """}"""} )
A ... | 77 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
f... | 77 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase ="\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 77 | 1 |
"""simple docstring"""
from timeit import timeit
def _A ( _a : int ):
"""simple docstring"""
if number < 0:
raise ValueError("""the value of input must not be negative""" )
A = 0
while number:
... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ... | 77 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
UpperCAmelCase =500_000
UpperCAmelCase , UpperCAmelCase =os.path.split(__file__)
UpperCAmelCase =os.path.join(RESULTS_BAS... | 77 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( _a : Callable[[int | float], int | float] , _a : int | float , _a : int | float , _a : int = 1_0_0 , ):
"""simple docs... | 77 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase ={
"configuration_whisper": ["WHISPER_PR... | 77 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( _a : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(_a , 0 ... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class lowerCamelCase__ :
'''simple docstring'''
_lowerCamelCase = 42
... | 77 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
... | 77 | 1 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the confi... | 77 |
"""simple docstring"""
def _A ( _a : int ):
"""simple docstring"""
A = abs(_a )
A = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def _A ( _a... | 77 | 1 |
"""simple docstring"""
import os
from pathlib import Path
def _A ( ):
"""simple docstring"""
from torch.utils.cpp_extension import load
A = Path(_a ).resolve().parent.parent.parent / """kernels""" / """deformable_detr"""
... | 77 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
UpperCAmelCase =TypeVar("KT")
UpperCAmelCase =TypeVar("VT")
class lowerCamelCase__ ( Generic[KT, VT] ):
'''simple docstring'''
def ... | 77 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
UpperCAmelCase =generate_large_matrix()
UpperCAmelCase =(
[[4, 3, 2, -1], [3, ... | 77 | 1 |
"""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 lowerCamelCase__ ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
... | 77 |
"""simple docstring"""
import pytest
UpperCAmelCase ="__dummy_dataset1__"
UpperCAmelCase ="\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_propert... | 77 |
"""simple docstring"""
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> Any:
A = 0
A = 0
A = {}
def UpperCamelCase__ ( self ,lowerCamelCase_ ) ... | 77 | 1 |
"""simple docstring"""
UpperCAmelCase =range(2, 20 + 1)
UpperCAmelCase =[10**k for k in range(ks[-1] + 1)]
UpperCAmelCase ={}
def _A ( _a : int , _a : Tuple , _a : Tuple , _a : Optional[int] ):
"""simple docstring"""
... | 77 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a ) + 1
A = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
def _A ( _a : list[int | float] , _a : int , _a : int ):
"""simple docstring"""
if len(_a ) == 0:
raise ValueError("""find_max() arg is an empty sequen... | 77 |
"""simple docstring"""
from math import factorial
def _A ( _a : int = 1_0_0 ):
"""simple docstring"""
return sum(map(_a , str(factorial(_a ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the N... | 77 | 1 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 |
"""simple docstring"""
from typing import Dict, Iterable, 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,
... | 77 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 77 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _A ( _a : Callable , _a : float , _a : float , _a : float , _a : float ):
"""simple docstring"""
A = int... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ... | 77 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 77 | 1 |
"""simple docstring"""
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ,lowerCamelCase_ ) -> None:
A = size
A = [0] * size
A = [0] * size
@staticmethod
... | 77 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL im... | 77 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
UpperCAmelCase =logging.get_logger(__name__)
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( ... | 77 |
"""simple docstring"""
import torch
from transformers import AutoModel
class lowerCamelCase__ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self ,lowerCamelCase_="sayef/fsner-bert-base-uncased" ) -> Tuple:
super(lowerCamelCase_ ... | 77 | 1 |
"""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/L... | 77 |
"""simple docstring"""
import random
def _A ( _a : list , _a : Any ):
"""simple docstring"""
A , A , A = [], [], []
for element in data:
if element < pivot:
less.append(... | 77 | 1 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a ) + 1
A = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 77 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 77 | 1 |
"""simple docstring"""
def _A ( _a : list[list[int | float]] ):
"""simple docstring"""
A = len(_a )
A = len(matrix[0] )
A = min(_a , _a )
for row in range(... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"distilbert-base-unca... | 77 | 1 |
"""simple docstring"""
import requests
UpperCAmelCase ="https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def _A ( _a : str ):
"""simple docstring"""
A = requests.get(_NEWS_API + bbc_news_api_key ).... | 77 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 | 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("1.11")
def ... | 77 |
"""simple docstring"""
def _A ( _a : Optional[int] ):
"""simple docstring"""
A = []
A = set({"""(""", """[""", """{"""} )
A = set({""")""", """]""", """}"""} )
A ... | 77 | 1 |
"""simple docstring"""
import random
from .binary_exp_mod import bin_exp_mod
def _A ( _a : str , _a : str=1_0_0_0 ):
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
... | 77 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase ="\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 77 | 1 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ... | 77 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
_lowerCamelCase = ['''image_processor''', '''tokeniz... | 77 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( _a : Callable[[int | float], int | float] , _a : int | float , _a : int | float , _a : int = 1_0_0 , ):
"""simple docs... | 77 | 1 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> None:
A = [2, 1, 2, -1]
A = [1, 2, 3, 4]
... | 77 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( _a : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(_a , 0 ... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def _A ( _a : float , _a : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("""Inductance cannot be 0 or negative""" ... | 77 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
... | 77 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"facebook/xmod-base":... | 77 |
"""simple docstring"""
def _A ( _a : int ):
"""simple docstring"""
A = abs(_a )
A = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def _A ( _a... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def _A ( _a : int , _a : int , _a : bool , _a : list[int] , _a : float ):
"""simple docstring"""
if depth < 0:
raise Value... | 77 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 | 1 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL im... | 77 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
UpperCAmelCase =generate_large_matrix()
UpperCAmelCase =(
[[4, 3, 2, -1], [3, ... | 77 | 1 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
["""em... | 77 |
"""simple docstring"""
import pytest
UpperCAmelCase ="__dummy_dataset1__"
UpperCAmelCase ="\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \... | 77 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _A ( _a : Callable , _a : float , _a : float , _a : float , _a : float ):
"""simple docstring"""
A = int... | 77 |
"""simple docstring"""
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> Any:
A = 0
A = 0
A = {}
def UpperCamelCase__ ( self ,lowerCamelCase_ ) ... | 77 | 1 |
"""simple docstring"""
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 ( ):
"""simple docstring"""
raise RuntimeErro... | 77 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a ) + 1
A = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 77 | 1 |
"""simple docstring"""
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class lowerCamelCase__ ( ctypes.Structure ):
'''simple docstring'''
_lowerCamelCase = [('''siz... | 77 |
"""simple docstring"""
from math import factorial
def _A ( _a : int = 1_0_0 ):
"""simple docstring"""
return sum(map(_a , str(factorial(_a ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the N... | 77 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import l... | 77 |
"""simple docstring"""
from typing import Dict, Iterable, 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,
... | 77 | 1 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def _A ( _a : int ):
"""simple docstring"""
if not isinstance(_a , _a ):
A = f'Input value of [number={number}] must be an integer'
... | 77 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _A ( _a : Callable , _a : float , _a : float , _a : float , _a : float ):
"""simple docstring"""
A = int... | 77 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ... | 77 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 77 | 1 |
"""simple docstring"""
from __future__ import annotations
def _A ( _a : list ):
"""simple docstring"""
if not nums:
raise ValueError("""List is empty""" )
return sum(_a ) / len(_a )
if __name__ == "__main_... | 77 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL im... | 77 | 1 |
"""simple docstring"""
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCamelCase__ ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase__ ( ... | 77 |
"""simple docstring"""
import torch
from transformers import AutoModel
class lowerCamelCase__ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self ,lowerCamelCase_="sayef/fsner-bert-base-uncased" ) -> Tuple:
super(lowerCamelCase_ ... | 77 | 1 |
"""simple docstring"""
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, Truncati... | 77 |
"""simple docstring"""
import random
def _A ( _a : list , _a : Any ):
"""simple docstring"""
A , A , A = [], [], []
for element in data:
if element < pivot:
less.append(... | 77 | 1 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
fro... | 77 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 77 | 1 |
"""simple docstring"""
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
... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"distilbert-base-unca... | 77 | 1 |
"""simple docstring"""
def _A ( _a : int = 1_0_0_0 ):
"""simple docstring"""
A = 2**power
A = 0
while n:
A , A = r + n % 1_0, n // 1_0
return r
if __name__ ... | 77 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_avail... | 77 |
"""simple docstring"""
def _A ( _a : Optional[int] ):
"""simple docstring"""
A = []
A = set({"""(""", """[""", """{"""} )
A = set({""")""", """]""", """}"""} )
A ... | 77 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"google/fnet-large": "https... | 77 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase ="\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 77 | 1 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class lowerCamelCase__ ( SCREAMING_SNAKE_C... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ... | 77 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( _a : Tuple , _a : Optional[int] , _... | 77 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( _a : Callable[[int | float], int | float] , _a : int | float , _a : int | float , _a : int = 1_0_0 , ):
"""simple docs... | 77 | 1 |
"""simple docstring"""
from math import pi
def _A ( _a : int , _a : int ):
"""simple docstring"""
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 77 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( _a : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(_a , 0 ... | 77 | 1 |
"""simple docstring"""
import os
from collections.abc import Iterator
def _A ( _a : str = "." ):
"""simple docstring"""
for dir_path, dir_names, filenames in os.walk(_a ):
A = [d for d in dir_names if d != """s... | 77 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
... | 77 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstri... | 77 |
"""simple docstring"""
def _A ( _a : int ):
"""simple docstring"""
A = abs(_a )
A = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def _A ( _a... | 77 | 1 |
"""simple docstring"""
# flake8: noqa
# Lint as: python3
UpperCAmelCase =[
"VerificationMode",
"Version",
"disable_progress_bar",
"enable_progress_bar",
"is_progress_bar_enabled",
"experimental",
]
from .info_utils import VerificationMode
from .logging import disable_p... | 77 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 | 1 |
"""simple docstring"""
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPi... | 77 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
UpperCAmelCase =generate_large_matrix()
UpperCAmelCase =(
[[4, 3, 2, -1], [3, ... | 77 | 1 |
"""simple docstring"""
UpperCAmelCase =256
# Modulus to hash a string
UpperCAmelCase =1_000_003
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a )
A = len(_a ... | 77 |
"""simple docstring"""
import pytest
UpperCAmelCase ="__dummy_dataset1__"
UpperCAmelCase ="\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \... | 77 | 1 |
"""simple docstring"""
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.... | 77 |
"""simple docstring"""
class lowerCamelCase__ :
'''simple docstring'''
def __init__( self ) -> Any:
A = 0
A = 0
A = {}
def UpperCamelCase__ ( self ,lowerCamelCase_ ) ... | 77 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
... | 77 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a ) + 1
A = len(_a ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 77 | 1 |
"""simple docstring"""
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
UpperCAmelCase ="src/transformers"
UpperCAmel... | 77 |
"""simple docstring"""
from math import factorial
def _A ( _a : int = 1_0_0 ):
"""simple docstring"""
return sum(map(_a , str(factorial(_a ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the N... | 77 | 1 |
"""simple docstring"""
from manim import *
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def UpperCamelCase__ ( self ) -> Union[str, Any]:
A = Rectangle(height=0.5 ,width=0.5 )
A ... | 77 |
"""simple docstring"""
from typing import Dict, Iterable, 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,
... | 77 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"camembert-base": "ht... | 77 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def _A ( _a : Callable , _a : float , _a : float , _a : float , _a : float ):
"""simple docstring"""
A = int... | 77 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase =logging.get_logger(__name__)
class lowerCamelCase__ ( SCREAMIN... | 77 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 77 | 1 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
... | 77 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL im... | 77 | 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
if is_torch_available()... | 77 |
"""simple docstring"""
import torch
from transformers import AutoModel
class lowerCamelCase__ ( torch.nn.Module ):
'''simple docstring'''
def __init__( self ,lowerCamelCase_="sayef/fsner-bert-base-uncased" ) -> Tuple:
super(lowerCamelCase_ ... | 77 | 1 |
"""simple docstring"""
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="%(message)s")
def _A ( _a : np.ndarray ):
"""simple docstring"""
return input_array.reshape... | 77 |
"""simple docstring"""
import random
def _A ( _a : list , _a : Any ):
"""simple docstring"""
A , A , A = [], [], []
for element in data:
if element < pivot:
less.append(... | 77 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
'''simp... | 77 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms... | 77 | 1 |
"""simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.s... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ={
"distilbert-base-unca... | 77 | 1 |
"""simple docstring"""
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 im... | 77 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class lowerCamelCase__ ( SC... | 77 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase ={
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransf... | 77 |
"""simple docstring"""
def _A ( _a : Optional[int] ):
"""simple docstring"""
A = []
A = set({"""(""", """[""", """{"""} )
A = set({""")""", """]""", """}"""} )
A ... | 77 | 1 |
"""simple docstring"""
def _A ( _a : str , _a : str ):
"""simple docstring"""
A = len(_a )
A = len(_a )
A = [[False for _ in range(m + 1 )] for _ in range(n + ... | 77 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
UpperCAmelCase ="\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {... | 77 | 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_image_inputs
i... | 77 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase =logging.get_logger(__name__)
UpperCAmelCase ... | 77 | 1 |
"""simple docstring"""
def _A ( _a : int ):
"""simple docstring"""
A = abs(_a )
A = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def _A ( _a... | 77 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( _a : Callable[[int | float], int | float] , _a : int | float , _a : int | float , _a : int = 1_0_0 , ):
"""simple docs... | 77 | 1 |
"""simple docstring"""
import inspect
import unittest
class lowerCamelCase__ ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase__ ( self ) -> int:
try:
import diffusers # noqa: F401
except ImportError... | 77 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( _a : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(_a , 0 ... | 77 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
UpperCAmelCase ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable... | 77 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=SCREAMING_SNAKE_CASE )
class lowerCamelCase__ ( SCREAMING_SNAKE_CASE ):
... | 77 | 1 |
"""simple docstring"""
from math import factorial
def _A ( _a : int = 1_0_0 ):
"""simple docstring"""
return sum(map(_a , str(factorial(_a ) ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the N... | 77 |
"""simple docstring"""
def _A ( _a : int ):
"""simple docstring"""
A = abs(_a )
A = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def _A ( _a... | 77 | 1 |
"""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, ... | 77 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
UpperCAmelCase =argparse.ArgumentParser()
parser.add_argument("--dump_path", de... | 77 | 1 |
"""simple docstring"""
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase =Lock()
def _A ( _a : Dict , _a : List[str] , _a : Dict , _a : Dict , _a ... | 350 |
"""simple docstring"""
def _A ( ):
"""simple docstring"""
return [list(range(1_0_0_0 - i , -1_0_0_0 - i , -1 ) ) for i in range(1_0_0_0 )]
UpperCAmelCase =generate_large_matrix()
UpperCAmelCase =(
[[4, 3, 2, -1], [3, ... | 77 | 0 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class ... | 351 |
"""simple docstring"""
import pytest
UpperCAmelCase ="__dummy_dataset1__"
UpperCAmelCase ="\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \... | 77 | 0 |
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