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 __SCREAMING_SNAKE_CASE ( lowerCamelCase ):
snake_case_ = ["""image_processor""", """tokenizer"""]
snake_case_ ... | 152 |
'''simple docstring'''
import socket
def _a( ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Tuple =socket.socket(socket.AF_INET, socket.SOCK_STREAM )
SCREAMING_SNAKE_CASE__ : str =socket.gethostname()
... | 152 | 1 |
import os
from math import logaa
def __A (_SCREAMING_SNAKE_CASE = "base_exp.txt" ) ->int:
"""simple docstring"""
lowerCAmelCase__ :float = 0
lowerCAmelCase__ :Union[str, Any] = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(lower... | 351 |
"""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.... | 254 | 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 AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__: Tuple = logging.get_... | 23 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...... | 119 | 0 |
"""simple docstring"""
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize('''dataset_size''' , [None, 400 * 2**20, 600 * 2**20] )
@pytest.mark.parametrize('''input_in_memory_max_size''' , ['''default''', 0, 100 * 2**20, 900 * 2**2... | 68 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
_lowerCAmelCase :int = '\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={arXiv p... | 68 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class lowerCamelCase ( metaclass=lowercase_ ):
'''simple docstring'''
__snake_case = ['speech']
def __init__( self : Tuple , *lowerCAmelCase_ : List[str] , **lowerCAmelC... | 134 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int, __snake_case : int, __snake_case : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(__snake_case : int, __snake_case : int ) -> in... | 134 | 1 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaa... | 59 |
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaa... | 59 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : Any = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
"""XCLIPTextCo... | 307 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 131 | 0 |
UpperCamelCase = tuple[float, float, float]
UpperCamelCase = tuple[float, float, float]
def __lowerCamelCase ( snake_case__ ,snake_case__ ) -> Vectorad:
"""simple docstring"""
_SCREAMING_SNAKE_CASE = end_pointa[0] - end_po... | 125 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load... | 125 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():... | 254 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenizat... | 254 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/... | 181 |
"""simple docstring"""
import operator as op
snake_case_ = """scaler.pt"""
snake_case_ = """pytorch_model"""
snake_case_ = """random_states"""
snake_case_ = """optimizer"""
snake_case_ = """scheduler"""
snake_case_ = """pytorch_model.bin"""
snake_c... | 181 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str , SCREAMING_SNAKE_CASE_: List[str] ) -> Tuple:
'''simple docstring'''
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: Optional[Any]... | 68 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENA... | 68 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase : List[str] = {
'''configuration_luke''': ['''LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LukeConfig'''],
'''tokenization_luke''':... | 354 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def UpperCAmelCase_ (__a : Optional[Any] ):
"""simple docstring"""
_a : int = FileLock(str(tmpdir / 'foo.lock' ) )
_a : List[Any] = ... | 5 | 0 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_uti... | 59 |
__lowerCamelCase = {
"joule": 1.0,
"kilojoule": 10_00,
"megajoule": 1_00_00_00,
"gigajoule": 10_00_00_00_00,
"wattsecond": 1.0,
"watthour": 36_00,
"kilowatthour": 3_60_00_00,
"newtonmeter": 1.0,
"calorie_nutr": 41_86.8,
"kilocalorie_nutr": 4_18_68_00.00,
... | 59 | 1 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE ( *lowercase_ ) -> bool:
"""simple docstring"""
A__ = len(lowercase_ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ... | 231 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase : Tuple = {
"""configuration_speech_to_text""": ["""SPEECH_TO... | 231 | 1 |
'''simple docstring'''
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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 ImageP... | 125 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_a... | 125 | 1 |
from __future__ import annotations
import time
__lowerCamelCase : Optional[Any] = list[tuple[int, int]]
__lowerCamelCase : List[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1,... | 286 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageRes... | 286 | 1 |
'''simple docstring'''
UpperCamelCase__ = '''Tobias Carryer'''
from time import time
class lowerCamelCase_ :
def __init__( self : int , _A : Union[str, Any] , _A : Dict , _A : Union[str, Any] , _A... | 181 |
'''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_distilbert'... | 181 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : List[Any] = {
"""configuration_funnel""": ["""FUNNEL_PRETRAIN... | 91 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers... | 91 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
__lowercase : Tuple = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_... | 27 |
from math import isqrt
def UpperCAmelCase_ ( __snake_case ) -> list[int]:
"""simple docstring"""
_lowercase =[True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __snake_case , ... | 5 | 0 |
class _snake_case :
def __init__( self: Dict ) -> Any:
__UpperCAmelCase : List[Any] = {}
def _lowerCamelCase ( self: int ) -> None:
print(self.vertex )
for i in self.vertex:
pri... | 342 | import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import... | 342 | 1 |
def lowerCamelCase__ ( __lowerCAmelCase : str ):
"""simple docstring"""
return " ".join(
"".join(word[::-1] ) if len(__lowerCAmelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(reverse_long_words... | 231 |
import functools
def lowerCamelCase__ ( __lowerCAmelCase : str , __lowerCAmelCase : str ):
"""simple docstring"""
lowerCAmelCase_ = len(__lowerCAmelCase )
lowerCAmelCase_ = len(__lowerCAmelCase )
@functools.cache
def min_distance(__lowerCAmelCase : ... | 231 | 1 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCamelCase : Tuple = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"con... | 208 |
from ..utils import DummyObject, requires_backends
class A( metaclass=UpperCamelCase ):
'''simple docstring'''
UpperCamelCase = ['''keras_nlp''']
def __init__( self : Optional[int] , *A_ : Any , **A_ : Dict ) -> ... | 208 | 1 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
lowerCamelCase_ : Union[str, Any] = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and ... | 286 |
"""simple docstring"""
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
... | 286 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_d... | 361 |
import math
import tensorflow as tf
from packaging import version
def A ( a_ ) -> Optional[Any]:
__UpperCamelCase : Dict =tf.convert_to_tensor(a_ )
__UpperCamelCase : str =0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(2.0 ) ,x.dtype ) ))
... | 245 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( Up... | 91 |
"""simple docstring"""
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 91 | 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
if is_torch_availa... | 312 | """simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase ) -> int:
if depth < 0:
raise ValueError('Depth cannot be less than 0' )
if len(Uppe... | 312 | 1 |
class snake_case__ :
def __init__( self ) -> Optional[Any]:
__magic_name__ : Optional[Any] = {}
def __magic_name__ ( self ) -> None:
print(self.vertex )
for i in self.vertex:
print(lowerCAmelCase__ , """ -> """ ... | 342 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils i... | 342 | 1 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class __lowerCamelCase ( UpperCamelCase__ ):
"""simple docstring"""
def __init__( self : ... | 221 |
from maths.prime_factors import prime_factors
def _A ( lowerCAmelCase_ : int ):
"""simple docstring"""
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
lowerCAmelCase__ = F'Input value of [number={number}] must be an int... | 221 | 1 |
'''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 ... | 208 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
... | 208 | 1 |
from graphs.minimum_spanning_tree_kruskal import kruskal
def __lowercase ( ) ->List[str]:
"""simple docstring"""
lowercase : Optional[Any] = 9
lowercase : List[str] = [
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
... | 173 |
def __lowercase ( _UpperCamelCase, _UpperCamelCase ) ->list[int]:
"""simple docstring"""
lowercase : Dict = int(_UpperCamelCase )
# Initialize Result
lowercase : Union[str, Any] = []
# Traverse through all denomi... | 173 | 1 |
from __future__ import annotations
import math
def __snake_case ( _UpperCAmelCase , _UpperCAmelCase ):
__a = u
for i in range(1 , _UpperCAmelCase ):
__a = temp * (u - i)
return temp
def __snake_case ( ):
__a = in... | 49 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowercase ( _A , _A , _A ) -> int:
SCREAMING_SNAKE_CASE : Optional[Any] = {
"""en""": """Machine learning is great, isn't it?""",
"""ru""": """Маши... | 245 | 0 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
__A = "\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Grisel, O. and Blond... | 2 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
__A = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the model ... | 2 | 1 |
'''simple docstring'''
import os
from pathlib import Path
def __a():
'''simple docstring'''
from torch.utils.cpp_extension import load
_lowerCAmelCase = Path(_lowerCAmelCase ).resolve().parent.parent.parent / "kernels" / "deformable_detr"
_lowerCAmelCase = [
ro... | 158 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIV... | 320 | 0 |
"""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,
AutoModelForMultipleChoi... | 361 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
log... | 45 | 0 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class UpperCamelCase__:
lowerCAmelCase__ : int = None
def snake_case__ ( self ) -> str:
A__ = ... | 221 | """simple docstring"""
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
... | 221 | 1 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
UpperCAmelCase : Any = yaml.safe_load(
"""\
name: \"\"
allow_empty: fal... | 357 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
def _A ( SCREAMING_SNAKE_CASE :... | 148 | 0 |
"""simple docstring"""
import math
import tensorflow as tf
from packaging import version
def __magic_name__ ( lowercase ):
SCREAMING_SNAKE_CASE_: Any =tf.convert_to_tensor(lowercase )
SCREAMING_SNAKE_CASE_: Optional[Any] =0.5 * (1.0 + tf.math.erf(x ... | 173 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import ... | 173 | 1 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
snake_case__ : Dict = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, do... | 274 | '''simple docstring'''
snake_case__ : str = '''Tobias Carryer'''
from time import time
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , snake_case_ , snake_case_ , snake_case_ , snake_case_=int(time() ) ): # no... | 274 | 1 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
lowerCamelCase : Dict = '\\n@article{scikit-learn,\n title={Scikit-learn: Machine Learning in {P}ython},\n author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.\n and Thirion, B. and Gri... | 2 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowerCamelCase : str = Mapping[str, np.ndarray]
lowerCamelCase : List[Any] = Mapping... | 2 | 1 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
__UpperCamelCase : Tuple = logging.get_logger(__name__)
class __magic_name__ :
def __init__( self : ... | 355 |
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__UpperCamelCase : List[Any] = pytest.mark.integration
@pytest.mark.parametrize('''path''' , ... | 51 | 0 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
lowercase : List[Any] = logging.getLogger()
@unittest.skip('''Temporarily disable t... | 99 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ : str = "The quick brown fox jumps over the lazy dog" , ) -> bool:
__a = set()
# Replace all the whitespace in our sentence
__a = input_str.replace(''' ''' , '''''' )
for a... | 45 | 0 |
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeat... | 371 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_CO... | 155 | 0 |
'''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''', da... | 70 |
"""simple docstring"""
import sys
from collections import defaultdict
class lowerCamelCase__ :
def __init__( self ):
"""simple docstring"""
snake_case : Dict = []
def lowerCamelCase_ ( self , SCREAMING_SNAKE_CASE ):... | 148 | 0 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase__ ( a__ , a__ , a__ ) ->int:
'''simple docstring'''
_UpperCame... | 63 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'''ut/deta''': '''https://huggingface.co/ut/deta/resolve/main/config.json''',
}
class _UpperC... | 63 | 1 |
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
A : Union[str, Any] = ... | 274 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from tra... | 274 | 1 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class snake_case__ (A__ ,... | 368 |
from __future__ import annotations
def lowerCAmelCase_ ( _lowercase : float , _lowercase : float , _lowercase : float , ) -> tuple[str, float]:
"""simple docstring"""
if (stress, tangential_force, area).count(0)... | 266 | 0 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _a ( ):
__lowerCAmelCase = ArgumentParser(
description=(
"PyTorch TPU distributed training launch... | 92 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class __snake_case :
pass
| 51 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPExcept... | 350 |
"""simple docstring"""
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from a... | 38 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class UpperCAmelCase__ ( A_ ):
"""simple ... | 62 |
"""simple docstring"""
import argparse
import json
from tqdm import tqdm
def lowercase () -> Dict:
'''simple docstring'''
lowerCAmelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"""--src_path""" , type=s... | 155 | 0 |
def __UpperCamelCase ( _A , _A , _A , _A , _A , ):
lowerCAmelCase_ = [redshift, radiation_density, matter_density, dark_energy]
if any(p < 0 for p in parameters ):
raise ValueError('''All input parameters must be positive''' )
if any(p > 1 for p in par... | 362 |
_A = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kilocalorie_nutr": 4_186_800.00,
"electronvolt": 1.602... | 167 | 0 |
'''simple docstring'''
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : int , __a : Union[str, Any] ):
# we need a list not a string, so do something to change the type
_a = arr.split("," )
de... | 63 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCAmelCase_ : int = {'configuration_gpt_neox': ['GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPT... | 63 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmark... | 358 |
"""simple docstring"""
def UpperCAmelCase ( a_ ):
'''simple docstring'''
lowerCamelCase : List[Any] = 1
for i in range(1, num + 1 ):
fact *= i
return fact
def UpperCAmelCase ( a_ ):
'''simple docstring'''
lowerCamelCa... | 205 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ : List[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ : int = {
'google/realm-cc-news-pretrained-embedder': (
'https:... | 335 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 266 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils impor... | 312 | """simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggingface.co/CarlCochet/... | 312 | 1 |
"""simple docstring"""
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
lowerCamelCase_ : Tuple = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create ... | 81 |
import argparse
import json
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import... | 38 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __SCREAMING_SNAKE_CASE ( __lowercase):
_SCREAMING_SNAKE_CASE : int = '''ClapFeatureExtractor'''
_SCREAMING_SNAKE_CASE : Any = ('''RobertaTokenizer''', '''Robert... | 122 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require... | 122 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowerCAmelCase_ = {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''... | 8 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
_lowerCamelCa... | 167 | 0 |
"""simple docstring"""
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_par... | 144 |
"""simple docstring"""
import numpy
# List of input, output pairs
_a = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
_a = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_50))
_a = [2, 4, 1, 5]
_a = len(... | 144 | 1 |
'''simple docstring'''
def UpperCamelCase__ ( lowerCAmelCase = 1_00 ):
"""simple docstring"""
_lowerCAmelCase = set()
_lowerCAmelCase = 0
_lowerCAmelCase = n + 1 # maximum limit
... | 70 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import Te... | 205 | 0 |
def a_ ( __lowercase : int ) -> str:
_snake_case = int(__lowercase )
if decimal in (0, 1): # Exit cases for the recursion
return str(__lowercase )
_snake_case , _snake_case = divmod(__lowercase , 2 )
return binary_recursive(__lowercase ) + str... | 130 |
import baseaa
def a_ ( __lowercase : str ) -> bytes:
return baseaa.aaaencode(string.encode('utf-8' ) )
def a_ ( __lowercase : bytes ) -> str:
return baseaa.aaadecode(__lowercase ).decode('utf-8' )
if __name__ == "__main__":
import doctest
doctest.tes... | 130 | 1 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_full... | 312 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore,
)
fr... | 312 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
lowerCAmelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class lower... | 52 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_ava... | 52 | 1 |
class lowercase_ :
def __init__( self , __UpperCamelCase , __UpperCamelCase=None , __UpperCamelCase=None ):
"""simple docstring"""
UpperCamelCase_ = data
UpperCamelCase_ = previous
UpperCamelCase_ = next_node
def _... | 122 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Dist... | 122 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
... | 357 | from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class a__ ( ... | 197 | 0 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@d... | 144 |
"""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.serialization... | 144 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https:/... | 341 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase(__UpperCamelCase ) -> bool:
_lowerCAmelCase =str(__UpperCamelCase )
return n == n[::-1]
def _lowerCamelCase(__UpperCamelCase = 1000000 ) -> str:
_lowerCAmelCase =0
for i in range(1 ... | 341 | 1 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common i... | 130 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.utils impo... | 130 | 1 |
import sys
a_ : int = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'6689664895044524452316173185640309871112172238... | 351 |
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require_torchaudio
@require... | 327 | 0 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Dict = logging.get_logger(__name__)
__lowerCamelCase : Optional[int] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-base... | 52 |
from math import sqrt
def A_ ( _lowerCAmelCase ) -> bool:
assert isinstance(_lowerCAmelCase , _lowerCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
UpperCamelCase : List[Any] = True
# 0 and 1 are none primes.
if number <= 1:
Upp... | 52 | 1 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
a__ : int = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Th... | 370 |
"""simple docstring"""
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
def UpperCAmelCase__ (lowerCAmelCase_ ... | 195 | 0 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Any = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/confi... | 3 | """simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def UpperCAmelCase__ ( lowerCAmelCase__ :int ) -> str:
'''simple docstring'''
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise TypeErr... | 197 | 0 |
def a__ ( UpperCAmelCase : int ) -> None:
UpperCAmelCase : Optional[Any] = generate_pascal_triangle(UpperCAmelCase )
for row_idx in range(UpperCAmelCase ):
# Print left spaces
for _ in range(num_rows - row_idx - 1 ):
print(end=''' ''' ... | 370 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def a__ ( UpperCAmelCase : int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCAmelCase : float , Upper... | 99 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
#... | 341 |
'''simple docstring'''
from math import factorial, radians
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 18 , _SCREAMING_SNAKE_CASE = 10 ):
_snake_case = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from... | 341 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a :Dict = logging.get_logger(__name__)
__a :int = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json'
),
'goo... | 329 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_... | 170 |
from __future__ import annotations
from collections import namedtuple
def SCREAMING_SNAKE_CASE__ ( __a , __a , __a ):
snake_case_ : Any = namedtuple('result' , 'name value' )
if (voltage, current, power).count(0 ) != 1:
rais... | 327 | 0 |
import math
import sys
def lowerCamelCase ( a_ ) -> int:
if number != int(lowercase__ ):
raise ValueError('the value of input must be a natural number' )
if number < 0:
raise ValueError('the value of input must not be... | 351 |
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_utils import (... | 14 | 0 |
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'The `image_to_image.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionImg2ImgPipeline` instead.'
)
| 205 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
UpperCAmelCase = logging.get_logger(__name__)
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
lowercase = r'\w+[.]\d+'
... | 195 | 0 |
'''simple docstring'''
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def _a ( _lowercase : str , _lowercase : Any=False ):
'''simple docstring'''
__UpperCAmelCase... | 240 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _a ( ):
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = ArgumentParser('''Diffusers CLI tool''' , usage='''diffuse... | 240 | 1 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( __UpperCAmelCase ):
def __init__( self , A_ , A_ = None , ... | 222 |
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
lowercase : List[str] = """src/transformers"""
lowercase : ... | 99 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase : int = {"UserAgent": UserAgent().random}
def UpperCAmelCase_ (_lowerCAmelCase : Any ):
__UpperCamelCase : Optional[Any] ... | 171 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowercase : Dict = (720, 1280) # Height, Width
lowercase : Any = (0.4, 0.6) # if height or width lower than this scale, drop it.
lowercase : Tuple ... | 171 | 1 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
_a = logging.get_logger(__name__)
class A_ ( snake_case__ ):
def __init__( self : Union[str, Any] , *UpperCAmelCase : Any , **UpperCAmelCase ... | 322 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stable... | 322 | 1 |
"""simple docstring"""
import unittest
from knapsack import greedy_knapsack as kp
class __UpperCAmelCase( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self ):
'''simple docstring'''
lowercase__ : List[Any... | 366 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
a : Any = get_logger(__name__)
a : Any = r"""
Args:
input_ids (`j... | 150 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
SCREAMING_SNAKE_CASE_: int =logging.get_logger(__name__)
class __A ( UpperCamelCase__ ):
def __init__(self : Optional[int] , *__a : Optional[Any... | 1 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> Dict:
"""simple docstring"""
A__ = args.pruning_method
A__ = ar... | 14 | 0 |
def __lowerCamelCase ( __a :float , __a :int ) -> float:
"""simple docstring"""
if digit_amount > 0:
return round(number - int(_SCREAMING_SNAKE_CASE ) , _SCREAMING_SNAKE_CASE )
return number - int(_SCREAMING_SNAKE_CASE )
if __... | 351 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
A : Dict = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies # noqa: E402
# This is... | 276 | 0 |
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class snake_case_ (lowerCamelCase_ ):
UpperCAmelCa... | 240 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
snake_case : Dict = logging.get_logger(__name__)
sn... | 240 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__A : Tuple = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__A : int = [file for file in filepaths if file != file.lower()... | 49 |
from math import pi, sqrt
def __UpperCamelCase ( _A : float ) ->float:
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
if num > 1_7_1.5:
raise OverflowError("""math range error""" )
elif... | 49 | 1 |
"""simple docstring"""
def a__ ( lowerCAmelCase , lowerCAmelCase ) -> list:
UpperCAmelCase__ : int = len(lowerCAmelCase )
UpperCAmelCase__ : Optional[int] = []
for i in range(len(lowerCAmelCase ) - pat_len + 1 ):
UpperCAmelCase__ ... | 171 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPEN... | 171 | 1 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
lowerCamelCase__ = get_logger(__name__)
lowerCamelCase__ = R'''
Args:
input_ids (`jnp.ndarray` of shape `(batch_size, sequence_length)... | 356 | import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenizer, FlaxMTaFo... | 63 | 0 |
'''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():
... | 3 | """simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def lowerCAmelCase__ ( _UpperCamelCase : Any="ro" , _UpperCamelCase : Optional[Any]="en" , _UpperCamelCase : Any="wmt16" , _UpperCamelCase : Tuple=None ) -> None:
... | 150 | 0 |
'''simple docstring'''
from math import factorial, pi
def _A ( _lowerCAmelCase , _lowerCAmelCase = 30 ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , (int, float) ):
raise ValueError('maclaurin_sin() requires either an int or float f... | 48 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from typing import Any
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : List[Any]):
'''simple docstring'''
__lowercase =[]
... | 48 | 1 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils... | 60 |
'''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... | 276 | 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 ... | 226 |
"""simple docstring"""
def lowercase ( A_ , A_ )-> float:
'''simple docstring'''
def get_matched_characters(A_ , A_ ) -> str:
a : Optional[int] = []
a : List[Any] = min(len(_stra ) , len(_st... | 226 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__snake_case :Tuple = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Wav2Vec... | 49 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 49 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
... | 241 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase__ ( metaclass=SCREAMING_SNAKE_CASE ):
'''simple docstring'''
UpperCamelCase = ['''flax''']
def __init__( self : Tuple , *_... | 241 | 1 |
from ....utils import logging
_snake_case = logging.get_logger(__name__)
class _snake_case ( lowerCamelCase_ ):
def __init__( self: Tuple , __lowerCamelCase: int , __lowerCamelCase: Any=None , __lowerCamelCase: Optional[int]=20_48 ) -> List[Any]:
__U... | 157 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int ) -> bool:
if num < 0:
return False
_a = num
_a = 0
while num > 0:
_a = rev_num * 10 + (num % 10)
num //= 10
return num_copy == rev_num
if __name__ == "__main... | 63 | 0 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
A__ : Optional[Any] = ''''''
A__ : Optional[int] = ''''''
A__ : List[str] = ''''''
A__ : Union[str, Any] = ''''''
def a_ ( _UpperCAmelCase : str ) -> ... | 0 |
'''simple docstring'''
def a_ ( _UpperCAmelCase : int ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
__snake_case... | 0 | 1 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__)
SCREAM... | 48 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCAmelCase__ ... | 48 | 1 |
'''simple docstring'''
from sklearn.metrics import mean_squared_error
import datasets
a : int = """\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and ... | 354 |
'''simple docstring'''
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampl... | 338 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase__ ( __UpperCamelCase ):
'''simple docstring'''
@staticmethod
@abstractmethod
def snake_case__ ( a_ : ArgumentParser ):
'''simple docstring'''
... | 226 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class UpperCAmelCase__ :
'''simple docstring'''
UpperCamelCase = None
def snake_case__ ( self : List[str] ):
'''sim... | 226 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltFor... | 203 | """simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
lowercase__ = '2.13.1'
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('3.7'):
raise... | 203 | 1 |
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