code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
B... | 65 |
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_ = logging.get_logger(__name__)
UpperCAmelCase_ = """▁"... | 2 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
raise ValueError("""multiplicative_persistence() only accepts integral values""" )
if num < 0:
... | 693 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__=None ):
'''simple docstring'''
lo... | 693 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = ... | 503 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_common import OnnxPipelineT... | 503 | 1 |
from __future__ import annotations
def __lowerCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError('days_between_payments must be > 0' )
if da... | 108 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase ( lowercase_ ):
def a ( self ):
return [
{"col_1": 3, "col_2": "a"},
{"col_1": 2, "col_2": "b"},
... | 108 | 1 |
'''simple docstring'''
def UpperCAmelCase ( A : int ):
SCREAMING_SNAKE_CASE : Tuple = []
SCREAMING_SNAKE_CASE : str = []
SCREAMING_SNAKE_CASE : str = {
'''^''': 3,
'''*''': 2,
... | 527 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_ima... | 527 | 1 |
'''simple docstring'''
def _lowerCAmelCase( UpperCAmelCase_ : List[str] , UpperCAmelCase_ : List[Any] ):
lowerCAmelCase__ = len(UpperCAmelCase_ )
print("""The following activities are selected:""" )
# The first activity is always selected
l... | 701 |
'''simple docstring'''
import argparse
import datetime
def _lowerCAmelCase( UpperCAmelCase_ : str ) -> str:
lowerCAmelCase__ = {
"""0""": """Sunday""",
"""1""": """Monday""",
"""2""": """Tuesday""",
"""3""": """Wedne... | 211 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _a ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
A :Any = ["image_processor", "tokenizer"]
A :str = "ViTImageProcessor"
... | 191 |
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention, ImageClassifierOutput... | 191 | 1 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin, SchedulerOutput
@dataclass
cl... | 714 | """simple docstring"""
import os
import sys
lowerCAmelCase_: Any = os.path.join(os.path.dirname(__file__), "src")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeq... | 668 | 0 |
from __future__ import annotations
from cmath import sqrt
def __SCREAMING_SNAKE_CASE ( lowerCAmelCase: List[Any] , lowerCAmelCase: Tuple , lowerCAmelCase: List[str] ) -> Tuple:
if a == 0:
raise ValueError("Coefficient 'a' must not be zero." )
_UpperCAmelCase : Tuple ... | 300 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
a_ = argparse.ArgumentParser()
parser.add_argument('--dump_path', default=None, type=str, required=True, help='Pa... | 25 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def __lowerCAmelCase ( lowerCamelCase : int ):
'''simple docstring'''
if num <= 0:
__lowerCAmelCase = f'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(lowerCa... | 39 |
'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __lowerCAmelCase ( lowerCamelCase : bytes , lowerCamelCase : int ):
'''simple docstring'''
__lowerCAmelCase = f''... | 39 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import Toke... | 225 |
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowerCamelCase__ = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE ( lowerCamelCase__ ):
def... | 225 | 1 |
'''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order spe... | 338 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_u... | 338 | 1 |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedulers.scheduling_... | 637 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {'''vocab_file''': '''vocab.txt'''}
__a = {
'''vocab_file''': ... | 319 | 0 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def _snake_case ( snake_case__ : int ):
return x + 2
class lowerCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def... | 714 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_... | 22 | 0 |
import requests
_lowerCamelCase : int = """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def __a ( __lowerCAmelCase ) -> None:
# fetching a list of articles in json format
SCREAMING_SNAKE_CASE : List[str] = requests.g... | 352 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_lowerCamelCase : List[str] = """\
"""
_lowerCamelCase : Optional[int] = """
Perplexity (PPL... | 352 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int, __snake_case : Optional[Any] ) -> int:
"""simple docstring"""
print("""\nThe shortest path matrix using Floyd Warshall algorithm\n""" )
for i in range(__snake_case ):
for j in range(__snake_case... | 687 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : Tuple = {
'vo... | 687 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import... | 516 | """simple docstring"""
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 On... | 516 | 1 |
"""simple docstring"""
def __lowerCamelCase ( lowerCAmelCase__ ,lowerCAmelCase__ ):
return base * power(lowerCAmelCase__ ,(exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print('''Raise base to the power of exponent using recursion...''')... | 716 |
"""simple docstring"""
import numpy as np
def __lowerCamelCase ( lowerCAmelCase__ ):
return 1 / (1 + np.exp(-vector ))
def __lowerCamelCase ( lowerCAmelCase__ ):
return vector * sigmoid(lowerCAmelCase__ )
if __name__ == "__main__":
... | 554 | 0 |
'''simple docstring'''
import requests
a__ : str = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def __lowerCamelCase ( UpperCAmelCase_ ) ->None:
# fetching a list of articles in json format
snake_case__ = reques... | 368 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher... | 368 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _SCREAMING_SNAKE_CASE ( _lowercase : Callable[[int | float], int | float] , _lowercase : int | float , _lowercase : int | float , _lowercas... | 31 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequ... | 31 | 1 |
'''simple docstring'''
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 A ( SCREAMING_SNAKE_CASE__ ):
def __init__( self :... | 48 |
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
__a : Tuple = Mapping[str, np.ndarray]
__a : int = Mapping[str, Any] ... | 397 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
def __a ( __lowerCamelCase : Optional[int] , __lowerCamelCase : int , __lowerCamelCase : Optional[int] , __lowerCamelCase : Tuple , __lowerCamelCase : Optional[Any] ) -> List[str]:
'''simp... | 703 | '''simple docstring'''
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase_ : Union[str, Any] =... | 461 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
a__ = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not use value network
... | 14 |
'''simple docstring'''
def A_ ( snake_case , snake_case ):
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
SCREAMING_SNAKE_CASE:int = str(bin(snake_case ) )[2:] # remove the leading "0b"
SCREAMING_SNAKE_CASE:Dict = str(bi... | 143 | 0 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerca... | 716 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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 util... | 343 | 0 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, ... | 189 |
'''simple docstring'''
from __future__ import annotations
from math import pi, sqrt
def a ( __a , __a ) -> tuple:
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance <= 0:
rais... | 189 | 1 |
import requests
from bsa import BeautifulSoup
def _a ( SCREAMING_SNAKE_CASE = "AAPL" ):
"""simple docstring"""
lowercase__ = f'https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'
lowercase__ = BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE ).text , '''html.par... | 719 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _a ( unittest.TestCase ):
def lowerCamelCase_ ( self: int ) -> None:
"""simple docstring... | 429 | 0 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
DistilB... | 37 |
from collections import deque
class lowerCAmelCase_ :
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : int , SCREAMING_SNAKE_CASE_ : int ):
lowerCAmelCase__ = process_name # process name
lowerC... | 668 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
def __lowerCamelCase ( _UpperCamelCase : float , _UpperCamelCase : float , _UpperCamelCase : float ):
'''simple docstring'''
UpperCAmelCase_ = namedtuple('... | 718 | '''simple docstring'''
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase ( lowerCamelCase , unittest.... | 43 | 0 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_... | 369 |
'''simple docstring'''
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_... | 369 | 1 |
def _lowercase ( a_ : Union[str, Any] ) -> List[Any]:
'''simple docstring'''
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
... | 716 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 184 | 0 |
class lowercase_ :
def __init__( self , lowercase_ , lowercase_) -> str:
a__ =name
a__ =val
def __str__( self) -> Tuple:
return F"""{self.__class__.__name__}({self.name}, {self.val})"""
def __lt__( self , ... | 20 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Optional[int] = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/re... | 694 | 0 |
from __future__ import annotations
def __lowerCamelCase ( lowerCamelCase__ ):
"""simple docstring"""
return len(set(lowerCamelCase__ ) ) == len(lowerCamelCase__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 81 |
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 81 | 1 |
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 import from_bytes, to_byt... | 80 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class A :
lowercase_ = 42
lowercase_ = 42
class A ... | 22 | 0 |
'''simple docstring'''
def snake_case_ ( a__ : List[str] ,a__ : Tuple ):
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
__lowercase = str(bin(_lowerCAmelCase ) )[2:... | 716 |
'''simple docstring'''
def snake_case_ ( a__ : int ):
"""simple docstring"""
__lowercase = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def snake_case_ ( a__ : int = 1_00 ):
... | 163 | 0 |
import unittest
import numpy as np
from datasets import load_dataset
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_to... | 55 |
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase__ :
def __init__( self : Optional[int] ) -> Optional[int]:
__lowerCamelCase = ''''''
__lowerCamelCase = ''''''
__lowerCamelCase ... | 298 | 0 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class SCREAMING_SNAKE_CASE :
'''simple docstring'''
UpperCamelCase_ : Optional[Union[str, Path]] = None
UpperCamelCase_ : bool = False
UpperCamel... | 488 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 488 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake... | 335 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
if TYPE_CHECKING:
... | 335 | 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
from ...utils.backbone_utils import BackboneConfigMixin, ... | 101 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
A = tuple[int, int]
class __lowercase :
'''simple docstring'''
def __init__( self , _UpperCAmelCase , _UpperCAmelCase ... | 101 | 1 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Tuple , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] , _lowerCAmelCase : Any ):
SCREAMING_SNAKE_CASE_ = name
SCREAMING_S... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
'''simple docstring'''
def UpperCAmelCase ( A : bytes ):
return "".join([hex(A )[2:].zfill(2 ).upper() for byte in list(A )] )
def UpperCAmelCase ( A : str ):
# Check data validity, following RFC3548
# https://www.ietf.org/rfc/rfc... | 464 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCamelCa... | 464 | 1 |
'''simple docstring'''
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from dif... | 161 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
_lowerCAmelCase = "\\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 jou... | 161 | 1 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCAmelCase__ :
"""simple docstring"""
def __init__(self , _a , _a , _a = 0 ) -> int:
lowercase_ ,lowercase_ : str = row, column
... | 708 | '''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__ ( _snake_case , unittest.TestCase ):
... | 438 | 0 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( lowerCamelCase__ , unittest.TestCase ):
__... | 313 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_co... | 313 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
__lowerCAmelCase : int = "docs/source/en/_toctree.yml"
def lowerCAmelCase ( UpperCamelCase__ : List[str] ):
"""simple docstring"""
__UpperCAmelCase = de... | 654 | '''simple docstring'''
def lowerCAmelCase ( UpperCamelCase__ : Tuple ):
"""simple docstring"""
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
__UpperCAmelCase = len(UpperCamelCase__ )
__... | 654 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"google/fnet-large": "https... | 581 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType... | 581 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
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 im... | 717 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 319 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"facebook/xlm-roberta-xl": "https://huggingface... | 469 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"facebook/vit-mae-base": "https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json",
# See all ViT MAE models at https://hugging... | 469 | 1 |
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_con... | 720 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
__magic_name__ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("", "|", "|"),
... | 391 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.nump... | 199 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( __magic_name__ ):... | 184 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import tor... | 719 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 563 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ = {
"configuration_clap": [
"CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
"ClapAudioConfig",
"ClapConfig",
"ClapTextConfig",
],
"proc... | 332 |
'''simple docstring'''
def lowerCamelCase ( _snake_case : str ):
'''simple docstring'''
return " ".join(
"".join(word[::-1] ) if len(_snake_case ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
impo... | 267 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_UpperCamelCase : Optional[int] = logging.get_logger(__name__)
_UpperCamelCase : Dict = {
"SenseTime/deformable-detr": ... | 645 | """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_ava... | 645 | 1 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.ut... | 558 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtracto... | 558 | 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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dim... | 719 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, BlipImageProcessor, B... | 149 | 0 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if i... | 482 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backb... | 482 | 1 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class _UpperCamelCase( nn.Module ):
def __init__( self : Tuple , _lowerCamelCase : int = 16 , _lowerCamelCase : int = 88 , _lowerCamelCase : Optional[int... | 328 |
from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE ) -> list[int]: # This function is recursive
"""simple docstring"""
_UpperCAmelCase : int = len(_SCREAMING_SNAKE_CASE )
# If the array contains only one elem... | 328 | 1 |
"""simple docstring"""
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase ) -> str:
"""simple docstring"""
__UpperCAmelCase : list[list[str]] = [[] for _ in range(UpperCamelCase )]
__UpperCAmelCase : Union[str, Any] ... | 77 |
def lowerCamelCase_ ( UpperCAmelCase_ : int | float | str ):
try:
lowercase : Dict = float(UpperCAmelCase_ )
except ValueError:
raise ValueError('''Please enter a valid number''' )
lowercase : str ... | 583 | 0 |
from __future__ import annotations
def __magic_name__ ( lowerCAmelCase_ = 4):
'''simple docstring'''
lowerCamelCase_ : Tuple = abs(lowerCAmelCase_) or 4
return [[1 + x + y * row_size for x in range(lowerCAmelCase_)] for y in range(lowerCAmelCase_)]
... | 702 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowerCAmelCase__ ( unittest.TestCase ):
"""... | 73 | 0 |
'''simple docstring'''
from __future__ import annotations
lowercase__ : Dict = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowercase__ : Optional[int] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def a__ ( lowercase : list[float] ... | 98 | '''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 config
# - gener... | 614 | 0 |
import warnings
from functools import wraps
from typing import Callable
def _lowerCamelCase ( A_ : Callable ) -> Callable:
'''simple docstring'''
@wraps(A_ )
def _inner_fn(*A_ : Union[str, Any] , **A_ : Tuple ):
warnings.warn(
(f'''\'{fn.__name__}... | 582 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class lowercase__( tf.keras.optimizers.schedules.LearningRateSchedule ):
''... | 582 | 1 |
"""simple docstring"""
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Un... | 555 |
"""simple docstring"""
import math
import unittest
def _UpperCamelCase ( _A ) -> bool:
"""simple docstring"""
assert isinstance(_A , _A ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
... | 555 | 1 |
'''simple docstring'''
from __future__ import annotations
class __UpperCAmelCase :
def __init__( self , _lowerCamelCase = 0 ):
lowerCAmelCase_ = key
def UpperCAmelCase_ ( self , _lowerCamelCase , _lowerCamelCase ):
assert isins... | 606 | '''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def snake_case_ ( __snake_case : Callable) -> Callable:
@wraps(__snake_case)
def _inner_fn(*__snake_case : str , **__snake_case : Optional[int]):
warnin... | 606 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProc... | 102 | """simple docstring"""
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCall... | 473 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, Bli... | 469 | from dataclasses import dataclass
from typing import Dict, Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .attention_processor import AttentionProcessor, AttnProcessor
from .mo... | 469 | 1 |
"""simple docstring"""
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
_lowerCAmelCase : List[Any] = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version(... | 438 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkp... | 438 | 1 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( snake_case ) -> Dict:
'''simple docstring'''
... | 341 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def __UpperCamelCase ( snake_case ) -> Any:
'''simple docstring'''
monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings''' , set() )
@pytest.fixture... | 341 | 1 |
'''simple docstring'''
import math
import tensorflow as tf
from packaging import version
def UpperCamelCase__ ( __magic_name__ : Tuple ) -> Tuple:
'''simple docstring'''
snake_case__ : List[Any] = tf.convert_to_tensor(__lowercase )
snake_case__ : ... | 38 |
def _a ( __lowercase = 1 , __lowercase = 1000 ) -> int:
"""simple docstring"""
__UpperCamelCase = 1
__UpperCamelCase = 0
for divide_by_number in range(__lowercase , digit + 1 ):
__UpperCamelCase = []
... | 383 | 0 |
"""simple docstring"""
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
a = models.Sequential()
... | 710 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class lowercase_ ( unittest.TestCase )... | 505 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase ( _snake_case : float ,_snake_case : int ):
'''simple docstring'''
lowercase__ = u
for i in range(1 ,_snake_case ):
lowe... | 267 |
'''simple docstring'''
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTes... | 267 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _lowe... | 703 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class _lowerCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def UpperCA... | 408 | 0 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
_A = logging.get_logger(__name__)
_A = {name: getattr(transformers, name + "Fast") for name in SLOW_TO_FAST_CONVERTERS}
def lowerCamelCase__... | 290 |
from functools import reduce
_A = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668966489504452445231617318564030987111217223831... | 290 | 1 |
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config import MAX_... | 534 |
from statistics import mean
import numpy as np
def SCREAMING_SNAKE_CASE__ ( __a , __a , __a , __a ):
snake_case_ : Optional[Any] = 0
# Number of processes finished
snake_case_ : List[str] = 0
# Displays the finished process.
# If it is 0, th... | 534 | 1 |
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowercase_ = False
lowercase_ = True
lowercase_ = False
if __name__ == "__main__":
lowercase_ = argp... | 291 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
lowercase_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenager... | 291 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
# See all CANINE models at ... | 709 |
"""simple docstring"""
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _... | 406 | 0 |
"""simple docstring"""
import argparse
import struct
import unittest
class UpperCamelCase_ :
def __init__( self : List[str] , lowerCAmelCase_ : bytes ) -> None:
UpperCAmelCase_ : Optional[Any] = data
# Initialize hash values
UpperCAmelCase_ ... | 95 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 456 | 0 |
"""simple docstring"""
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
__A : List[str] = logging.getLogger()
@unittest.skip("Temporari... | 281 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( _lowerCamelCase, _lowerCamelCase = None ) ->list[list[str]]:
"""simple docstring"""
__lowercase : List[Any] = word_bank or []
# create a table
__lowercase : int ... | 281 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class __UpperCamelCase :
def __init__( self : Any , UpperCAmelCase : int ) -> None:
lowerCAmelCase :str = num_of_nodes
lowerCAmelCase :list[list[in... | 553 |
"""simple docstring"""
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def UpperCAmelCase ( a__ , a__=None ):
'''simple docstring'''
lowerCAmelCase :str = No... | 553 | 1 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def UpperCamelCase_ ( A__ : Dict[str, torch.Tensor] ):
'''simple docstring'''
lowerCAmelCase_ : ... | 720 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
__A : Tuple = TypeVar("T")
__A : Optional[Any] = TypeVar("U")
class __snake_case ( Generic... | 398 | 0 |
"""simple docstring"""
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCal... | 180 |
'''simple docstring'''
import re
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : str ) -> bool:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[str] = re.compile(R"^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$" )
if match := re.search(SCREAMING_SNA... | 421 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( __lowerCamelCase:int ):
'''simple docstring'''
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def _lowerCAmelCase ( __lowerCamelCase:int ):
'''simple docstring'''
... | 468 |
"""simple docstring"""
def _lowerCAmelCase ( __lowerCamelCase:int = 2_0_0_0_0_0_0 ):
'''simple docstring'''
__magic_name__ = [0 for i in range(n + 1 )]
__magic_name__ = 1
__magic_name__ = 1
for i in ran... | 468 | 1 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE: int ):
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise ValueError('Input must be an integer' )
if input_num <= 0:
... | 580 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copie... | 580 | 1 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class __magi... | 226 |
def A(__a: int ):
lowerCAmelCase_ = abs(__a )
lowerCAmelCase_ = 0
while n > 0:
res += n % 10
n //= 10
return res
def A(__a: int ):
lowerCAmelCase_ = abs(__a )
return n if n < 10 else n % 10 + sum_of_digits(n // 10 )
def A(__a: int ... | 226 | 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 req... | 8 |
"""simple docstring"""
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *lowerCAmelCase ):
'''simple docstring'''
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
... | 673 | 0 |
'''simple docstring'''
import numpy as np
def a__ ( lowerCAmelCase__ ) -> np.array:
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 312 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusi... | 312 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Any =logging.get_logger(__name__)
_lowerCAmelCase : Dict ={
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/m... | 113 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
"""configuration_perceiver""": ["""PE... | 104 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase__ )
class UpperCAmelCase__ ( UpperCAmelCase__ ):
'''simple docstring'''
_SCREAMING_SNAKE_CAS... | 321 |
def lowerCamelCase ( UpperCAmelCase_ : int )-> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input ... | 321 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
def __UpperCAmelCase (lowercase__ ,lowercase__ ,lowercase__ ) -> tuple:
'''simple docstring'''
a_ = namedtuple("result" ,"name value" )
if (voltag... | 685 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational... | 685 | 1 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_availabl... | 716 |
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import (
ProphetNetForConditionalGeneration as Prop... | 81 | 0 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class lowerCamelCase__ ( datasets.BeamBasedBuilder):
"""simple docstring"""
def snak... | 2 | '''simple docstring'''
import os
import sys
import unittest
_a : Optional[int] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402... | 168 | 0 |
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test... | 688 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __SCREAMING_SNAK... | 688 | 1 |
"""simple docstring"""
import numpy
class lowerCAmelCase :
"""simple docstring"""
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> None:
'''simple docstring'''
lowerCamelCase_ = input_array
# R... | 142 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder... | 142 | 1 |
'''simple docstring'''
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
Ad... | 701 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils impo... | 470 | 0 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_... | 287 |
def _lowerCamelCase ( SCREAMING_SNAKE_CASE = 100 ):
'''simple docstring'''
A_ = 0
A_ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ ... | 203 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 707 | def UpperCamelCase ( __lowercase : list ):
'''simple docstring'''
A_ : str = len(__lowercase )
for _ in range(__lowercase ):
for i in range(_ % 2 ,arr_size - 1 ,2 ):
if arr[i + 1] < arr[i]:
A_ , A_ : Optional[Any] = a... | 70 | 0 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class __a (unittest.TestCase):
'''simple docstring'''
def _a ( self ) -> Union[str, Any]:
"""simple docstring"""
SCREAMING_SNAKE_CASE__ :... | 680 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__a : Optional[int] = 1_0
def __magic_name__ ( lowercase_ , lowercase_ , lowercase_ , low... | 606 | 0 |
import logging
from transformers import PretrainedConfig
lowercase : List[Any] = logging.getLogger(__name__)
lowercase : Tuple = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolv... | 708 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
lowercase : int = {
'''configuration_audio_spectrogram_transformer''': [
'''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 114 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowerCAmelCase = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONF... | 536 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__lowerCAmelCase = TypeVar("T")
class __SCREAMING_SNAKE_CASE (Generic[T] ):
"""simple docstring"""
def __init__( self , UpperCamel... | 536 | 1 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( lowerCamelCase__ ):
"""simple docstring"""
snake_case_ = (CMStochasticIterativeScheduler,)
snake_case_ = 1_0
... | 147 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
"""microsoft/xprophetnet-large-wiki100-cased""": (
"""https://huggingface.co/microsoft/xprophetnet-large-wiki100... | 147 | 1 |
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionScheduler
from ..... | 256 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _SCREAMING_SNAKE_CASE ( snake_case ):
lowerCamelCase_ = (CMStochasticIterativeScheduler,)
lowerCamelCase_ = 1_0
def _UpperCAmelCase ( ... | 256 | 1 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
lowerCAmelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
def __SCREAMING_SNAKE_CASE... | 675 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acceler... | 675 | 1 |
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