code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
import re
def lowerCamelCase__ ( UpperCAmelCase_ )-> list:
"""simple docstring"""
return [char.split() for char in re.split(R"[^ a-z A-Z 0-9 \s]" , str_ )]
def lowerCamelCase__ ( UpperCAmelCase_ )-> ... | 554 |
import unittest
from transformers import XLMConfig, 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_common import ModelTesterMixin, ids_te... | 124 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =42
class __SCREAMING_SN... | 692 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipe... | 124 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : int = logging.get_logger(__name__)
__UpperCamelCase : Any = {
"SCUT-DLVCLab/lilt-roberta-en-base": (
"https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main... | 248 |
import os
import numpy
import onnx
def lowerCAmelCase_ ( _snake_case : Tuple , _snake_case : int ) -> List[str]:
'''simple docstring'''
__magic_name__ : Dict = a.name
__magic_name__ : Optional[Any] = b.name
__magic_name__ : Opti... | 124 | 0 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
_a : Optional[Any] = {
"<": operator.lt,
"<=": operator.le,
"==": operator.eq,
"!=": operator.ne,
">=": operator.ge,
... | 689 |
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_determinis... | 124 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__lowerCamelCase :str = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_A... | 222 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _snake_case : int , _snake_case : Union[str, Any] ) ... | 124 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCAmelCase__ :Optional[Any] = {
"configuration_trocr": ["TROCR_PRETRAIN... | 150 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMScheduler... | 124 | 0 |
"""simple docstring"""
import string
import numpy
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return b if a == 0 else greatest_common_divisor(b % a , _snake_case )
class __l... | 480 |
# coding=utf-8
# Copyright 2020 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
#
# Unless required by applicabl... | 124 | 0 |
"""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
_lowerCAmelCase : int = logging.get_logger(__name__)
_lowerCAmelCase : str = {
"v... | 289 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 124 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMSched... | 332 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling
f... | 124 | 0 |
'''simple docstring'''
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGeneration... | 251 |
import os
import sys
import unittest
snake_case : List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_... | 124 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class a__ ( A__ ):
def __init__( self : Optional[int],_A : int,_A : L... | 216 |
from __future__ import annotations
from typing import Any
class _snake_case ( snake_case ):
pass
class _snake_case :
def __init__( self , _a ):
__magic_name__ : Any = data
__magic_name__ : Node | None = None
def __it... | 124 | 0 |
"""simple docstring"""
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def ... | 554 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxT... | 124 | 0 |
'''simple docstring'''
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
lowerCAmelCase_ : str = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
lowerCAmelCase_ : List[str] = typing.Union[n... | 692 |
import requests
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> None:
'''simple docstring'''
__magic_name__ : Any = {"Content-Type": "application/json"}
__magic_name__ : Optional[int] = requests.post(_snake_case , json={"te... | 124 | 0 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr, require_... | 248 |
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(snake_case ) , 'Tatoeba dir... | 124 | 0 |
'''simple docstring'''
import os
import sys
import unittest
_a : 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... | 689 |
import math
def lowerCAmelCase_ ( _snake_case : int ) -> int:
'''simple docstring'''
if not isinstance(_snake_case , _snake_case ):
__magic_name__ : str = F'''Input value of [number={number}] must be an integer'''
raise TypeError(_snake_case )
if number ... | 124 | 0 |
"""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_attention... | 222 |
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_ ( _snake_case : int = 1000000 , _snake_case : int = 10 ) -> int:
'''simple docstring'''
__magic_name__ : defaultdict = defaultdict(_snake_case )
for outer_width in range(3 ... | 124 | 0 |
'''simple docstring'''
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch... | 150 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
snake_case : Optional[int] = ... | 124 | 0 |
"""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 TokenizerTester... | 480 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
snake_case : int = "\\n@misc{chen2021evaluating,\n title={Evaluating Large Language... | 124 | 0 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common impo... | 289 |
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
snake_case : Optional[int] = get_logger(__name__)
snake_case : Union[str, Any] = R"\n Args:\n input_ids (`jnp.ndarray` ... | 124 | 0 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampli... | 332 |
from typing import Dict
from .base import GenericTensor, Pipeline
class _snake_case ( snake_case ):
def SCREAMING_SNAKE_CASE ( self , _a=None , _a=None , _a=None , **_a ):
if tokenize_kwargs is None:
__magic_name__ : Tuple = {}
if tr... | 124 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( a_ , a_ , a_ ) -> int:
'''simple docstring'''
if len(_snake_case ) != len(_snake_case ):
raise ValueError('The length of profit and weight must be same.' )
if max_weight <= ... | 251 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
... | 124 | 0 |
from pathlib import Path
import fire
from tqdm import tqdm
def _snake_case ( lowerCAmelCase : Optional[Any]="ro" , lowerCAmelCase : Union[str, Any]="en" , lowerCAmelCase : Any="wmt16" , lowerCAmelCase : Union[str, Any]=None ):
"""simple docstring"""
try:
im... | 216 |
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> float:
'''simple docstring'''
def get_matched_characters(_snake_case : str , _snake_case : str ) -> str:
__magic_name__ : str = []
__magic_name__ : Optional[Any] = min(len... | 124 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LIC... | 554 |
import unittest
from transformers import XLMConfig, 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_common import ModelTesterMixin, ids_te... | 124 | 0 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase_ : Optional[int] = [True] * 1_00_00_01
lowerCAmelCase_ : Tuple = 2
while i * i <= 1_00_00_00:
if seive[i]:
for j in range(i * i, 1_00_00_01, i):
lowerCAmelCase_ : ... | 692 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipe... | 124 | 0 |
from __future__ import annotations
__UpperCamelCase : Optional[Any] = list[list[int]]
# assigning initial values to the grid
__UpperCamelCase : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, ... | 248 |
import os
import numpy
import onnx
def lowerCAmelCase_ ( _snake_case : Tuple , _snake_case : int ) -> List[str]:
'''simple docstring'''
__magic_name__ : Dict = a.name
__magic_name__ : Optional[Any] = b.name
__magic_name__ : Opti... | 124 | 0 |
'''simple docstring'''
from __future__ import annotations
_a : Optional[Any] = 8.988E9 # units = N * m^s * C^-2
def _lowerCAmelCase ( lowercase , lowercase , lowercase , lowercase ) -> dict[str, float]:
__lowerCAmelCase = abs(charg... | 689 |
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_determinis... | 124 | 0 |
"""simple docstring"""
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_t... | 222 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _snake_case : int , _snake_case : Union[str, Any] ) ... | 124 | 0 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import ... | 150 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMScheduler... | 124 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a_ = {
"configuration_canine": ["CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP", "CanineConfig"],
"tokenization_canine": ["CanineTokeni... | 480 |
# coding=utf-8
# Copyright 2020 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
#
# Unless required by applicabl... | 124 | 0 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE__ : Optional[int] ) -> List[str]:
'''simple docstring'''
_UpperCAmelCase : List[str] = []
_UpperCAmelCase : Any = set({"(", "[", "{"} )
_Upper... | 289 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 124 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDE... | 332 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling
f... | 124 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
_lowerCAmelCase ... | 251 |
import os
import sys
import unittest
snake_case : List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_... | 124 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
__lowerCamelCase : List[str] = TypeVar('''T''')
class a__ ( Generic[T] ):
def __init__( self : str,_A : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : ... | 216 |
from __future__ import annotations
from typing import Any
class _snake_case ( snake_case ):
pass
class _snake_case :
def __init__( self , _a ):
__magic_name__ : Any = data
__magic_name__ : Node | None = None
def __it... | 124 | 0 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import... | 554 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxT... | 124 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : str = logging.get_logger(__name__)
lowerCAmelCase_ : Optional[Any] = {
"microsoft/biogpt": "https://huggingface.co/microsoft/biogpt/resolve/ma... | 692 |
import requests
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> None:
'''simple docstring'''
__magic_name__ : Any = {"Content-Type": "application/json"}
__magic_name__ : Optional[int] = requests.post(_snake_case , json={"te... | 124 | 0 |
import os
import sys
import unittest
__UpperCamelCase : List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_ob... | 248 |
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(snake_case ) , 'Tatoeba dir... | 124 | 0 |
'''simple docstring'''
import random
class _UpperCAmelCase :
@staticmethod
def lowerCamelCase__ ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__lowerCAmelCase = [ord(_a ) for i in text]
__lowerCAmelCase = []
__lowerCAmel... | 689 |
import math
def lowerCAmelCase_ ( _snake_case : int ) -> int:
'''simple docstring'''
if not isinstance(_snake_case , _snake_case ):
__magic_name__ : str = F'''Input value of [number={number}] must be an integer'''
raise TypeError(_snake_case )
if number ... | 124 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__lowerCamelCase :Dict = {
"config": [
"EXTERNAL_DATA_FORMAT_SIZE_LIMIT",
"OnnxConfig",
"OnnxConfigWithPast",
"OnnxSeq2SeqConfigWithPast",
"PatchingSpec",
],
"... | 222 |
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_ ( _snake_case : int = 1000000 , _snake_case : int = 10 ) -> int:
'''simple docstring'''
__magic_name__ : defaultdict = defaultdict(_snake_case )
for outer_width in range(3 ... | 124 | 0 |
'''simple docstring'''
def __lowercase (_lowercase ) -> int:
"""simple docstring"""
if not isinstance(_snake_case, _snake_case ):
raise ValueError("""multiplicative_persistence() only accepts integral values""" )
if num < 0:
raise ValueError("""multiplicative_p... | 150 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
snake_case : Optional[int] = ... | 124 | 0 |
"""simple docstring"""
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
a_ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', '''|''', '''... | 480 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
snake_case : int = "\\n@misc{chen2021evaluating,\n title={Evaluating Large Language... | 124 | 0 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
_lowerCAmelCase : int = "\\n@misc{chen2021evaluating,\n ... | 289 |
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
snake_case : Optional[int] = get_logger(__name__)
snake_case : Union[str, Any] = R"\n Args:\n input_ids (`jnp.ndarray` ... | 124 | 0 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils imp... | 332 |
from typing import Dict
from .base import GenericTensor, Pipeline
class _snake_case ( snake_case ):
def SCREAMING_SNAKE_CASE ( self , _a=None , _a=None , _a=None , **_a ):
if tokenize_kwargs is None:
__magic_name__ : Tuple = {}
if tr... | 124 | 0 |
'''simple docstring'''
import math
import qiskit
def __lowerCAmelCase ( a_ = 1 , a_ = 1 , a_ = 1 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(_snake_case , _snake_case )
or i... | 251 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
... | 124 | 0 |
import math
def _snake_case ( lowerCAmelCase : int ):
"""simple docstring"""
if not isinstance(_snake_case , _snake_case ):
SCREAMING_SNAKE_CASE_ : str = f'Input value of [number={number}] must be an integer'
raise TypeError(_snake_case )
if ... | 216 |
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> float:
'''simple docstring'''
def get_matched_characters(_snake_case : str , _snake_case : str ) -> str:
__magic_name__ : str = []
__magic_name__ : Optional[Any] = min(len... | 124 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
SCRE... | 554 |
import unittest
from transformers import XLMConfig, 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_common import ModelTesterMixin, ids_te... | 124 | 0 |
'''simple docstring'''
from math import factorial, pi
def _lowerCamelCase ( lowercase : float , lowercase : int = 30 ) -> float:
if not isinstance(_snake_case , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or flo... | 692 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipe... | 124 | 0 |
from math import factorial
__UpperCamelCase : dict[str, int] = {str(digit): factorial(digit) for digit in range(10)}
def A ( _lowercase ):
if not isinstance(_snake_case , _snake_case ):
raise TypeError('''Parameter number must be int''' )
if numbe... | 248 |
import os
import numpy
import onnx
def lowerCAmelCase_ ( _snake_case : Tuple , _snake_case : int ) -> List[str]:
'''simple docstring'''
__magic_name__ : Dict = a.name
__magic_name__ : Optional[Any] = b.name
__magic_name__ : Opti... | 124 | 0 |
'''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
_a : Optional[int] = logging.get_logger(__name__)
_a... | 689 |
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_determinis... | 124 | 0 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
__lowerCamelCase :str = "docs/source/en/_toctree.yml"
def snake_case ( UpperCamelCase__ : List[Any] ) -> Union[str, Any]:
lowerCamelCase : str = defaultdict(_snake_c... | 222 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _snake_case : int , _snake_case : Union[str, Any] ) ... | 124 | 0 |
'''simple docstring'''
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to... | 150 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMScheduler... | 124 | 0 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_avai... | 480 |
# coding=utf-8
# Copyright 2020 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
#
# Unless required by applicabl... | 124 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffu... | 289 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 124 | 0 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscrete... | 332 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling
f... | 124 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCAmelCase :int = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
... | 251 |
import os
import sys
import unittest
snake_case : List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_... | 124 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvailable()
except O... | 216 |
from __future__ import annotations
from typing import Any
class _snake_case ( snake_case ):
pass
class _snake_case :
def __init__( self , _a ):
__magic_name__ : Any = data
__magic_name__ : Node | None = None
def __it... | 124 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( UpperCAmelCase_ , UpperCAmelCase_ )-> list[list[int]]:
"""simple docstring"""
UpperCamelCase = []
create_all_state(1 , _snake_case , _snake_case ,... | 554 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxT... | 124 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : Optional[Any] ) -> Optional[int]:
if not head:
return True
# split the list to two parts
_a = head.next, head
while fast and fast.next:
_a = fast.next.next
... | 692 |
import requests
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> None:
'''simple docstring'''
__magic_name__ : Any = {"Content-Type": "application/json"}
__magic_name__ : Optional[int] = requests.post(_snake_case , json={"te... | 124 | 0 |
from math import sqrt
def A ( _lowercase ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
... | 248 |
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(snake_case ) , 'Tatoeba dir... | 124 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax ... | 689 |
import math
def lowerCAmelCase_ ( _snake_case : int ) -> int:
'''simple docstring'''
if not isinstance(_snake_case , _snake_case ):
__magic_name__ : str = F'''Input value of [number={number}] must be an integer'''
raise TypeError(_snake_case )
if number ... | 124 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase :Union[str, Any] = logging.get_logger(__name__)
__lowerCamelCase :Tuple = {
"RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/c... | 222 |
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_ ( _snake_case : int = 1000000 , _snake_case : int = 10 ) -> int:
'''simple docstring'''
__magic_name__ : defaultdict = defaultdict(_snake_case )
for outer_width in range(3 ... | 124 | 0 |
'''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 (
BnbQuantizationConf... | 150 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
snake_case : Optional[int] = ... | 124 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaF... | 480 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
snake_case : int = "\\n@misc{chen2021evaluating,\n title={Evaluating Large Language... | 124 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSe... | 289 |
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
snake_case : Optional[int] = get_logger(__name__)
snake_case : Union[str, Any] = R"\n Args:\n input_ids (`jnp.ndarray` ... | 124 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by... | 332 |
from typing import Dict
from .base import GenericTensor, Pipeline
class _snake_case ( snake_case ):
def SCREAMING_SNAKE_CASE ( self , _a=None , _a=None , _a=None , **_a ):
if tokenize_kwargs is None:
__magic_name__ : Tuple = {}
if tr... | 124 | 0 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def __lowerCAmelCase ( a_ = 100_0000 , a_ = 10 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE : defaultdict = defaultdic... | 251 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
... | 124 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
__lowerCamelCase : Dict = HfApi()
__lowerCamelCase : int = {}
# fmt: off
__lowerCamelCase : Any = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347, 1.3433,... | 216 |
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> float:
'''simple docstring'''
def get_matched_characters(_snake_case : str , _snake_case : str ) -> str:
__magic_name__ : str = []
__magic_name__ : Optional[Any] = min(len... | 124 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrai... | 554 |
import unittest
from transformers import XLMConfig, 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_common import ModelTesterMixin, ids_te... | 124 | 0 |
'''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
lowerCAmelCase_ : Tuple = logging.get_logger(__name__)
l... | 692 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipe... | 124 | 0 |
def A ( _lowercase , _lowercase , _lowercase = 0 , _lowercase = 0 ):
SCREAMING_SNAKE_CASE : List[str] = right or len(_snake_case ) - 1
if left > right:
return -1
elif list_data[left] == key:
return left
el... | 248 |
import os
import numpy
import onnx
def lowerCAmelCase_ ( _snake_case : Tuple , _snake_case : int ) -> List[str]:
'''simple docstring'''
__magic_name__ : Dict = a.name
__magic_name__ : Optional[Any] = b.name
__magic_name__ : Opti... | 124 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( lowercase , lowercase ) -> list[str]:
if nth_term == "":
return [""]
__lowerCAmelCase = int(_snake_case )
__lowerCAmelCase = int(_snake_case )
__lowerCA... | 689 |
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_determinis... | 124 | 0 |
"""simple docstring"""
def snake_case ( UpperCamelCase__ : str , UpperCamelCase__ : str ) -> float:
def get_matched_characters(UpperCamelCase__ : str , UpperCamelCase__ : str ) -> str:
lowerCamelCase : str = [... | 222 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _snake_case : int , _snake_case : Union[str, Any] ) ... | 124 | 0 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
"""split_dict""", [
SplitDict(),
SplitDict({"""train""": SplitInfo(name="""train""", num_bytes=1_337, num_examples=42, datas... | 150 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMScheduler... | 124 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
"""simple docstring"""
return int((input_a, input_a).count(0 ) != 0 )
def SCREAMING_SNAKE_CASE__ ( ):
"""simple docstring"""
... | 480 |
# coding=utf-8
# Copyright 2020 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
#
# Unless required by applicabl... | 124 | 0 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
_lowerCAmelCase : Dict = "\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER ... | 289 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 124 | 0 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 332 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling
f... | 124 | 0 |
'''simple docstring'''
def __lowerCAmelCase ( a_ , a_ ) -> int:
'''simple docstring'''
return int(input_a == input_a == 0 )
def __lowerCAmelCase ( ) -> None:
'''simple docstring'''
print('... | 251 |
import os
import sys
import unittest
snake_case : List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_... | 124 | 0 |
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 Tokenize... | 216 |
from __future__ import annotations
from typing import Any
class _snake_case ( snake_case ):
pass
class _snake_case :
def __init__( self , _a ):
__magic_name__ : Any = data
__magic_name__ : Node | None = None
def __it... | 124 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCamelCase__ ( UpperCAmelCase_ )-> Optional[Any]:
"""simple docstring"""
return ConvertCommand(
... | 554 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxT... | 124 | 0 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 692 |
import requests
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> None:
'''simple docstring'''
__magic_name__ : Any = {"Content-Type": "application/json"}
__magic_name__ : Optional[int] = requests.post(_snake_case , json={"te... | 124 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__UpperCamelCase : Union[str, Any] = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
... | 248 |
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(snake_case ) , 'Tatoeba dir... | 124 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vi... | 689 |
import math
def lowerCAmelCase_ ( _snake_case : int ) -> int:
'''simple docstring'''
if not isinstance(_snake_case , _snake_case ):
__magic_name__ : str = F'''Input value of [number={number}] must be an integer'''
raise TypeError(_snake_case )
if number ... | 124 | 0 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests... | 222 |
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase_ ( _snake_case : int = 1000000 , _snake_case : int = 10 ) -> int:
'''simple docstring'''
__magic_name__ : defaultdict = defaultdict(_snake_case )
for outer_width in range(3 ... | 124 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Paddin... | 150 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
snake_case : Optional[int] = ... | 124 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE__ ( SCREAMING_SNAKE_CASE__ : int = 1_0**9 ):
"""simple docstring"""
snake_case_ : Any = 1
snake_case_ : Optional[Any] = 2
snake_case_ : Dict = 0
snake_ca... | 480 |
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
snake_case : int = "\\n@misc{chen2021evaluating,\n title={Evaluating Large Language... | 124 | 0 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class UpperCAmelCase_ :
def __init__( self : Union[str, Any] ):
_UpperCAmelCase : Dict = ""
_UpperCAmelCase : ... | 289 |
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
snake_case : Optional[int] = get_logger(__name__)
snake_case : Union[str, Any] = R"\n Args:\n input_ids (`jnp.ndarray` ... | 124 | 0 |
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase__ = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Ind... | 332 |
from typing import Dict
from .base import GenericTensor, Pipeline
class _snake_case ( snake_case ):
def SCREAMING_SNAKE_CASE ( self , _a=None , _a=None , _a=None , **_a ):
if tokenize_kwargs is None:
__magic_name__ : Tuple = {}
if tr... | 124 | 0 |
'''simple docstring'''
_lowerCAmelCase :List[str] = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def __lowerCAmelCase ( a_ ) -> bytes:
'''simple docstring'''
if not isinstance(_snake_case , _snake_case ):
... | 251 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
... | 124 | 0 |
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 : Optional[int] = get_logger(__name__)
__lowerCamelCase : Union[str, Any] = R"\n Args:\n input_ids ... | 216 |
def lowerCAmelCase_ ( _snake_case : str , _snake_case : str ) -> float:
'''simple docstring'''
def get_matched_characters(_snake_case : str , _snake_case : str ) -> str:
__magic_name__ : str = []
__magic_name__ : Optional[Any] = min(len... | 124 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effec... | 554 |
import unittest
from transformers import XLMConfig, 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_common import ModelTesterMixin, ids_te... | 124 | 0 |
'''simple docstring'''
import os
import unicodedata
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
lowerCAmelCase_ : List[str] = ... | 692 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipe... | 124 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fai... | 248 |
import os
import numpy
import onnx
def lowerCAmelCase_ ( _snake_case : Tuple , _snake_case : int ) -> List[str]:
'''simple docstring'''
__magic_name__ : Dict = a.name
__magic_name__ : Optional[Any] = b.name
__magic_name__ : Opti... | 124 | 0 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .s... | 689 |
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_determinis... | 124 | 0 |
"""simple docstring"""
from scipy.stats import spearmanr
import datasets
__lowerCamelCase :List[str] = "\nThe Spearman rank-order correlation coefficient is a measure of the\nrelationship between two datasets. Like other correlation coefficients,\nthis one varies between -1 and +1 with 0 implying n... | 222 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCAmelCase_ ( _snake_case : int , _snake_case : Union[str, Any] ) ... | 124 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase__ :Optional[Any] = ... | 150 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMScheduler... | 124 | 0 |
"""simple docstring"""
import pytest
a_ = "__dummy_dataset1__"
a_ = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\": REPO_URL + \"wikiann-bn-train.jsonl\", \"validation\": RE... | 480 |
# coding=utf-8
# Copyright 2020 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
#
# Unless required by applicabl... | 124 | 0 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class UpperCAmelCase_ ( _UpperCamelCase ):
# to overwrite at... | 289 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 124 | 0 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase__ = "\\n\n"
UpperCAmelCase__ = "\nPerplexity (PPL) is one of the most common metrics for evaluating lang... | 332 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling
f... | 124 | 0 |
'''simple docstring'''
import string
def __lowerCAmelCase ( a_ ) -> str:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = ""
for i in sequence:
SCREAMING_SNAKE_CASE : Union[str, Any] ... | 251 |
import os
import sys
import unittest
snake_case : List[Any] = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_... | 124 | 0 |
def _snake_case ( lowerCAmelCase : str , lowerCAmelCase : int ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : list[list[str]] = [[] for _ in range(_snake_case )]
SCREAMING_SNAKE_CASE_ : str = key - 1
if key <= 0:
raise ValueEr... | 216 |
from __future__ import annotations
from typing import Any
class _snake_case ( snake_case ):
pass
class _snake_case :
def __init__( self , _a ):
__magic_name__ : Any = data
__magic_name__ : Node | None = None
def __it... | 124 | 0 |
"""simple docstring"""
import heapq
import sys
import numpy as np
SCREAMING_SNAKE_CASE = tuple[int, int]
class __a :
def __init__( self : Tuple )-> Union[str, Any]:
"""simple docstring"""
UpperCamelCase = []
... | 554 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, FlaxT... | 124 | 0 |
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