code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import pprint
import requests
_A: Tuple = 'https://zenquotes.io/api'
def _lowerCAmelCase ( )-> Dict:
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def _lowerCAmelCase ( )-> str:
return requests.get(API_ENDPOINT_URL + '/... | 711 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , )-> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less t... | 617 | 0 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> ... | 712 |
'''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 TokenizerTesterMixin
@r... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_A: Optional[Any] = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if n... | 713 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if not nums:
return 0
__UpperCAmelCase = nums[0]
__UpperCAmelCase = 0
for num in nums[1:]:
__UpperCAmelCase , __UpperCAmelCase = (
max_excludin... | 617 | 0 |
'''simple docstring'''
import math
import sys
def _lowerCAmelCase ( _lowerCAmelCase )-> Tuple:
'''simple docstring'''
__UpperCAmelCase = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
__UpperCAmelCase = binary_file.read()
for dat in d... | 714 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase ( _lowerCAmelCase = 3 )-> qiskit.result.counts.Counts:
if isinstance(_lowerCAmelCase , _lowerCAmelCase ... | 617 | 0 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
_A: Optional[int] = [
# tf -> hf
("/", "."),
("layer_", "layers."),
(... | 715 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A: int = logging.getLogger(__name__)
class UpperCAmelCase :
def __init__( self ... | 617 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json""",
... | 716 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Optional[Any] = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggi... | 617 | 0 |
'''simple docstring'''
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCAmelCase :
pass
| 717 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffus... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase = 1 , _lowerCAmelCase = 10_00 )-> int:
__UpperCAmelCase = 1
__UpperCAmelCase = 0
for divide_by_number in range(a_ , digit + 1 ):
__UpperCAmelCase = []
__UpperCAmelCase = numerator
... | 718 |
'''simple docstring'''
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_config... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
'''configuration_roformer''': ['''ROFORMER_PRETRAINE... | 719 |
'''simple docstring'''
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 Generatio... | 617 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_A: Dict = logging.get_logger(__name__)
_A: List[str] = {
"""kssteven/ibert-roberta-... | 720 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str | Literal[False]:
__UpperCAmelCase = list(_lowerCAmelCase )
__UpperCAmelCase ... | 617 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
_A: Optional[int] = logging.get_logger(__name__)
class UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
def __init__( self , *__A , ... | 721 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
"""configuration_whisper""": ["""WHISPER_PRETRA... | 617 | 0 |
'''simple docstring'''
_A: Tuple = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loade... | 700 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 617 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_A: Any = logging.get_logger(__name__)
# TODO: upload to AWS
_A: List[Any] = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokeni... | 617 | 0 |
'''simple docstring'''
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_... | 702 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : List[Any] = """timm_backbone"""
def __init__( self ,... | 617 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_A: Tuple = logging.get_logger(__name__)
_A: Any = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-Attention-Network/van-base/blob/main/co... | 703 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_A: Union[s... | 617 | 0 |
'''simple docstring'''
import os
import sys
_A: int = os.path.join(os.path.dirname(__file__), """src""")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSeque... | 704 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 617 | 0 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
_A: Optional[int] = """htt... | 705 |
'''simple docstring'''
from collections.abc import Sequence
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> float:
return sum(c * (x**i) for i, c in enumerate(_lowerCAmelCase ) )
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase = 10_00 )-> Dict:
return sum(e for e in range(3 , snake_case__ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F"""{solution() = }""")
| 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: List[str] = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/conf... | 617 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_ut... | 707 |
'''simple docstring'''
from string import ascii_uppercase
_A: Union[str, Any] = {char: i for i, char in enumerate(ascii_uppercase)}
_A: str = dict(enumerate(ascii_uppercase))
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAm... | 617 | 0 |
'''simple docstring'''
from __future__ import annotations
_A: str = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
_A: List[Any] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def _lowerCAmelCase ( _lowerCAmelCase )-> list[float]:
_... | 708 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_A: Tuple = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
... | 617 | 0 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_A: Optional[int] = '''src/transformers'''
_A... | 709 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_A: List[str] = logging.... | 617 | 0 |
'''simple docstring'''
import logging
from transformers import PretrainedConfig
_A: Tuple = logging.getLogger(__name__)
_A: Dict = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json'... | 710 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 617 | 0 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
_A: int = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""enhancement""",
"""new pipeline/model""",
"""new scheduler""",
"""wip""",
]
... | 711 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , )-> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less t... | 617 | 0 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> int:
__UpperCAmelCase = [0] * no_of_processes
__UpperCAmelCase = [0] * no_of_processes
#... | 712 |
'''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 TokenizerTesterMixin
@r... | 617 | 0 |
'''simple docstring'''
class UpperCAmelCase :
def __init__( self ):
__UpperCAmelCase = ''
__UpperCAmelCase = ''
__UpperCAmelCase = []
def __lowerCamelCase ( self , __A , __A ):
if m == -1:
return n + 1
e... | 713 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if not nums:
return 0
__UpperCAmelCase = nums[0]
__UpperCAmelCase = 0
for num in nums[1:]:
__UpperCAmelCase , __UpperCAmelCase = (
max_excludin... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase )-> List[str]:
'''simple docstring'''
__UpperCAmelCase = 0
# if input_string is "aba" than new_input_string become "a|b|a"
__UpperCAmelCase = """"""
__UpperCAmelCase = """"""
# append each character + ... | 714 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase ( _lowerCAmelCase = 3 )-> qiskit.result.counts.Counts:
if isinstance(_lowerCAmelCase , _lowerCAmelCase ... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> int:
return x if y == 0 else greatest_common_divisor(SCREAMING_SNAKE_CASE_ , x % y )
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> int:
return... | 715 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A: int = logging.getLogger(__name__)
class UpperCAmelCase :
def __init__( self ... | 617 | 0 |
'''simple docstring'''
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward... | 716 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Optional[Any] = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggi... | 617 | 0 |
'''simple docstring'''
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def _lowerCAmelCase ( ... | 717 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffus... | 617 | 0 |
'''simple docstring'''
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 UpperCAmelCase ( UpperCAmelCase__ ):
de... | 718 |
'''simple docstring'''
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_config... | 617 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCAmelCase ( __a ):
_A : U... | 719 |
'''simple docstring'''
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 Generatio... | 617 | 0 |
'''simple docstring'''
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,
Dist... | 720 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str | Literal[False]:
__UpperCAmelCase = list(_lowerCAmelCase )
__UpperCAmelCase ... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase )-> str:
if length <= 0 or not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(_UpperCamelCase )]
if __name__ ==... | 721 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
"""configuration_whisper""": ["""WHISPER_PRETRA... | 617 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Dict = {
"""facebook/xlm-... | 700 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: Union[str, Any] = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable(... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokeni... | 617 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCAmelCase ( metaclass=__snake_case ):
_A : List[Any] = ["""torch""", """transformers""", """onnx"""]
def __init__( self , *__A , **__A ):
requires_backends(s... | 702 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : List[Any] = """timm_backbone"""
def __init__( self ,... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> Dict:
if len(lowerCAmelCase_ ) != len(lowerCAmelCase_ ):
raise ValueError('String lengths must match!' )
__UpperCAmelCase = 0
for chara, chara in zip(lowerCAmelCase_ , lower... | 703 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_A: Union[s... | 617 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> Union[str, Any]:
__UpperCAmelCase = list(SCREAMING_SNAKE_CASE__ )
__UpperCAmelCase ... | 704 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: Dict = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailabl... | 705 |
'''simple docstring'''
from collections.abc import Sequence
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> float:
return sum(c * (x**i) for i, c in enumerate(_lowerCAmelCase ) )
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase... | 617 | 0 |
'''simple docstring'''
import math
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
__UpperCAmelCase = [True] * n
__UpperCAmelCase = False
__UpperCAmelCase = False
__UpperCAmelCase = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
__... | 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: List[str] = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/conf... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase )-> str:
__UpperCAmelCase = []
__UpperCAmelCase = []
__UpperCAmelCase = {
"^": 3,
"*": 2,
"/": 2,
"%": 2,
"+": 1,
"-": 1,
} # Priority of each operator
__UpperCAmelCase = len... | 707 |
'''simple docstring'''
from string import ascii_uppercase
_A: Union[str, Any] = {char: i for i, char in enumerate(ascii_uppercase)}
_A: str = dict(enumerate(ascii_uppercase))
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAm... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase = 60_08_51_47_51_43 )-> int:
try:
__UpperCAmelCase = int(__UpperCamelCase )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter ... | 708 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_A: Tuple = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
... | 617 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
... | 709 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_A: List[str] = logging.... | 617 | 0 |
'''simple docstring'''
from math import loga
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if a < 0:
raise ValueError('Input value must be a positive integer' )
elif isinstance(snake_case_ , snake_case_ ):
raise TypeError('Input value must be a \'int\' type' )
return... | 710 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 617 | 0 |
'''simple docstring'''
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_py... | 711 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , )-> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less t... | 617 | 0 |
'''simple docstring'''
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditio... | 712 |
'''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 TokenizerTesterMixin
@r... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAmelCase = len(__snake_case )
__UpperCAmelCase = len(__snake_case )
__UpperCAmelCase = (
first_str_length if first_str_length > second_str_length else second... | 713 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if not nums:
return 0
__UpperCAmelCase = nums[0]
__UpperCAmelCase = 0
for num in nums[1:]:
__UpperCAmelCase , __UpperCAmelCase = (
max_excludin... | 617 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
... | 714 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase ( _lowerCAmelCase = 3 )-> qiskit.result.counts.Counts:
if isinstance(_lowerCAmelCase , _lowerCAmelCase ... | 617 | 0 |
'''simple docstring'''
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> Optional[int]:
__UpperCAmelCas... | 715 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A: int = logging.getLogger(__name__)
class UpperCAmelCase :
def __init__( self ... | 617 | 0 |
'''simple docstring'''
import os
def _lowerCAmelCase ( )-> Optional[Any]:
with open(os.path.dirname(_UpperCAmelCase ) + '/grid.txt' ) as f:
__UpperCAmelCase = [] # noqa: E741
for _ in range(20 ):
l.append([int(_UpperCAmelCase ) for x in f.readline().split()] )... | 716 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Optional[Any] = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggi... | 617 | 0 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class UpperCAmelCase ( U... | 717 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffus... | 617 | 0 |
'''simple docstring'''
class UpperCAmelCase :
def __init__( self ):
__UpperCAmelCase = {}
def __lowerCamelCase ( self ):
print(self.vertex )
for i in self.vertex:
print(__A , ' -> ' , ' -> '.join([str(__A ) for j in self.ve... | 718 |
'''simple docstring'''
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_config... | 617 | 0 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
_A: Optional[int] = 6_378_137.0
_A: Optional[Any] = 6_356_752.314_245
_A: Optional[Any] = 6_378_137
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _l... | 719 |
'''simple docstring'''
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 Generatio... | 617 | 0 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
... | 720 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str | Literal[False]:
__UpperCAmelCase = list(_lowerCAmelCase )
__UpperCAmelCase ... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: Union[str, Any] = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONF... | 721 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
"""configuration_whisper""": ["""WHISPER_PRETRA... | 617 | 0 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_A: List[Any] = logging.get_logger(__name__)
_A: List[Any] = {
"""CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
"""https://huggingface.co... | 700 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 617 | 0 |
'''simple docstring'''
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_s... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokeni... | 617 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: int = logging.get_logger(__name__)
_A: Optional[Any] = {
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrai... | 702 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : List[Any] = """timm_backbone"""
def __init__( self ,... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase = 1 , _lowerCAmelCase = 10_00 )-> int:
__UpperCAmelCase = 1
__UpperCAmelCase = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE_ , digit + 1 ):
__UpperCAmelCase = []
__UpperCAmelCase ... | 703 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_A: Union[s... | 617 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( __A ):
def __init__( self , *__A , **__A ):
warnings... | 704 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: int = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Op... | 705 |
'''simple docstring'''
from collections.abc import Sequence
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> float:
return sum(c * (x**i) for i, c in enumerate(_lowerCAmelCase ) )
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase... | 617 | 0 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class UpperCAmelCase ( unittest.TestCase ):
def __lowerCamelCase ( self ):
__UpperCAmelCase = get_activation('swish' )
... | 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: List[str] = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/conf... | 617 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
_A: Any = False
class UpperCAmelCase ( unittest.TestCas... | 707 |
'''simple docstring'''
from string import ascii_uppercase
_A: Union[str, Any] = {char: i for i, char in enumerate(ascii_uppercase)}
_A: str = dict(enumerate(ascii_uppercase))
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAm... | 617 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
_A: Optional[int] = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for T... | 708 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_A: Tuple = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
... | 617 | 0 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
_A: Dict = logging.getLogger(__name__)
@dataclass
class UpperCAmelCase ( lowerCAmelCa... | 709 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_A: List[str] = logging.... | 617 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: int = logging.get_logger(__name__)
_A: str = {
'asapp/sew-tiny-100k': 'https://huggingface.co/asapp/sew-tiny-100k/resolve/main/config.json',
... | 710 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 617 | 0 |
'''simple docstring'''
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_A: Any = logging.get_logger(__name__)
class UpperCAmelCase ( snake_case__ ):
_A : List[Any... | 711 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , )-> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less t... | 617 | 0 |
'''simple docstring'''
import qiskit
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> qiskit.result.counts.Counts:
__UpperCAmelCase = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
__UpperCAmelCase = qi... | 712 |
'''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 TokenizerTesterMixin
@r... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_A: List[Any] = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try... | 713 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if not nums:
return 0
__UpperCAmelCase = nums[0]
__UpperCAmelCase = 0
for num in nums[1:]:
__UpperCAmelCase , __UpperCAmelCase = (
max_excludin... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> Optional[Any]:
'''simple docstring'''
if height >= 1:
move_tower(height - 1 , A__ , A__ , A__ )
move_disk(... | 714 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase ( _lowerCAmelCase = 3 )-> qiskit.result.counts.Counts:
if isinstance(_lowerCAmelCase , _lowerCAmelCase ... | 617 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_A: Dict = logging.get_logger(__name__)
_A: Union[str, Any] = {
"""xlm-mlm-en-... | 715 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A: int = logging.getLogger(__name__)
class UpperCAmelCase :
def __init__( self ... | 617 | 0 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
# TODO Update this
_A = {
"""facebook/esm-1b""": """https://huggingface.co/f... | 716 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Optional[Any] = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggi... | 617 | 0 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOC... | 717 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffus... | 617 | 0 |
'''simple docstring'''
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
_A: Union[str, Any] = get_logger(__name__)
class UpperCAmelCase ( enum.Enum ):
_A : List[Any] = 'all_... | 718 |
'''simple docstring'''
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_config... | 617 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class Upp... | 719 |
'''simple docstring'''
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 Generatio... | 617 | 0 |
'''simple docstring'''
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *_lowerCAmelCase )-> Any:
if not isinstance(__a , __a ):
__UpperCAmelCase = list(__a )
for i in rang... | 720 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str | Literal[False]:
__UpperCAmelCase = list(_lowerCAmelCase )
__UpperCAmelCase ... | 617 | 0 |
'''simple docstring'''
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def _lowerCAmelCase ( _lowerCAmelCase = True , *_lowerCAmelCase , **_lowerCAmelCase )-> Optional[int]:
... | 721 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
"""configuration_whisper""": ["""WHISPER_PRETRA... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase = 10**9 )-> int:
__UpperCAmelCase = 1
__UpperCAmelCase = 2
__UpperCAmelCase = 0
__UpperCAmelCase = 0
__UpperCAmelCase = 0
while perimeter <= max_perimeter:
perimeters_sum += perimeter
prev_va... | 700 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 617 | 0 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
from .feature_extraction_wavaveca import WavaVecaFeatureExtractor
from .tokenization_wavaveca import WavaVecaCTCTokenizer
class UpperCAmelCase ( __UpperCAmelCase ):
... | 701 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: List[str] = {
"""configuration_luke""": ["""LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LukeConfig"""],
"""tokenization_luke""": ["""LukeTokeni... | 617 | 0 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
_A: Union[str, Any] = logging.get_logger... | 702 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : List[Any] = """timm_backbone"""
def __init__( self ,... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP", "... | 703 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_A: Union[s... | 617 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def _lowerCAmelCase ( _... | 704 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 617 | 0 |
'''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EXTRACTOR_MAPPING,
AutoConfig,
AutoFeatureExtractor,
WavaVecaConfig,
WavaVecaFeatureExtractor,
)
from transform... | 705 |
'''simple docstring'''
from collections.abc import Sequence
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> float:
return sum(c * (x**i) for i, c in enumerate(_lowerCAmelCase ) )
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase... | 617 | 0 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
_A: Tuple = logging.getLogger(__name__)
_A: Optional[int... | 706 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: List[str] = {
"""weiweishi/roc-bert-base-zh""": """https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/conf... | 617 | 0 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
_A: List[Any] = logging.get_logger(__name... | 707 |
'''simple docstring'''
from string import ascii_uppercase
_A: Union[str, Any] = {char: i for i, char in enumerate(ascii_uppercase)}
_A: str = dict(enumerate(ascii_uppercase))
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAm... | 617 | 0 |
'''simple docstring'''
import warnings
warnings.warn(
"""memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: """
"""`from accelerate import find_executable_batch_size` to avoid this warning.""",
FutureWarning,
)
| 708 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_A: Tuple = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
... | 617 | 0 |
'''simple docstring'''
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_config... | 709 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_A: List[str] = logging.... | 617 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool
if TYPE_CHECKING:
from PIL import Image
class UpperCAmelCase ( a__ ):
_A : Tuple = "Salesforce/b... | 710 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 617 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertT... | 711 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , )-> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less t... | 617 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_au... | 712 |
'''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 TokenizerTesterMixin
@r... | 617 | 0 |
'''simple docstring'''
_A: Any = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def _lowerCAmelCase ( _lowerCAmelCase )-> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(a_ , a_ ):
__UpperCAmelCase = ... | 713 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if not nums:
return 0
__UpperCAmelCase = nums[0]
__UpperCAmelCase = 0
for num in nums[1:]:
__UpperCAmelCase , __UpperCAmelCase = (
max_excludin... | 617 | 0 |
'''simple docstring'''
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@da... | 714 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _lowerCAmelCase ( _lowerCAmelCase = 3 )-> qiskit.result.counts.Counts:
if isinstance(_lowerCAmelCase , _lowerCAmelCase ... | 617 | 0 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers i... | 715 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A: int = logging.getLogger(__name__)
class UpperCAmelCase :
def __init__( self ... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase = 1_00_00_00 )-> int:
__UpperCAmelCase = set(range(3 , _UpperCamelCase , 2 ) )
primes.add(2 )
for p in range(3 , _UpperCamelCase , 2 ):
if p not in primes:
continue
prim... | 716 |
'''simple docstring'''
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Optional[Any] = {
"""huggingface/autoformer-tourism-monthly""": """https://huggingface.co/huggi... | 617 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision... | 717 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffus... | 617 | 0 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_A: Dict = False
class UpperCAmelCase ( ... | 718 |
'''simple docstring'''
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_config... | 617 | 0 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A: str = logging.getLogger(__name__)
class UpperCAmelCase :
def __init__( self ):
... | 719 |
'''simple docstring'''
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 Generatio... | 617 | 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: int = logging.get_logger(__name__)
_A: Any = {
""... | 720 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str | Literal[False]:
__UpperCAmelCase = list(_lowerCAmelCase )
__UpperCAmelCase ... | 617 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAmelCase = ''
for word_or_phrase in separated:
if not isinstance(lowerCamelCase__ , lowerCamelCase__ ):
raise Exception('join() accepts only strings to be joined' ... | 721 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: str = {
"""configuration_whisper""": ["""WHISPER_PRETRA... | 617 | 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: List[str] = logging.get_logger(__name__)
_A: Tuple ... | 700 |
'''simple docstring'''
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
... | 617 | 0 |
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