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'''
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 |
'''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 | 1 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
_A: Optional[Any] = """
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For bina... | 617 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: str = logging.get_logger(__name__)
_A: Optional[Any] = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10... | 617 |
'''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 | 1 |
'''simple docstring'''
_A: Optional[Any] = """0.18.2"""
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_ve... | 617 |
'''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 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAmelCase = ''
for i in table:
res += inp[i - 1]
return res
def _lowerCAmelCase ( _lowerCAmelCase )-> str:
return data[1:] + data[0]
def _lowerCAmel... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils... | 617 |
'''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 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> float:
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_lowerCAmelCase ) * abs(_lowerCAmelCase )
if __name__ == "__main__":
import doct... | 617 |
'''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 | 1 |
'''simple docstring'''
from statistics import mean, stdev
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase = 3 )-> list:
__UpperCAmelCase = min(_lowerCAmelCase )
__UpperCAmelCase = max(_lowerCAmelCase )
# normalize data
return [round((x - x_min) / (... | 617 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import... | 617 |
'''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 | 1 |
'''simple docstring'''
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_A: Optional[Any] = logging.get_logger(__name__)
_A: Dict ... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
_A: Any = namedtuple(
"""_TestCommandArgs""",... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase ( UpperCAmelCase_ , unittest.TestCase ):
_A... | 617 |
'''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 | 1 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
_A: Any = True
except (ImportError, ModuleNotFoundError):
_A: List[str] = False
if NLTK_AVAILABLE:
with FileLock(""".lock""") as lock:
nltk.download("""punkt""", quiet=True)
... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def _lowerCAmelCase ( _lowerCAmelCase )-> Dict:
__UpperCAmelCase = FileLock(str(tmpdir / 'foo.lock' ) )
__UpperCAmelCase = FileLock(str(tmpdir / 'foo.lo... | 617 |
'''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 | 1 |
'''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 DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transform... | 617 |
'''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 | 1 |
'''simple docstring'''
from maths.prime_check import is_prime
def _lowerCAmelCase ( _lowerCAmelCase )-> int:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
__UpperCAmelCase = F'Input value of [number={number}] must be an integer'
raise TypeError(_lowerCAme... | 617 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A: Any = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 617 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> dict[str, float]:
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and only one argument must be 0' )... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokeniz... | 617 |
'''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 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from .... | 617 |
'''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 | 1 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from ... | 617 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
from manim import *
class UpperCAmelCase ( UpperCAmelCase_ ):
def __lowerCamelCase ( self ):
__UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
__UpperCAmelCase = Rectangle(height=0.4_6 , width=0.4_6 )... | 617 |
'''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 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> Dict:
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
__UpperCAmelCase = mf_knapsack(i - 1 , _low... | 617 |
'''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 | 1 |
'''simple docstring'''
import math
def _lowerCAmelCase ( _lowerCAmelCase )-> list[int]:
__UpperCAmelCase = []
__UpperCAmelCase = 2
__UpperCAmelCase = int(math.sqrt(_lowerCAmelCase ) ) # Size of every segment
__UpperCAmelCase = [True] * (end + 1)
__Upp... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
loggi... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pyt... | 617 |
'''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 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
_A: Any = logging.get_logger(__name__)
_... | 617 |
'''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 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionP... | 617 |
'''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 | 1 |
'''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... | 617 |
'''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 | 1 |
'''simple docstring'''
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.prepro... | 617 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> float:
if days_between_payments <= 0:
raise ValueError('days_between_payments must be > 0' )
if daily_interest_rate < 0:
rai... | 617 |
'''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 | 1 |
'''simple docstring'''
import math
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase = 0 , _lowerCAmelCase = 0 )-> list:
__UpperCAmelCase = end or len(_lowerCAmelCase )
for i in range(_lowerCAmelCase , _lowerCAmelCase ):
__UpperCAmelCase ... | 617 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenizatio... | 617 |
'''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 | 1 |
'''simple docstring'''
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDif... | 617 |
'''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 | 1 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> List[Any]:
__UpperCAmelCase = {
'en': 'Machine learnin... | 617 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transform... | 617 |
'''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 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vi... | 617 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
_A: int = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_A: in... | 617 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Any = logging.get_logger(__name__)
_A: Dict = {
"""facebook/s2t-small-librispeech-asr""": (
"""https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/... | 617 |
'''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 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: str = {
"""xlm-roberta-... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switc... | 617 |
'''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 | 1 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device... | 617 |
'''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 | 1 |
'''simple docstring'''
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> List[str]:
__UpperCAmelCase = AutoConfig.from_pretra... | 617 |
'''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 | 1 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 617 |
'''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 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase )-> list:
__UpperCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__UpperCAmelCase = True
for i in range(0 , len(_lowerCAmelCase ) - 1 , 2 ): #... | 617 |
'''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 | 1 |
'''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_a... | 617 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: int = logging.get_logger(__name__)
_A: List[Any] = {
"""bigcode/gpt_bigcode-santacoder""": """https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.j... | 617 |
'''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 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class UpperCAmelCase ( unittest.TestCase ):
_A : O... | 617 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_A: Union[str, Any] = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDepen... | 617 |
'''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 | 1 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'kwargs, expected' , [
({'num_shards': 0, 'max_num_jobs': 1}, []),
({'num_shards': 10, 'max_num_jobs': ... | 617 |
'''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 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: List[str] = {"""vocab_file""": """vocab.json"""}
_A: Tupl... | 617 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configurat... | 617 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (... | 617 |
'''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 | 1 |
'''simple docstring'''
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def _lowerCAmelCase ( _lowerCAmelCase )-> Dict[str, torch.Tensor]:
__UpperCAmelCase = []
__UpperCAmelCase ... | 617 |
'''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 | 1 |
'''simple docstring'''
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _lowerCAmelCase ( *_lowerCAmelCase )-> Optional[Any]:
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
__UpperCAmelCase = ... | 617 |
'''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 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_A: int = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": ... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArg... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase ... | 617 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: Tuple = {
"""configuration_informer""": [
"""INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""I... | 617 |
'''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 | 1 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class Uppe... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
... | 617 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...tes... | 617 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A: int = {
"""configuration_clap""": [
"""CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
"""ClapAudioConfig""",
"""ClapConfig""",
... | 617 |
'''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 | 1 |
'''simple docstring'''
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCAmelCase ( UpperCAmelCase_ ):
_A : Tuple = CustomTokenizer
pass
| 617 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import Tokenizer... | 617 |
'''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 | 1 |
'''simple docstring'''
import requests
_A: Optional[Any] = """https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="""
def _lowerCAmelCase ( _lowerCAmelCase )-> None:
# fetching a list of articles in json format
__UpperCAmelCase = requests.get(_NEWS_AP... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _lowerCAmelCase... | 617 |
'''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 | 1 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerCAmelCas... | 617 |
'''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 | 1 |
'''simple docstring'''
from string import ascii_uppercase
_A: Optional[int] = {str(ord(c) - 55): c for c in ascii_uppercase}
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
if isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise Ty... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils imp... | 617 |
'''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 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCA... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
_A: Tuple = """1"""
_A: Optional[int] = """0"""
_A: Union[str, Any] = """1"""
_A: Union[str, Any] = ort.SessionOptions()
_A: List[str] = ort.GraphOptim... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import collections
import os
import re
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_table.py
_A: Dict = """src/tran... | 617 |
'''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 | 1 |
'''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
_A: List[str] = datasets.logging.get_logger(__name__)
_A: int = """\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon}... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
_A: Optional[int] = {
"""sample_size""": 32,
"""in_channels""": 3,
"""out_channels""": 3,
"""layers_per_bl... | 617 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A: Union[str, Any] = logging.get_logger(__name__)
_A: int = {
"""alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json"... | 617 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def _lowerCAmelCase ( _lowerCAmelCase )-> str:
return "".join(sorted(_lowerCAmelCase ) )
def _lowerCAmelCase ( _lowerCAmelCase )-> list[str]... | 617 |
'''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 | 1 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
fr... | 617 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> str:
__UpperCAmelCase = 0
__UpperCAmelCase = len(_lowerCAmelCase ) - 1
while left <= right:
# avoid divided by 0 during interpolation
if sorted_collection[left] == sorted_collecti... | 617 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> list[list[int]]:
__UpperCAmelCase = []
create_all_state(1 , _lowerCAmelCase , _lowerCAmelCase , [] , _lowerCAmelCase... | 617 |
'''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 | 1 |
'''simple docstring'''
from collections.abc import Callable
class UpperCAmelCase :
def __init__( self , __A = None ):
# Stores actual heap items.
__UpperCAmelCase = []
# Stores indexes of each item for supporting updates and deletion.
__UpperCAmelCase ... | 617 |
'''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 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_A: Optional[int] = logging.get_logger(__name__)
_A: str ... | 617 |
'''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 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase )-> bool:
__UpperCAmelCase = len(_lowerCAmelCase ) + 1
__UpperCAmelCase = len(_lowerCAmelCase ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
# length i of i... | 617 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_A: Dict = logging.get_logger(__name__)
class UpperCAmelCase ( UpperCAmelCase_... | 617 |
'''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 | 1 |
'''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , )-> tuple[float | int, list[tuple[int, int]]]:
__UpperCAmelCase , __Upper... | 617 |
'''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 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoi... | 617 |
'''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 | 1 |
'''simple docstring'''
import re
def _lowerCAmelCase ( _lowerCAmelCase )-> bool:
__UpperCAmelCase = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(_lowerCAmelCase , _lowerCAmelCase ):
return match.string == phone
return False
if __n... | 617 |
'''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 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow... | 617 |
'''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 | 1 |
'''simple docstring'''
import os
import posixpath
import uuid
from dataclasses import dataclass
from typing import TYPE_CHECKING, Iterable, List, Optional, Tuple, Union
import numpy as np
import pyarrow as pa
import datasets
from datasets.arrow_writer import ArrowWriter, ParquetWriter
from datasets.config i... | 617 |
'''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 | 1 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class UpperCAmelCase ( UpperCAmelCase_ , UpperCAmelCase_ ):
@register_to_config
def __init__( self , *,
... | 617 |
'''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 | 1 |
'''simple docstring'''
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
fr... | 617 |
'''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 | 1 |
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