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 |
|---|---|---|---|---|
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'vocab_file': 'vocab.txt',
'merges_file': 'bpe.codes',
}
_... | 711 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeli... | 712 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = 0
while num > 0:
digit_sum += num % 1_0
num //= 1_0
return digit_sum
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0 ) ->int:
UpperCAmelCase = 1
UpperCAmelCase ... | 713 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__a = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_torch_available():
raise OptionalDependencyN... | 714 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 0 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __lowercase ( __lowerCAmelCase ):
def _lowercase ( self : Optional[Any] , __lowerCamelCase : ... | 715 |
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_vision
from trans... | 627 | 0 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->Dict:
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 716 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import loa... | 717 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 0 |
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
"""split_dict""" , [
SplitDict(),
SplitDict({"""train""": SplitInfo(name="""train""" , num_bytes=1_3_3_7 , num_examples=4_2 , data... | 718 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowercase ( _UpperCAmelCase ):
UpperCamelCase = (DDPMScheduler,)
def _lowercase ( self : Li... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 0 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, ... | 720 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 0 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__a = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->List[str]:
... | 721 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 0 |
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_tokenization_common import Token... | 700 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 0 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from... | 701 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 0 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
__a = logging.getLogger(__name__)
if __name__ == "__main__":
__a... | 702 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class __lowercase ... | 703 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->Any:
return round(float(moles / volume ) * nfactor )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->List[Any]:
return round(float((moles... | 704 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 0 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="""session""" )
def _... | 705 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 0 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __lowercase ( __a ):
UpperCamelCase ... | 706 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 0 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->float:
if days_between_payments <= 0:
raise ValueError("""days_between_payments must be > 0""" )
if daily_interest_rate < 0:
raise Va... | 707 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 0 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__a = "scheduler_config.json"
class __lowercase ( _UpperCAmelCase ):
UpperCamelCase = ... | 708 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class __lowercase ... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import ... | 710 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 0 |
from __future__ import annotations
from fractions import Fraction
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->List[Any]:
return (
num != den and num % 1_0 == den // 1_0 and (num // 1_0) / (den % 1_0) == num / den
)
def _UpperCamelCase ( lowerCA... | 711 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 0 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transformer... | 712 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 0 |
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_utils import Ge... | 713 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__a = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0 ) ->Dict:
UpperCAmelCase = set()
UpperCAmelCase = 0
UpperCAmelCase = n + 1 # maximum limit
for a in range(2 , lowerCAmelCase_ ):
for b in range(2 , lowerCAmelCase_ ):
... | 714 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 0 |
import gc
import threading
import time
import psutil
import torch
class __lowercase :
def __init__( self : Optional[int] ) -> List[Any]:
"""simple docstring"""
UpperCAmelCase = psutil.Process()
... | 715 |
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_vision
from trans... | 627 | 0 |
import sys
import turtle
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->tuple[float, float]:
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , ) ... | 716 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->List[str]:
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
UpperCAmelCase = str(bin(lowerCAmelCase_ ) )[2:] # remove the leading "0b"
UpperCAmelCase ... | 717 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 0 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplif... | 718 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , ... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 0 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowercase ( __lowercase ):
UpperCamelCase = (DDPMScheduler,)
def _lowercase ( self : Any , **__lowerCamelCase ... | 720 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
f... | 721 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(lowerCAmelCase_ ) )
def _UpperCamelCase ( lowerCAmelCase_ , lowerC... | 700 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 0 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
__a = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any membership function
# (trapmf(), gbellmf(), gaussm... | 701 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoMode... | 702 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
if not is_torch_available():
raise... | 703 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 0 |
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 __lowercase ( _UpperCAme... | 704 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
"""configuration_table_transformer""": [
"""TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""TableTransformerCo... | 705 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 0 |
'''simple docstring'''
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerC... | 706 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 0 |
class __lowercase :
def __init__( self : Optional[Any] , __lowerCamelCase : list[int] ) -> None:
"""simple docstring"""
UpperCAmelCase = len(__a )
UpperCAmelCase = [0] * ... | 707 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 0 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __lowercase ( ctypes.Structure ):
UpperCamelCase = [("size", ctypes.c_int), ("visible", ctypes.c_byte)]
def _Uppe... | 708 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 0 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONA... | 710 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 0 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils i... | 711 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 0 |
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transformers.model... | 712 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 0 |
from datetime import datetime
import requests
def _UpperCamelCase ( lowerCAmelCase_ ) ->bytes:
UpperCAmelCase = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
UpperCAmelCase = requests.get(base_url + url ).json()[0]["urls"][0]["src"]
ret... | 713 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__a = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 0 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->Dict:
Upp... | 714 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 0 |
import math
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->List[Any]:
if (
not isinstance(UpperCamelCase__ , (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError("""power_factor must be a valid float value b... | 715 |
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_vision
from trans... | 627 | 0 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class A ( __UpperCAmelCase ):
def _lowercase ( self : int ) -> int:
"""simple docstring"""
... | 716 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 0 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __lowercase :
UpperCamelCase = 42
UpperCamelCase = None
UpperCamelCase = None
__a = namedtuple("""Coi... | 717 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 0 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
__a = logging.get_logger(__name__)
class __lowercase :
def __init__( self : ... | 718 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 0 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 0 |
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__snake_case ):
UpperCamelCase = ['''onnx''']
def __init__( self : Optional[int] , *__lowerCamelCase : int , **__lowerCamelCase : ... | 720 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 0 |
'''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 ImageProcessingS... | 721 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 0 |
from math import ceil, sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
UpperCAmelCase = max(ceil(sqrt(outer_width**2 - limit ... | 700 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 0 |
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from transformers i... | 701 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 0 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
__a = transforms.Compo... | 702 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = 1
UpperCAmelCase = 2
while i * i <= n:
UpperCAmelCase = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
... | 703 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 0 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
__a = """2.13.1"""
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse("""3.7"""):
raise Impo... | 704 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1... | 705 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _UpperCamelCase ( lowerCAmelCase_ ) ->Union[str, Any]:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
... | 706 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->Union[str, Any]:
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
UpperCAmelCase = mf_knapsack(i - 1 , lowerCAmelC... | 707 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 708 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 0 |
import random
from typing import Any
def _UpperCamelCase ( lowerCAmelCase_ ):
for _ in range(len(_A ) ):
UpperCAmelCase = random.randint(0 , len(_A ) - 1 )
UpperCAmelCase = random.randint(0 , len(_A ) - 1 )
UpperCAmelCase , Upp... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 0 |
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'huggingface/autoformer-tourism-monthly': 'https://huggingface.co/huggingface/autoformer-tourism-monthly/resolve/main/config.json',... | 710 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = [[0 for _ in range(lowerCAmelCase_ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
UpperCAmelCase = 1
for n in range(m + 1 ):
for k in range(1 , lowerCAmelCase_ ):
... | 711 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 0 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class __lowercase ( __snake_case ):
UpperCamelCas... | 712 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 0 |
import copy
import re
class __lowercase :
UpperCamelCase = '''hp'''
UpperCamelCase = {}
UpperCamelCase = None
@classmethod
def _lowercase ( cls : Optional[int] , __lowerCamelCase ... | 713 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__a = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available(... | 714 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 0 |
import os
from collections.abc import Iterator
def _UpperCamelCase ( lowerCAmelCase_ = "." ) ->Any:
for dir_path, dir_names, filenames in os.walk(lowerCamelCase__ ):
UpperCAmelCase = [d for d in dir_names if d != "scripts" and d[0] not in "._"]
for filename in ... | 715 |
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_vision
from trans... | 627 | 0 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
__a = numpy.array([0, 0])
__a = numpy.array([0.5, 0.8_66_02_54])
__a = numpy.array([1, 0])
__a = [VECTOR_1, VECTOR_2, VECTOR_3, VECTOR_1]
def _... | 716 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 0 |
import argparse
from collections import defaultdict
import yaml
__a = """docs/source/en/_toctree.yml"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Union[str, Any]:
UpperCAmelCase = defaultdict(snake_case__ )
for doc in model_doc:
counts[doc["local"]] += 1... | 717 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
__a = logging.get_logger(__name__)
... | 718 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
def _UpperCamelCase ( lowerCAmelCase_ ) ->dict:
UpperCAmelCase = F"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(lowerCAmelCase_ ).json()... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 0 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __lowercase ( __lowerC... | 720 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 0 |
'''simple docstring'''
from __future__ import annotations
class __lowercase :
def __init__( self : int , __lowerCamelCase : str , __lowerCamelCase : Union[str, Any] ) -> Dict:
"""simple d... | 721 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 0 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 700 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 0 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
... | 701 |
from math import sqrt
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = 0
UpperCAmelCase = 0
UpperCAmelCase = 42
while num_cuboids <= limit:
max_cuboid_size += 1
for sum_shortest_sides in range(2 , ... | 627 | 0 |
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ = False ) ->int:
if radian_mode:
return [magnitude * cos(lowerCame... | 702 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ ) ->None:
create_state_space_tree(lowerCAmelCase_ , [] , 0 , [0 for i in range(len(lowerCAmelCase_ ) )] )
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAm... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
UpperCAmelCase = 1
UpperCAmelCase = 1
while repunit:
UpperCAmelCase = (1_0 * repunit + 1) % divisor
repunit_index += 1
... | 703 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from... | 704 |
import argparse
__a = """docs/source/_static/js/custom.js"""
def _UpperCamelCase ( lowerCAmelCase_ ) ->Optional[Any]:
with open(lowerCAmelCase_ , encoding="""utf-8""" , newline="""\n""" ) as f:
UpperCAmelCase = f.readlines()
UpperCAmelCase ... | 627 | 0 |
'''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_determi... | 705 |
import math
class __lowercase :
def _lowercase ( self : Union[str, Any] , __lowerCamelCase : list[list[float]] , __lowerCamelCase : list[int] ) -> int:
"""simple docstring"""
... | 627 | 0 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
__a = '\\n@misc{chen2021evaluating,\n titl... | 706 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def _UpperCamelCase ( lowerCAmelCase_ ) ->int:
UpperCAmelCase = {}
UpperCAmelCase = tok... | 627 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 707 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__a = """\
@article{wang2019superglue,
title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},
author={Wang, Alex and Pruksach... | 627 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 708 |
import math
import qiskit
def _UpperCamelCase ( lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 , lowerCAmelCase_ = 1 ) ->qiskit.result.counts.Counts:
if (
isinstance(lowerCAmelCase_ , lowerCAmelCase_ )
or isinstance(lowerCAmelCase_ , lowerCAmelCase_ ... | 627 | 0 |
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.test_util... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class __lowercase ( __snake_case ):
UpperCamelCase = '''ct... | 627 | 0 |
import mpmath # for roots of unity
import numpy as np
class __lowercase :
def __init__( self : List[str] , __lowerCamelCase : List[Any]=None , __lowerCamelCase : List[str]=None ) -> Tuple:
"""simp... | 710 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 627 | 0 |
import collections
import os
import re
from pathlib import Path
__a = """src/transformers"""
# Matches is_xxx_available()
__a = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
__a = re.compile(R"""^_import_structure\s+=\s+\{([^\}]+)\}""")
... | 711 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfig"""]}
try:
if not is_torch_available():
raise OptionalDepen... | 627 | 0 |
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 = logging.get_logger(__name__)
__a = {
"hustvl/yolos-small": "https://hugging... | 712 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotA... | 627 | 0 |
from __future__ import annotations
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->tuple[float, list[float]]:
UpperCAmelCase = list(range(len(a_ ) ) )
UpperCAmelCase = [v / w for v, w in zip(a_ , a_ )]
index.so... | 713 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
__a = logging.get_logger(__name__)
def _UpperCamelCase ( lowerCAmelCase_ , ... | 627 | 0 |
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class __lowercase ( _a ):
def __init__( self : Any , __lowerCamelCase : Dict , ... | 714 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->str | Literal[False]:
UpperCAmelCase = list(lowerCAmelCase_ )
UpperCAmelCase = list(lowerCAmelCas... | 627 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerca... | 715 |
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_vision
from trans... | 627 | 0 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformers.... | 716 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subproc... | 627 | 0 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils impor... | 717 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowercase ( unittest.TestCase ):
def _lowercase ( self : ... | 627 | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def _UpperCamelCase ( lowerCAmelCase_ ) ->Union[str, Any]:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives,... | 718 |
from math import isqrt
def _UpperCamelCase ( lowerCAmelCase_ ) ->bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(lowerCAmelCase_ ) + 1 ) )
def _UpperCamelCase ( lowerCAmelCase_ = 1_0**6 ) ->int:
UpperCAmelCase = 0
UpperCAm... | 627 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Auto... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
class __lowercase ( __snake_case ):... | 627 | 0 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__a = get_tests_dir("""fixtures/spiece.model""")
... | 720 |
__a = [
(1000, """M"""),
(900, """CM"""),
(500, """D"""),
(400, """CD"""),
(100, """C"""),
(90, """XC"""),
(50, """L"""),
(40, """XL"""),
(10, """X"""),
(9, """IX"""),
(5, """V"""),
(4, """IV"""),
(1, """I"""),
]
def _UpperCamelCase ( ... | 627 | 0 |
'''simple docstring'''
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) ->float:
UpperCAmelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
def _Upper... | 721 |
def _UpperCamelCase ( lowerCAmelCase_ , lowerCAmelCase_ ) ->int:
return int((input_a, input_a).count(0 ) == 0 )
def _UpperCamelCase ( ) ->None:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ) == 0
... | 627 | 0 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->float:
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
UpperCAmelCase = sum(lowerCAmelCase_ ) / len(lowerCAmelCase_ ) # Calculate the average
return sum(abs(x - average )... | 700 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 627 | 0 |
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