code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A_ ( sn... | 350 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ ( unittest.TestCase ... | 280 | 0 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
lowercase__ = "\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Mult... | 351 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = (
first_str_length if first_str_length > second_str... | 280 | 0 |
'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatu... | 352 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if depth < 0:
raise ValueError('Depth cannot be less than 0' )
if not scores:
... | 353 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if len(UpperCAmelCase_ ) == 0:
raise ValueError('find_max() arg is an empty sequence' )
if (
left >= len(UpperCAmelCase_ )
or ... | 280 | 0 |
'''simple docstring'''
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
impor... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
return 10 - x * x
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if equation(UpperCAmelCase_ ) * equation(UpperCAmelCase_ ) >= 0:
raise ValueError('Wrong space!' )
UpperCAmelCase : Any ... | 355 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase__ = 3
def UpperCamelCase( UpperCAmelCase_ ):
print('Generating primitive root of p' )
while True:
UpperCAmelCase : ... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowercase__ = (3, 9, -11, 0, 7, 5, 1, -1)
lowercase__ = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class A_ :
'''s... | 356 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase( UpperCAmelCase_ , UpperCAm... | 280 | 0 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ = HUGGINGFACE_HUB_CACHE
lowercase__ = "config.json"
lowercase__ = "diffusion_pytorch_model.bin"
lowercase__ = "diffusion_flax_model.msgpack"
lowercase_... | 357 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ = {
"facebook/maskformer-s... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {'configuration_unispeech': ['UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP', 'UniSpeechCon... | 358 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase_ , int(b / 2 ) ) * actual_power(UpperCAmelCase_ , int(b / 2 ) )
else:
return a * actual_power(UpperCAmelCase_ , in... | 280 | 0 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info... | 359 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 280 | 0 |
'''simple docstring'''
import math
import os
import sys
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : int = ''
try:
with open(UpperCAmelCase_ , 'rb' ) as binary_file:
UpperCAmelCase : List[Any] = binary_file.read()
for dat in data:
U... | 360 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2... | 280 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr
import datasets
lowercase__ = "\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies ... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ = 4_00_00_00 ):
UpperCAmelCase : List[Any] = [0, 1]
UpperCAmelCase : List[str] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
UpperCAmelCase : List[Any] =... | 362 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowercase__ = logging.get_logger("transformers.models.speecht5")
def UpperCamelCase( UpperCAmelCa... | 280 | 0 |
'''simple docstring'''
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class A_ ( _snake_case , _snake_case ):
'''s... | 363 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def UpperCamelCase( ):
UpperCAmelCase : List[Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , type=UpperCAmelCase_ , default='biencoder-nq-dev.json' ... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : str = []
for data in source_data:
for i, el in enumerate(SCREAMING_SNAKE_CASE_ ):
if len(SCREAMING_SNAKE_CASE_ ) < i + 1:
data_lists.append([] )
data_lists[i].append(float(SCREAMING_SNAKE_... | 364 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A_ ... | 280 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
... | 365 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dim... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : List[Any] = len(lowerCAmelCase__ )
print('The following activities are selected:' )
# The first activity is always selected
UpperCAmelCase : Optional[int] = 0
... | 366 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowercase__ = TypeVar("KEY")
lowercase__ = TypeVar("VAL")
@dataclass(frozen=_snake_case , slots=_snake_case )
cla... | 280 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils ... | 367 |
'''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... | 280 | 0 |
'''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_squeezebert import SqueezeBertTokenizer
lowercase__ = logging.ge... | 368 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowercase__ = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseC... | 369 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return x if y == 0 else greatest_common_divisor(__SCREAMING_SNAKE_CASE , x % y )
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return (x * y) // greatest_common_divisor(__SCREAMING_SNAKE_CA... | 370 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
while a != 0:
UpperCAmelCase , UpperCAmelCase : Tuple = b % a, a
return b
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if gcd(UpperCAmelCase_ , UpperCAmelCase_ ... | 280 | 0 |
'''simple docstring'''
from collections import namedtuple
import requests
from lxml import html # type: ignore
lowercase__ = namedtuple("covid_data", "cases deaths recovered")
def UpperCamelCase( UpperCAmelCase_ = "https://www.worldometers.info/coronavirus/" ):
UpperCA... | 371 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
re... | 280 | 0 |
'''simple docstring'''
class A_ :
'''simple docstring'''
def __init__( self : str , lowercase_ : Tuple , lowercase_ : Optional[Any] ) -> Optional[Any]:
UpperCAmelCase : int = name
UpperCAmelCase : Optiona... | 350 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ ( unittest.TestCase ... | 280 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=_snake_case )
class A_ ( _snake_case ):
'''simple d... | 351 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = (
first_str_length if first_str_length > second_str... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
class A_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , lowercase_ : str , lowercase_ : str ) -> Any:
UpperCAmelCase : List[Any] = ... | 352 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 280 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.j... | 353 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if len(UpperCAmelCase_ ) == 0:
raise ValueError('find_max() arg is an empty sequence' )
if (
left >= len(UpperCAmelCase_ )
or ... | 280 | 0 |
'''simple docstring'''
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
lowercase__ = 299792458
# Symbols
lowercase__ , lowercase__ , lowercase__ , lowercase__ = symbols("ct x y z")
def UpperCamelC... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 280 | 0 |
'''simple docstring'''
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
lowercase__ = logging.get_logger(__name__)
... | 355 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase__ = 3
def UpperCamelCase( UpperCAmelCase_ ):
print('Generating primitive root of p' )
while True:
UpperCAmelCase : ... | 280 | 0 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase( UpperCAmelCase_ , UpperCAm... | 356 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase( UpperCAmelCase_ , UpperCAm... | 280 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_mo... | 357 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ = {
"facebook/maskformer-s... | 280 | 0 |
'''simple docstring'''
from PIL import Image
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : int = image.size
UpperCAmelCase : Tuple = 0
UpperCAmelCase : Tuple = image.load()
for i in range(UpperCAmelCase_ ):
for j in range(UpperCAmelCase_ ):
... | 358 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase_ , int(b / 2 ) ) * actual_power(UpperCAmelCase_ , int(b / 2 ) )
else:
return a * actual_power(UpperCAmelCase_ , in... | 280 | 0 |
'''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,
AutoModelForMult... | 359 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
if length <= 0 or not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(UpperCAmelCase_ )]
if __name__ == "__main__":
... | 360 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 280 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
lowercase__ = logging.get_logger(__name__)
class A_ ( _snake_case ):
'''simple docstring'''
def __init__( self : Opt... | 362 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowercase__ = logging.get_logger("transformers.models.speecht5")
def UpperCamelCase( UpperCAmelCa... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
class A_ :
'''simple docstring'''
def __init__( self : Dict , lowercase_ : int ) -> None:
UpperCAmelCase : Any = data
UpperCAmelCase : Node | None =... | 363 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def UpperCamelCase( ):
UpperCAmelCase : List[Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , type=UpperCAmelCase_ , default='biencoder-nq-dev.json' ... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : List[str] = [0] * len(UpperCAmelCase_ )
UpperCAmelCase : Optional[Any] = []
UpperCAmelCase : Dict = [1] * len(UpperCAmelCase_ )
for values in graph.values():
for i in values:
... | 364 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A_ ... | 280 | 0 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def UpperCamelCase( UpperCAmelCase_ ):
return getitem, k
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return se... | 365 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dim... | 280 | 0 |
'''simple docstring'''
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
lowercase__ = (
"This metric will be removed from the li... | 366 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowercase__ = TypeVar("KEY")
lowercase__ = TypeVar("VAL")
@dataclass(frozen=_snake_case , slots=_snake_case )
cla... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],
}
... | 367 |
'''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... | 280 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ ... | 368 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 280 | 0 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_=None , **UpperCAmelCase_ ) -> Any:
UpperCAmelCase : Tuple = [x.strip() for x in open(UpperCAmelCase_ ).readlines(... | 369 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark... | 280 | 0 |
'''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
if ver... | 370 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
while a != 0:
UpperCAmelCase , UpperCAmelCase : Tuple = b % a, a
return b
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if gcd(UpperCAmelCase_ , UpperCAmelCase_ ... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ = {
... | 371 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
re... | 280 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowercase__ = logging.get_logger(__name__)
... | 350 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ ( unittest.TestCase ... | 280 | 0 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import tor... | 351 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = (
first_str_length if first_str_length > second_str... | 280 | 0 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase__ = 3
def UpperCamelCase( UpperCAmelCase_ ):
print('Generating primitive root of p' )
while True:
UpperCAmelCase : ... | 352 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : str = [], []
while len(UpperCAmelCase_ ) > 1:
UpperCAmelCase : Any = min(UpperCAmelCase_ ), max(UpperCAmelCase_ )
start.append(UpperCAmelCase_ )
end.append(UpperCAmelCas... | 353 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if len(UpperCAmelCase_ ) == 0:
raise ValueError('find_max() arg is an empty sequence' )
if (
left >= len(UpperCAmelCase_ )
or ... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase_ , int(b / 2 ) ) * actual_power(UpperCAmelCase_ , int(b / 2 ) )
else:
return a * actual_power(UpperCAmelCase_ , in... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_... | 355 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase__ = 3
def UpperCamelCase( UpperCAmelCase_ ):
print('Generating primitive root of p' )
while True:
UpperCAmelCase : ... | 280 | 0 |
'''simple docstring'''
lowercase__ = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAm... | 356 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase( UpperCAmelCase_ , UpperCAm... | 280 | 0 |
import csv
import tweepy
# Twitter API credentials
lowercase__ = ""
lowercase__ = ""
lowercase__ = ""
lowercase__ = ""
def UpperCamelCase( UpperCAmelCase_ ):
# authorize twitter, initialize tweepy
UpperCAmelCase : Optional[in... | 357 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ = {
"facebook/maskformer-s... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
while a != 0:
UpperCAmelCase : Tuple = b % a, a
return b
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if gcd(UpperCAmelCase_ , UpperCAmelCase_ ) != 1:
UpperCAmelCase : ... | 358 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase_ , int(b / 2 ) ) * actual_power(UpperCAmelCase_ , int(b / 2 ) )
else:
return a * actual_power(UpperCAmelCase_ , in... | 280 | 0 |
'''simple docstring'''
from collections import namedtuple
lowercase__ = namedtuple("from_to", "from_ to")
lowercase__ = {
"cubicmeter": from_to(1, 1),
"litre": from_to(0.001, 1000),
"kilolitre": from_to(1, 1),
"gallon": from_to(0.00454, 264.172),
"cubicyar... | 359 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('You cannot supply more or less than 2 values' )
elif stress < 0:
raise... | 360 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2... | 280 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def UpperCamelCase( UpperCAmelC... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 280 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ ( unittest.TestCase ):
'... | 362 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowercase__ = logging.get_logger("transformers.models.speecht5")
def UpperCamelCase( UpperCAmelCa... | 280 | 0 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase__ = ... | 363 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def UpperCamelCase( ):
UpperCAmelCase : List[Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , type=UpperCAmelCase_ , default='biencoder-nq-dev.json' ... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
return str(UpperCAmelCase_ ) == str(UpperCAmelCase_ )[::-1]
def UpperCamelCase( UpperCAmelCase_ ):
return int(UpperCAmelCase_ ) + int(str(UpperCAmelCase_ )[::-1] )
def UpperCamelCase( UpperCAme... | 364 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A_ ... | 280 | 0 |
'''simple docstring'''
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
lowercase__ = "\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n au... | 365 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dim... | 280 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import requir... | 366 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowercase__ = TypeVar("KEY")
lowercase__ = TypeVar("VAL")
@dataclass(frozen=_snake_case , slots=_snake_case )
cla... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ = {
"configuration_falcon": ["FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP", "FalconConfig"],
}
try:
if not is_... | 367 |
'''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... | 280 | 0 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def UpperCamelCase( UpperCAmelCase_ = 3 ):
if isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('number of qubi... | 368 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 280 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 369 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark... | 280 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
sm... | 370 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
while a != 0:
UpperCAmelCase , UpperCAmelCase : Tuple = b % a, a
return b
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if gcd(UpperCAmelCase_ , UpperCAmelCase_ ... | 280 | 0 |
'''simple docstring'''
import unittest
import numpy as np
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ = None , ):
UpperCAmelCase : Optional[int] = np.shape(UpperCAmelCase_ )
UpperCAmelCase : Tuple = np.shape(Upp... | 371 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
re... | 280 | 0 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark... | 350 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ ( unittest.TestCase ... | 280 | 0 |
'''simple docstring'''
from torch import nn
class A_ ( nn.Module ):
'''simple docstring'''
def __init__( self : Union[str, Any] , lowercase_ : Optional[Any] , lowercase_ : List[Any] ) -> int:
super().__init__(... | 351 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = (
first_str_length if first_str_length > second_str... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : Optional[int] = min(UpperCAmelCase_ ) # min() finds the minimum value
UpperCAmelCase : int = max(UpperCAmelCase_ ) # max() finds the maximum value
UpperCAmelCase : int = ... | 352 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 280 | 0 |
'''simple docstring'''
lowercase__ = {
"a": "AAAAA",
"b": "AAAAB",
"c": "AAABA",
"d": "AAABB",
"e": "AABAA",
"f": "AABAB",
"g": "AABBA",
"h": "AABBB",
"i": "ABAAA",
"j": "BBBAA",
"k": "ABAAB",
"l": "ABABA",
"m": "ABABB",
"n": "ABB... | 353 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if len(UpperCAmelCase_ ) == 0:
raise ValueError('find_max() arg is an empty sequence' )
if (
left >= len(UpperCAmelCase_ )
or ... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise ValueError('iterations must be defined as integers' )
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ) or not number >= 1:
raise V... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 280 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
class A_ ( _snake_case ):
'''simple docstring'''
UpperCAmelCase_ : Tuple = """timm_backbone"""
def _... | 355 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase__ = 3
def UpperCamelCase( UpperCAmelCase_ ):
print('Generating primitive root of p' )
while True:
UpperCAmelCase : ... | 280 | 0 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowercase__ = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import word_to... | 356 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase( UpperCAmelCase_ , UpperCAm... | 280 | 0 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowercase__ = logging.get_logger("transformers.models.speecht5")
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , ... | 357 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ = {
"facebook/maskformer-s... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ ):
if not nums:
return 0
UpperCAmelCase : Optional[int] = nums[0]
UpperCAmelCase : List[str] = 0
for num in nums[1:]:
UpperCAmelCase : List[str] = (
max_excl... | 358 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase_ , int(b / 2 ) ) * actual_power(UpperCAmelCase_ , int(b / 2 ) )
else:
return a * actual_power(UpperCAmelCase_ , in... | 280 | 0 |
'''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 parqu... | 359 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 280 | 0 |
'''simple docstring'''
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2,})")
lowercase__... | 360 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase__ = {"configuration_vit_mae": ["VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP", "V... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 280 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowercase__ = logging.get_logger(__name__)
class A_ ( _snake_case ):
'''simple docstring'''
def __init__( self : Optional[Any] , ... | 362 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowercase__ = logging.get_logger("transformers.models.speecht5")
def UpperCamelCase( UpperCAmelCa... | 280 | 0 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def UpperCamelCase( UpperCAmelCase_ ):
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCAmelCase_ , UpperCAmelCas... | 363 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def UpperCamelCase( ):
UpperCAmelCase : List[Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , type=UpperCAmelCase_ , default='biencoder-nq-dev.json' ... | 280 | 0 |
'''simple docstring'''
class A_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , lowercase_ : Optional[Any] , lowercase_ : Optional[Any] , lowercase_ : Union[str, Any] ) -> List[Any]:
UpperCAmelCase : str ... | 364 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A_ ... | 280 | 0 |
'''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... | 365 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dim... | 280 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowercase__ = logging.get_logger(__name_... | 366 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowercase__ = TypeVar("KEY")
lowercase__ = TypeVar("VAL")
@dataclass(frozen=_snake_case , slots=_snake_case )
cla... | 280 | 0 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from... | 367 |
'''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... | 280 | 0 |
'''simple docstring'''
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
... | 368 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 280 | 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 ImageProcessingSavingTestM... | 369 |
'''simple docstring'''
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark... | 280 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMS... | 370 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
while a != 0:
UpperCAmelCase , UpperCAmelCase : Tuple = b % a, a
return b
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if gcd(UpperCAmelCase_ , UpperCAmelCase_ ... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : Union[str, Any] = credit_card_number
UpperCAmelCase : str ... | 371 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
re... | 280 | 0 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_co... | 350 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A_ ( unittest.TestCase ... | 280 | 0 |
'''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.p... | 351 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = len(UpperCAmelCase_ )
UpperCAmelCase : int = (
first_str_length if first_str_length > second_str... | 280 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 352 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Con... | 280 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"google/fnet-larg... | 353 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ ):
if len(UpperCAmelCase_ ) == 0:
raise ValueError('find_max() arg is an empty sequence' )
if (
left >= len(UpperCAmelCase_ )
or ... | 280 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list... | 354 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
UpperCAmelCase : str = u
for i in range(1 , UpperCAmelCase_ ):
UpperCAmelCase : Dict = temp * (u - i)
return temp
def UpperCamelCa... | 355 |
'''simple docstring'''
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowercase__ = 3
def UpperCamelCase( UpperCAmelCase_ ):
print('Generating primitive root of p' )
while True:
UpperCAmelCase : ... | 280 | 0 |
'''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_squeezebert import SqueezeBertTokenizer
lowercase__ = logging.ge... | 356 |
'''simple docstring'''
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCamelCase( UpperCAmelCase_ , UpperCAm... | 280 | 0 |
from heapq import heappop, heappush
import numpy as np
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ , ):
UpperCAmelCase : Optional[Any] = grid.shape
UpperCAmelCase : List[str] = [-1, 1, 0, 0]
UpperCAmelCase : Opti... | 357 |
'''simple docstring'''
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowercase__ = {
"facebook/maskformer-s... | 280 | 0 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf... | 358 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(UpperCAmelCase_ , int(b / 2 ) ) * actual_power(UpperCAmelCase_ , int(b / 2 ) )
else:
return a * actual_power(UpperCAmelCase_ , in... | 280 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=_snake_case ):
'''simple docstring'''
UpperCAmelCase_ : Dict = ["""torch""", """scipy"""]
def __init__( self : Any , *lowercase_... | 359 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 280 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
if len(UpperCAmelCase_ ) <= 1:
return lst
UpperCAmelCase : List[str] = 1
while i < len(UpperCAmelCase_ ):
if lst[i - 1] <= lst[i]:
i += 1
else:
UpperCAmelCase : Optional[int] = lst... | 360 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2... | 280 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class A_ :
'''simple docstring'''
def __init__( self : Optional[int] , lowercase_ : Collecti... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm"... | 280 | 0 |
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