code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class lowerCAmelCase ( unittest.TestCase , a ):
def lowercase ( self ):
lowerCAmelCase : Dict = load_tool('text-classificatio... | 720 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedT... | 721 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 0 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_... | 700 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCAmelCase : Dict = {'configuration_vit_mae': ['VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMAEConfig']}
try:
if not ... | 701 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Tuple = {
'configuration_conditional_detr': [
'CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Condi... | 702 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
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 Toke... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
_lowerCAmelCase : Any = 1.6021E-19 # units = C
def __UpperCamelCase ( _A : float , _A : float , _A : float , ) -> tuple[str, float]:
"""simple docstring"""
i... | 703 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 0 |
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 705 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 0 |
'''simple docstring'''
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 ...... | 706 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[Any] = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main... | 707 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 0 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[Any] = len(snake_case__ )
lowerCAmelCase : Tuple = [0] * len_array
if len_array > 0:
lowerCAmelCase : Optional[int] ... | 708 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 0 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
"""simple docstring"""
... | 709 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 0 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class lowerCAmelCase ( yaml.SafeLoader ):
def lowercase ( self , snake_case__ ):
lowerCAmelCase : Union[str, Any] = [self.con... | 710 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 0 |
'''simple docstring'''
from collections import namedtuple
_lowerCAmelCase : Tuple = namedtuple('from_to', 'from_ to')
_lowerCAmelCase : List[Any] = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.0_0_1, 1000),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0_4_5_4, 264.172)... | 711 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 0 |
def __UpperCamelCase ( _A : dict ) -> set:
"""simple docstring"""
lowerCAmelCase : int = set()
# edges = list of graph's edges
lowerCAmelCase : List[str] = get_edges(_A )
# While there are still elements in edges list, take an arbitrar... | 712 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 0 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
fr... | 713 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 714 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
_lowerCAmelCase : Tuple = logging.getLogger(_... | 715 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 0 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , ty... | 716 |
'''simple docstring'''
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 646 | 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_funnel import FunnelTokenizer
_lowerCAmelCase : str = logging.get_logger(__name... | 717 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 718 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 0 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 719 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 0 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase ( a ):
def __init__( self , snake_case__ , snake_case__ = None , ... | 720 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 0 |
'''simple docstring'''
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from tran... | 721 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import... | 700 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 0 |
from bisect import bisect
from itertools import accumulate
def __UpperCamelCase ( _A : Optional[Any] , _A : Tuple , _A : Dict , _A : List[Any] ) -> int:
"""simple docstring"""
lowerCAmelCase : str = sorted(zip(_A , _A ... | 701 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 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 import (... | 702 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
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 Toke... | 646 | 0 |
'''simple docstring'''
import numpy as np
class lowerCAmelCase :
def __init__( self , snake_case__=None , snake_case__=None , snake_case__=None , snake_case__=None , snake_case__=None ):
self.set_matricies(red=snake_case__ , green=snake_case__ , bl... | 703 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase : Any = {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}
try:
... | 705 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : List[Any] = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.js... | 706 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from tra... | 707 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 0 |
'''simple docstring'''
from manim import *
class lowerCAmelCase ( a ):
def lowercase ( self ):
lowerCAmelCase : int = Rectangle(height=0.5 , width=0.5 )
lowerCAmelCase : List[str] = Rectangle(height=0.4_6 , width=0.4_6 ).s... | 708 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : str = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase ( a ):
_lowerCamelCase ... | 709 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowerCAmelCase : Dict = TypeVar('T')
class lowerCAmelCase ( Generic[T] ):
def __init__( self , snake_case__ = True ):
lowerCAmelCase : dict[T... | 710 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 0 |
'''simple docstring'''
from collections.abc import Sequence
def __UpperCamelCase ( _A : Sequence[float] , _A : bool = False ) -> float:
"""simple docstring"""
if not arr:
return 0
lowerCAmelCase : Union[str, Any] = 0 if allow_empty_subarray... | 711 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 0 |
import operator as op
_lowerCAmelCase : Any = 'scaler.pt'
_lowerCAmelCase : List[str] = 'pytorch_model'
_lowerCAmelCase : Union[str, Any] = 'random_states'
_lowerCAmelCase : Tuple = 'optimizer'
_lowerCAmelCase : List[str] = 'scheduler'
_lowerCAmelCase : Tuple = 'pyto... | 712 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 0 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
_lowerCAmelCase : Any = {
'linear': PIL.Image.Resampling.BILINEAR,
'bilinear': PIL.Image.Resampling.BILINEAR,... | 713 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 714 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 0 |
'''simple docstring'''
from string import ascii_uppercase
_lowerCAmelCase : List[str] = {char: i for i, char in enumerate(ascii_uppercase)}
_lowerCAmelCase : List[Any] = dict(enumerate(ascii_uppercase))
def __UpperCamelCase ( _A : str , _A : str ) -> str:
... | 715 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 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():
from .... | 716 |
'''simple docstring'''
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 646 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_i... | 717 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, loa... | 718 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils... | 719 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 0 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
if num < 0:
return False
lowerCAmelCase : int = num
lowerCAmelCase : int = 0
while num > 0:
lowerCAmelCase : List[str] = r... | 720 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 0 |
'''simple docstring'''
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase : List[Any] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
_lowerCamelCase ... | 721 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 0 |
'''simple docstring'''
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVis... | 700 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}
class lo... | 646 | 0 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowerCAmelCase : List[str] = [
'Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of ... | 701 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'SenseTime/deformable-detr': 'https://huggingface... | 646 | 0 |
'''simple docstring'''
import math
from collections.abc import Iterator
from itertools import takewhile
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3... | 702 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
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 Toke... | 646 | 0 |
'''simple docstring'''
def __UpperCamelCase ( _A : str ) -> bool:
"""simple docstring"""
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
lowerCAmelCase : List[Any] ... | 703 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def __UpperCamelCase ( _A : np.ndarray , _A : float ) -> np.ndarray:
"""simple docstring"""
lowerCAmelCase : Union[str, Any] = math.sqrt(_A )
lowerCAmelCase : ... | 646 | 0 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase :... | 704 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase : int = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch... | 646 | 0 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin... | 705 |
'''simple docstring'''
from typing import Any
class lowerCAmelCase :
def __init__( self , snake_case__ ):
lowerCAmelCase : Optional[int] = data
lowerCAmelCase : Optional[Any] = None
def __repr__( self ):
return f"Node({self.data})"
c... | 646 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import f... | 706 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {str(digit): digit**5 for digit in range(10)}
def __UpperCamelCase ( _A : int ) -> int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_A ) )
def __UpperCamelCase ( ) ... | 646 | 0 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 707 |
'''simple docstring'''
def __UpperCamelCase ( _A : List[str] ) -> Optional[Any]:
"""simple docstring"""
if not head:
return True
# split the list to two parts
lowerCAmelCase , lowerCAmelCase : str = head.next, head
while fast and fast.next:
l... | 646 | 0 |
'''simple docstring'''
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSaving... | 708 |
'''simple docstring'''
import math
def __UpperCamelCase ( _A : int = 1_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : List[Any] = sum(i * i for i in range(1 , n + 1 ) )
lowerCAmelCase : Optional[Any] = int(math.pow(sum... | 646 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def __UpperCamelCase ( _A : List[str] , _A : Optional[int]=10_00 ) -> Any:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
lowerCAmelCase : Union[s... | 709 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase : Union[str, Any] = get_tests_dir('fixture... | 646 | 0 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def __UpperCamelCase ( _A : Tuple ) -> List[Any]:
"""simple docstring"""
lowerCAmelCase : int = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
... | 710 |
'''simple docstring'''
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 646 | 0 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 711 |
'''simple docstring'''
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
'files' , [
['full:README.md', 'dataset_infos.json'],
['empty:README.md', 'dataset_infos... | 646 | 0 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
_lowerCAmelCase : Optional[Any] ... | 712 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSchedule... | 646 | 0 |
from math import sqrt
def __UpperCamelCase ( _A : int = 1_00_00_00 ) -> int:
"""simple docstring"""
lowerCAmelCase : int = 0
lowerCAmelCase : int = 0
lowerCAmelCase : int
while num_cuboids <= limit:
max_cuboid_size += 1
for su... | 713 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_det... | 646 | 0 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
_lowerCAmelCase : int = '\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (... | 714 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Tuple = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'fac... | 646 | 0 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def __UpperCamelCase ( _A : int ) -> bool:
"""simple docstring"""
lowerCAmelCase : int = int(number**0.5 )
return number == sq * sq
def... | 715 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase : Dict = 'src/diffusers'
# Pattern that looks at the indentation in a line.
_lowerCAmelCase : str = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCAmelCase : Any = re.c... | 646 | 0 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __UpperCamelCase ( _A : str , _A : dict ) -> str:
"""simple docstring"""
lowerCAmelCase : List[Any] = BeautifulSoup(requests.get(_A , params=_A ).content , ... | 716 |
'''simple docstring'''
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 646 | 0 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def __UpperCamelCase ( _A : str , _A : str , _A : List[Any] ) -> List[An... | 717 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( _A : Dict ) -> int:
... | 646 | 0 |
'''simple docstring'''
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def __UpperCamelCase ( _A , _A , _A=0 ) -> Optional[int]:
"""simple docstring"""
if name is None:
lowerCAmelCase : Optio... | 718 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'xlm-r... | 646 | 0 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase :
def __init__( self , snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__=0.2 , snake_case__=0.2 ):
lowerCAmelCas... | 719 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCAmelCase : List[Any] = logging.getLogger(__name__)
def __UpperCamelCase ( ) -> Any:
"""simple docstring"""
lowerCAmelCase ... | 646 | 0 |
'''simple docstring'''
def __UpperCamelCase ( _A : list[int] ) -> list[list[int]]:
"""simple docstring"""
lowerCAmelCase : Optional[int] = []
if len(_A ) == 1:
return [nums.copy()]
for _ in range(len(_A ) ):
lowerCAmelCase : Optional[A... | 720 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
_lowerCAmelCase : List[str] = logging.get_logger('transformers.models.speecht5')
def __UpperCamelCase ( _A : Any... | 646 | 0 |
'''simple docstring'''
_lowerCAmelCase : List[str] = {
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-'... | 721 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_lowerCAmelCase : Dict = '\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n ... | 646 | 0 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
Traini... | 647 | import numpy as np
def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ):
assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme... | 647 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : str = "The quick brown fox jumps over the lazy dog" , ):
SCREAMING_SNAKE_CASE = set()
# Replace all the whitespace in our sentence
SCREAMING_SNAKE_CASE = input_str.replace(" " , "" )
for alpha in input... | 647 | import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
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... | 647 | 1 |
from __future__ import annotations
class lowercase :
def __init__( self : Dict , _UpperCamelCase : str , _UpperCamelCase : str ) -> Tuple:
'''simple docstring'''
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE... | 647 | import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_lowerCamelCase : ... | 647 | 1 |
from scipy.stats import pearsonr
import datasets
_lowerCamelCase : Any = '''
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption th... | 647 | def __lowerCamelCase (UpperCAmelCase__ : int ):
assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE = F"The input value o... | 647 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : List[Any] = {
'''uw-madison/mra-base-512-4''': '''https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config... | 647 | 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 lowercase ( unittest.TestCase ):
... | 647 | 1 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common impor... | 647 | import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase ( a ):
lowercase__ : Tuple = (KDPMaDiscreteScheduler,)
lowercase__ : Optiona... | 647 | 1 |
def __lowerCamelCase ():
return 1
def __lowerCamelCase (UpperCAmelCase__ : int ):
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __lowerCamelCase (UpperCAmelCase__ : int ):
return 0 if x < 0 else five_pence(x - 5 ) + two_pe... | 647 | from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_lowerCamelCase : Tuple = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytor... | 647 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : int = 1_0**9 ):
SCREAMING_SNAKE_CASE = 1
SCREAMING_SNAKE_CASE = 2
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 0
while perimeter <= max... | 647 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Optional[int] = {
'''configuration_blenderbot''': [
... | 647 | 1 |
import warnings
from ...utils import logging
from .image_processing_owlvit import OwlViTImageProcessor
_lowerCamelCase : Any = logging.get_logger(__name__)
class lowercase ( a ):
def __init__( self : str , *_UpperCamelCase : Optional[int... | 647 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_lowerCamelCase : Optional[Any] = TypeVar('''T''')
class lowercase ( Generic[T] ):
def __init__( self : Any , _UpperCamelCase : T ... | 647 | 1 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowercase ( unittest.TestCase ):
def __snake_case( self : Optional[int] ) -> Any:
''... | 647 | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 647 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : Any = logging.get_logger(__name__)
_lowerCamelCase : Union[str, Any] = {
'''robert... | 647 | def __lowerCamelCase (UpperCAmelCase__ : list[int] ):
if not numbers:
return 0
if not isinstance(UpperCAmelCase__ , (list, tuple) ) or not all(
isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for number in numbers ):
raise ValueError("numbers... | 647 | 1 |
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 lowercase ( unittest.TestCase ):
... | 647 | import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.u... | 647 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : list[list] ):
SCREAMING_SNAKE_CASE = current_set.copy()
for row_index, row in enumerate(UpperCAmelCase__ ):
SCREAMING_SNAKE_CASE = row[0]
for column_index, column in enumerate(UpperCAmelCase__ ):
... | 647 | import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(a ) , """Tatoeba direc... | 647 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase : Any = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''MobileNetV2Config''',
... | 647 | import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import C... | 647 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
_lowerCamelCase : Dict = 6_378_137.0
_lowerCamelCase : List[str] = 6_356_752.314_245
_lowerCamelCase : str = 6_37_81_37
def __lowerCamelCase (UpperCAmelCase__ : float , UpperCAmelCase__... | 647 | from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageIn... | 647 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 647 | import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 647 | 1 |
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_pytorch_model
from transform... | 647 | from typing import Dict, List, Optional, Union
import numpy as np
from .feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from .utils import PaddingStrategy, TensorType, is_tf_tensor, is_torch_tensor, logging, to_numpy
_lowerCamelCase : Optional[Any] = logging.get_logger(__na... | 647 | 1 |
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 647 | import functools
def __lowerCamelCase (UpperCAmelCase__ : list[int] , UpperCAmelCase__ : list[int] ):
# Validation
if not isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) or not all(isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) for day in days ):... | 647 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Spl... | 647 | from __future__ import annotations
import math
def __lowerCamelCase (UpperCAmelCase__ : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, al... | 647 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_n... | 647 | import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 647 | 1 |
from math import factorial, radians
def __lowerCamelCase (UpperCAmelCase__ : float , UpperCAmelCase__ : int = 1_8 , UpperCAmelCase__ : int = 1_0 ):
SCREAMING_SNAKE_CASE = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Conve... | 647 | import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
... | 647 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : int = 1_0_0_0_0_0_0 ):
SCREAMING_SNAKE_CASE = set(range(3 , UpperCAmelCase__ , 2 ) )
primes.add(2 )
for p in range(3 , UpperCAmelCase__ , 2 ):
if p not in primes:
continue
... | 647 | import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase : Dict = logging.get_logger(__name__)
_lowerCamelCase : List[Any] = '''... | 647 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
... | 647 | import numpy as np
def __lowerCamelCase (UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : np.ndarray , UpperCAmelCase__ : float = 1e-12 , UpperCAmelCase__ : int = 1_0_0 , ):
assert np.shape(UpperCAmelCase__ )[0] == np.shape(UpperCAme... | 647 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
_lowerCamelCase : str = HfArgumentParser(InitializationArguments)
_lowerCamelCase : Optional[Any] = parser.parse_args()
# Load c... | 647 | import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
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... | 647 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCamelCase : str = {
'''shi-la... | 647 | import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
_lowerCamelCase : ... | 647 | 1 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class lowercase ( n... | 647 | def __lowerCamelCase (UpperCAmelCase__ : int ):
assert isinstance(UpperCAmelCase__ , UpperCAmelCase__ ), F"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE = F"The input value o... | 647 | 1 |
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : int = logging.get_logger(__name__)
_lowerCamelCase... | 647 | 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 lowercase ( unittest.TestCase ):
... | 647 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : int ):
if upper_limit < 0:
raise ValueError("Limit for the Catalan sequence must be ≥ 0" )
SCREAMING_SNAKE_CASE = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
SCREAMING_SNAKE_CASE = 1
... | 647 | import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase ( a ):
lowercase__ : Tuple = (KDPMaDiscreteScheduler,)
lowercase__ : Optiona... | 647 | 1 |
def __lowerCamelCase (UpperCAmelCase__ : int ):
if isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
raise TypeError("'str' objec... | 647 | from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_lowerCamelCase : Tuple = {
'''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
'''susnato/ernie-m-large_pytor... | 647 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingfac... | 647 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Optional[int] = {
'''configuration_blenderbot''': [
... | 647 | 1 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformer... | 647 | from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_lowerCamelCase : Optional[Any] = TypeVar('''T''')
class lowercase ( Generic[T] ):
def __init__( self : Any , _UpperCamelCase : T ... | 647 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase : Tuple = {
'''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
'''tokenizat... | 647 | # coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by a... | 647 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.