code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
def _snake_case ( _snake_case : int = 1 , _snake_case : int = 10_00 ) -> int:
'''simple docstring'''
_A = 1
_A = 0
for divide_by_number in range(_snake_case , digit + 1 ):
_A = []
... | 7 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Any = ['''image_processor''', '''tokenizer''']
UpperCAmel... | 7 | 1 |
"""simple docstring"""
a = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingfac... | 7 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 1 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
a = re.compile(r'''([A-Z]+)([A-Z][a-z])''')
a = re.compile(r'''([a-z\d])([A-Z])''')
a = re.compile(r'''(?<!_)_(?!_)''')
a = re.compile(r'''(_{2,})''')
a = ... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
c... | 7 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class lowercase_ ( unittest.TestCas... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
return " ".join(
''.join(word[::-1] ) if len(_snake_case ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfi... | 7 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Optional[int] = (KDPMaDis... | 7 | 1 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class lowercase_ ( unittest.TestCase , __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Optional[Any] ):
_A ... | 7 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 7 | 1 |
"""simple docstring"""
from math import factorial, pi
def _snake_case ( _snake_case : float , _snake_case : int = 30 ) -> float:
'''simple docstring'''
if not isinstance(_snake_case , (int, float) ):
raise ValueError('maclaurin_si... | 7 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if (
not isinstance(_snake_case , (int, float) )
or power_factor < -1
or power_fac... | 7 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''BAAI/AltCLIP''': '''https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json'... | 7 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/xmod-base''': '''https://... | 7 | 1 |
"""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... | 7 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxrunt... | 7 | 1 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transfo... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
a = {
'''configuration_graphormer''': ['''GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GraphormerConfig'''],
}
try:
... | 7 |
"""simple docstring"""
from manim import *
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Union[str, Any] ):
_A = Rectangle(height=0.5 , width=0.5 )
_A = Rectangle(height=0.46 , w... | 7 | 1 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils ... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : int , _snake_case : int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def _snake_case ( ) -> None:
'''simple docstring'''
asser... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int ) -> int:
'''simple docstring'''
_A = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _snake_case ( _snake_case : int = 1_00 ) ... | 7 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
a = logging.getLogger(__name__)
@dataclass
class lowercase_ ( __lowerCAmelCase ):
... | 7 | 1 |
"""simple docstring"""
import math
import qiskit
def _snake_case ( _snake_case : int = 1 , _snake_case : int = 1 , _snake_case : int = 1 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(_snake_case ,... | 7 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
a = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
]... | 7 | 1 |
"""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,
Image... | 7 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase_ ( __lowerCAmelCas... | 7 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_... | 7 |
"""simple docstring"""
class lowercase_ :
'''simple docstring'''
def __init__( self : List[Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : int ):
_A = None
_A = None
_A = graph... | 7 | 1 |
"""simple docstring"""
a = {
0: '''0''',
1: '''1''',
2: '''2''',
3: '''3''',
4: '''4''',
5: '''5''',
6: '''6''',
7: '''7''',
8: '''8''',
9: '''9''',
10: '''a''',
11: '''b''',
12: '''c''',
13: '''d''',
14: '''e''',
15: '''f''',
}
... | 7 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_to... | 7 | 1 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 7 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int = 10_00 ) -> int:
'''simple docstring'''
_A = 2**power
_A = str(_snake_case )
_A = list(_snake_case )
_A = 0
for i in list_num:
sum_of_num += int(_snake... | 7 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 | 1 |
"""simple docstring"""
from collections.abc import Callable
def _snake_case ( _snake_case : Callable[[float], float] , _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
_A = a
_A = b
if funct... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE mode... | 7 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTe... | 7 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 7 | 1 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class lowercase_ :
'''simple docstring'''
def __init__( self : Dict ):
_A = [2, 1, 2, -1]
_A = [1, 2, 3, 4]
def lowerCAmelCase_ ( self : Dict ):... | 7 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( _snake_case : Dict ) -> Optional[Any]:
'''simple docstring'''
for param in module.parameters():
_A = False
def _snake_case ( ... | 7 | 1 |
"""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 (
... | 7 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Any = ['''image_processor''', '''tokenizer''']
UpperCAmel... | 7 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def _snake_case ( _snake_case : Sequence[float] , _snake_case : bool = False ) -> float:
'''simple docstring'''
if not arr:
return 0
_A = 0 if allow_empty_subarrays else ... | 7 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 1 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
c... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Mask2FormerConfig'''... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
return " ".join(
''.join(word[::-1] ) if len(_snake_case ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
... | 7 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase_ ( metaclass=__lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Union[str, Any] = ['''transformers''', '''torch''', '''note_seq''']
def __init__( self : str , ... | 7 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Optional[int] = (KDPMaDis... | 7 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Optional[int] = '''bert-generation'''
def __init__( self : Optional[int] , _UpperCAmelCase : Optiona... | 7 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 7 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 7 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if (
not isinstance(_snake_case , (int, float) )
or power_factor < -1
or power_fac... | 7 | 1 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/xmod-base''': '''https://... | 7 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
a = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''albert-large-v1''... | 7 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxrunt... | 7 | 1 |
"""simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionMod... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config... | 7 | 1 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won... | 7 |
"""simple docstring"""
from manim import *
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Union[str, Any] ):
_A = Rectangle(height=0.5 , width=0.5 )
_A = Rectangle(height=0.46 , w... | 7 | 1 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''RUCAIBox/mvp''': '''https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json''',
}
class lowerca... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : int , _snake_case : int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def _snake_case ( ) -> None:
'''simple docstring'''
asser... | 7 | 1 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''vocab_file''': '''vocab.json''',
... | 7 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
a = logging.getLogger(__name__)
@dataclass
class lowercase_ ( __lowerCAmelCase ):
... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int ) -> bool:
'''simple docstring'''
_A = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 7 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
a = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
]... | 7 | 1 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if (
not isinstance(_snake_case , (int, float) )
or power_factor < -1
or power_fac... | 7 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase_ ( __lowerCAmelCas... | 7 | 1 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 7 |
"""simple docstring"""
class lowercase_ :
'''simple docstring'''
def __init__( self : List[Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : int ):
_A = None
_A = None
_A = graph... | 7 | 1 |
"""simple docstring"""
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configurat... | 7 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_to... | 7 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pi... | 7 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 7 | 1 |
"""simple docstring"""
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class lowercase_ ( yaml.SafeLoader ):
'''simple docstring'''
def lowerCAmelCase_ ( self : List[str] , _UpperCAmelCase : List[Any] ... | 7 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common import... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE mode... | 7 | 1 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _snake_case ( _snake_case : Tuple , _snake_case : str ) -> Any:
'''simple docstring'''
for e in env_keys:
_A = int(os.environ.get(_snake_case , -1 ) ... | 7 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 7 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase_ ( __lowerCAmelCase ,... | 7 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( _snake_case : Dict ) -> Optional[Any]:
'''simple docstring'''
for param in module.parameters():
_A = False
def _snake_case ( ... | 7 | 1 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _snake_case ( _snake_case : float ) -> float:
'''simple docstring'''
if num <= 0:
raise ValueError('math domain error' )
return quad(_snake_case ... | 7 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Any = ['''image_processor''', '''tokenizer''']
UpperCAmel... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int , _snake_case : int ) -> int:
'''simple docstring'''
while second != 0:
_A = first & second
first ^= second
_A = c << 1
return first
if __name__ ==... | 7 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
a = logging.get_logger(__name__)
a = {
'''CarlCochet/trajectory-transformer-halfcheetah-medium-v2''': (
'''https://huggingface.co/CarlCochet/trajectory-transform... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
c... | 7 | 1 |
"""simple docstring"""
a = tuple[float, float, float]
a = tuple[float, float, float]
def _snake_case ( _snake_case : Pointad , _snake_case : Pointad ) -> Vectorad:
'''simple docstring'''
_A = end_pointa[0] - end_point... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
return " ".join(
''.join(word[::-1] ) if len(_snake_case ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
... | 7 | 1 |
"""simple docstring"""
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def _snake_case ( _snake_case : int , _snake_case : int , _snake_case : float = 1 / sqrt(2 ) ) -> IIRFilter:
'''simple docstring'''
... | 7 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Optional[int] = (KDPMaDis... | 7 | 1 |
"""simple docstring"""
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class lowercase... | 7 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> list:
'''simple docstring'''
_A = [0] * len(_snake_case )
for i in range(1 , len(_snake_case ) ):
# use last results for better performance - dynamic programming
... | 7 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if (
not isinstance(_snake_case , (int, float) )
or power_factor < -1
or power_fac... | 7 | 1 |
"""simple docstring"""
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
a = 10
def _snake_case ( _snake_case : int , _snake_case : int ... | 7 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/xmod-base''': '''https://... | 7 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/nllb-moe-54B''': '''https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json''',
}
class lowerc... | 7 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxrunt... | 7 | 1 |
"""simple docstring"""
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
fro... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
a = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 7 |
"""simple docstring"""
from manim import *
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Union[str, Any] ):
_A = Rectangle(height=0.5 , width=0.5 )
_A = Rectangle(height=0.46 , w... | 7 | 1 |
"""simple docstring"""
import requests
a = '''YOUR API KEY'''
def _snake_case ( _snake_case : str , _snake_case : str = giphy_api_key ) -> list:
'''simple docstring'''
_A = '+'.join(query.split() )
_A = F'''https://api... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : int , _snake_case : int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def _snake_case ( ) -> None:
'''simple docstring'''
asser... | 7 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils ... | 7 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
a = logging.getLogger(__name__)
@dataclass
class lowercase_ ( __lowerCAmelCase ):
... | 7 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from .... | 7 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
a = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
]... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 7 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase_ ( __lowerCAmelCas... | 7 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logg... | 7 |
"""simple docstring"""
class lowercase_ :
'''simple docstring'''
def __init__( self : List[Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : int ):
_A = None
_A = None
_A = graph... | 7 | 1 |
"""simple docstring"""
import random
def _snake_case ( _snake_case : List[str] , _snake_case : int , _snake_case : Dict ) -> Dict:
'''simple docstring'''
_A = a[left_index]
_A = left_index + 1
for j in range(left_index... | 7 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_to... | 7 | 1 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import ... | 7 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 7 | 1 |
"""simple docstring"""
a = 8.3_1_4_4_6_2 # Unit - J mol-1 K-1
def _snake_case ( _snake_case : float , _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
... | 7 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 | 1 |
"""simple docstring"""
import math
import os
import sys
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
_A = ''
try:
with open(_snake_case , 'rb' ) as binary_file:
_A = binary_file.read()
... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE mode... | 7 | 1 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( _snake_case : int = 4 ) -> list[list[int]]:
'''simple docstring'''
_A = abs(_snake_case ) or 4
return [[1 + x + y * row_size for x in range(_snake_case )] for y in range(_snak... | 7 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 7 | 1 |
"""simple docstring"""
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBe... | 7 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( _snake_case : Dict ) -> Optional[Any]:
'''simple docstring'''
for param in module.parameters():
_A = False
def _snake_case ( ... | 7 | 1 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( _snake_case : list , _snake_case : int ) -> Optional[Any]:
'''simple docstring'''
if len(_snake_case ) <= 1 or n <= 1:
return
insert_next(_snake_case ... | 7 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Any = ['''image_processor''', '''tokenizer''']
UpperCAmel... | 7 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
c... | 7 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbo... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
c... | 7 | 1 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _snake_case ( _snake_case : int = 3 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if isinstance(_sna... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
return " ".join(
''.join(word[::-1] ) if len(_snake_case ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {
'''configuration_upernet''': ['''UperNetConfig'''],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailab... | 7 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Optional[int] = (KDPMaDis... | 7 | 1 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
... | 7 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 7 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
a = ... | 7 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if (
not isinstance(_snake_case , (int, float) )
or power_factor < -1
or power_fac... | 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
a = {'''tokenization_wav2vec2_phoneme''': ['''Wav2Vec2PhonemeCTCTokenizer''']}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
import sys
... | 7 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/xmod-base''': '''https://... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
if not all(char in '01' for char in bin_string ):
raise ValueError('Non-binary value was passed to the function' )
if not bin_string:
raise ValueE... | 7 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxrunt... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError('number must not be negative' )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doc... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config... | 7 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_to... | 7 |
"""simple docstring"""
from manim import *
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Union[str, Any] ):
_A = Rectangle(height=0.5 , width=0.5 )
_A = Rectangle(height=0.46 , w... | 7 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
a = logging.getLogger(... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : int , _snake_case : int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def _snake_case ( ) -> None:
'''simple docstring'''
asser... | 7 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase_ ( __lowerCAmelCas... | 7 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
a = logging.getLogger(__name__)
@dataclass
class lowercase_ ( __lowerCAmelCase ):
... | 7 | 1 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( _snake_case : list[float] , _snake_case : list[float] ) -> float:
'''simple docstring'''
_A = sorted(numsa + numsa )
_A , _A = divmod(len(_snake_case ... | 7 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
a = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
]... | 7 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
a = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generatio... | 7 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase_ ( __lowerCAmelCas... | 7 | 1 |
"""simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a = logging.get_logger(__name__)
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring''... | 7 |
"""simple docstring"""
class lowercase_ :
'''simple docstring'''
def __init__( self : List[Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : int ):
_A = None
_A = None
_A = graph... | 7 | 1 |
"""simple docstring"""
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
'split_dict' , [
SplitDict(),
SplitDict({'train': SplitInfo(name='train' , num_bytes=13_37 , num_examples... | 7 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_to... | 7 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}
class lowercase_ ( _... | 7 |
"""simple docstring"""
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 7 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''V... | 7 |
"""simple docstring"""
import argparse
a = '''docs/source/_static/js/custom.js'''
def _snake_case ( _snake_case : Dict ) -> Any:
'''simple docstring'''
with open(_snake_case , encoding='utf-8' , newline='\n' ) as f:
_... | 7 | 1 |
"""simple docstring"""
import unittest
import numpy as np
def _snake_case ( _snake_case : np.ndarray , _snake_case : np.ndarray , _snake_case : np.ndarray , _snake_case : np.ndarray | None = None , ) -> np.ndarray:
'''simple do... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE mode... | 7 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
a = logging.get_logger(__name__)
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def __init__( self : Optional[int] , ... | 7 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transforme... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F'''{price_plus_tax(100, 0.2_5) = }''')
print(F'''{price_plus_t... | 7 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( _snake_case : Dict ) -> Optional[Any]:
'''simple docstring'''
for param in module.parameters():
_A = False
def _snake_case ( ... | 7 | 1 |
"""simple docstring"""
a = 256
# Modulus to hash a string
a = 1_000_003
def _snake_case ( _snake_case : str , _snake_case : str ) -> bool:
'''simple docstring'''
_A = len(_snake_case )
_A = len(_snake_ca... | 7 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Any = ['''image_processor''', '''tokenizer''']
UpperCAmel... | 7 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''goo... | 7 |
"""simple docstring"""
import math
from datetime import datetime, timedelta
def _snake_case ( _snake_case : int ) -> datetime:
'''simple docstring'''
_A = year % 19
_A = year % 4
_A = year % 7
_A = math.floor(year / 1_00 )
... | 7 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/xmod-base''': '''https://... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
c... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : list[list[int]] , _snake_case : int , _snake_case : int , _snake_case : set ) -> int:
'''simple docstring'''
_A , _A = len(_snake_case ), len(grid[0] )
i... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : str ) -> str:
'''simple docstring'''
return " ".join(
''.join(word[::-1] ) if len(_snake_case ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
... | 7 | 1 |
"""simple docstring"""
a = '''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_lib... | 7 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
UpperCAmelCase : Optional[int] = (KDPMaDis... | 7 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( __lowerCAmelCase ):
... | 7 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 7 | 1 |
"""simple docstring"""
def _snake_case ( _snake_case : int ) -> bool:
'''simple docstring'''
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('''Program to check whether a number is a P... | 7 |
"""simple docstring"""
import math
def _snake_case ( _snake_case : float , _snake_case : float ) -> float:
'''simple docstring'''
if (
not isinstance(_snake_case , (int, float) )
or power_factor < -1
or power_fac... | 7 | 1 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def _snake_case ( _snake_case : str = "AAPL" ) -> str:
'''simple docstring'''
_A = F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
_A = BeautifulSoup(requests.get(_snake... | 7 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/xmod-base''': '''https://... | 7 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config... | 7 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxrunt... | 7 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 7 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
a = {
'''facebook/s2t-small-librispeech-asr''': (
'''https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config... | 7 | 1 |
"""simple docstring"""
import itertools
import string
from collections.abc import Generator, Iterable
def _snake_case ( _snake_case : Iterable[str] , _snake_case : int ) -> Generator[tuple[str, ...], None, None]:
'''simple docstring'''
_A = iter(_sn... | 7 |
"""simple docstring"""
from manim import *
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Union[str, Any] ):
_A = Rectangle(height=0.5 , width=0.5 )
_A = Rectangle(height=0.46 , w... | 7 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
... | 7 |
"""simple docstring"""
def _snake_case ( _snake_case : int , _snake_case : int ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def _snake_case ( ) -> None:
'''simple docstring'''
asser... | 7 | 1 |
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