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'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
UpperCAmelCase_ : List... | 24 |
"""simple docstring"""
import baseaa
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baaencode(string.encode("utf-8" ) )
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baadecode(_UpperCamelCase ).decode("utf-... | 636 | 0 |
def lowerCAmelCase__ ( _a : Optional[Any] , _a : Tuple , _a : Tuple , _a : Optional[Any] , _a : int , _a : List[Any] ):
if index == r:
for j in range(_UpperCamelCase ):
print(data[j] , end=" " )
... | 568 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_t... | 636 | 0 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import ... | 148 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a ):
__lowerCAmelCase = str(id_ )
__lowerCAmelCase = No... | 636 | 0 |
"""simple docstring"""
from __future__ import annotations
def __snake_case ( __A ,__A = None ,__A = None ) -> Optional[int]:
if start is None:
lowercase : Tuple = 0
if end is None:
lowercase : Tuple = len(_UpperC... | 607 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A : Optional[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 636 | 0 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase ) -> List[str]:
'''simple docstring'''
lowercase_ , lowercase_ = np.shape(_UpperCamelCase )
if rows != columns:... | 567 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Union[str, Any] = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_avail... | 636 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __snake_case ( lowerCAmelCase__ ):
@staticmethod
@abstractmethod
def _snake_case ( UpperCamelCase_ ) -> Any:
raise NotImplementedError(... | 368 |
"""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.activations import gelu_new, gelu_python, get_activation
@require_torch
class _UpperCamelCase ( unittest.Test... | 636 | 0 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class __lowercase (lowerCAmelCase__... | 101 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mo... | 636 | 0 |
from sklearn.metrics import fa_score
import datasets
__lowerCamelCase : Optional[int] = "\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n"
__lowerCamelCase : Dict = "\nArgs:\n ... | 323 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowerCAmelCase = True
for i in range(0 , le... | 636 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
... | 125 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 636 | 0 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Optional[Any] = logging.get_logger(__name__)
# TODO Update this
_snake_case : Optional[Any] ... | 22 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : int =["""torch"""]
def __init__( self , *__a , **__a ):
requ... | 636 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
"google/vivit-b-16x2-kinetics400": (
"https://huggingface.co/google/vivit-b-16x2-kinetics400/r... | 688 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(_UpperCamelCase ... | 636 | 0 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
UpperCAmelCase_ : List[str] = "\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Te... | 24 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = [False] * len(_UpperCamelCase )
__lowerCAmelCase = []
queue.appe... | 636 | 0 |
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 TokenizerTesterMixin
lowe... | 568 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase__ )
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstr... | 636 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : str ={
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanlp/visualbert-vqa-p... | 148 |
"""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 _UpperCamelCase ... | 636 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase: List[str] ={
"configuration_graphormer": ["GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "GraphormerConf... | 607 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : List[str] ="""Speech2TextFeatureExtractor"""
__Up... | 636 | 0 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
UpperCAmelCase : Dict = get_logger(__name__)
UpperCAmelCase : Dict = R"\n Args:\n inp... | 567 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load... | 636 | 0 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import data... | 368 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentPars... | 636 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ : Union[str, Any] ={
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_av... | 101 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A : Dict = get_logger(__name__)
A : Dict = R"\n Args:\n input_ids (`jnp.ndarray` of shape `(... | 636 | 0 |
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
IMAGENET_STANDARD_MEAN,... | 323 |
"""simple docstring"""
from __future__ import annotations
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a=None ):
__lowerCAmelCase = data
__lowerCAmelCase = None
def __repr__( self )... | 636 | 0 |
'''simple docstring'''
from math import ceil
def SCREAMING_SNAKE_CASE ( lowerCAmelCase__ : Any = 10_01) -> List[Any]:
'''simple docstring'''
_lowercase : List[Any] = 1
for i in range(1 , int(ceil(n / 2.0))):
_lowercase : List[st... | 125 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : Tuple =(... | 636 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_snake_case : Dict = {
"configuration_trocr": ["TROCR_PRETRAI... | 22 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
A : List[Any] = ... | 636 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.... | 688 |
"""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 .token... | 636 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class lowerCAmelCase :
def __init__( self , __SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
'''simple docstring'''
__snake_case = value
__sn... | 24 |
"""simple docstring"""
import baseaa
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baaencode(string.encode("utf-8" ) )
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baadecode(_UpperCamelCase ).decode("utf-... | 636 | 0 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
... | 568 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_t... | 636 | 0 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 148 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a ):
__lowerCAmelCase = str(id_ )
__lowerCAmelCase = No... | 636 | 0 |
"""simple docstring"""
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_downl... | 607 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A : Optional[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 636 | 0 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase ) -> Tuple:
'''simple docstring'''
assert isinstance(_UpperCamelCase , _UpperCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number <... | 567 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Union[str, Any] = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_avail... | 636 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import List, Optional
class __snake_case ( lowerCAmelCase__ ):
def __init__( self ) -> Optional[int]:
# test for the above condition
self.test()
def _snake_... | 368 |
"""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.activations import gelu_new, gelu_python, get_activation
@require_torch
class _UpperCamelCase ( unittest.Test... | 636 | 0 |
def a__ ( A__, A__ ):
print('\nThe shortest path matrix using Floyd Warshall algorithm\n' )
for i in range(_UpperCamelCase ):
for j in range(_UpperCamelCase ):
if dist[i][j] != float('inf' ):
print(int(dist[i][j] ), end='\t' )
... | 101 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mo... | 636 | 0 |
def lowerCamelCase_(lowerCamelCase_ , lowerCamelCase_ ) -> int:
UpperCAmelCase = len(_UpperCamelCase )
UpperCAmelCase = len(_UpperCamelCase )
UpperCAmelCase = [[False for _ in range(m + 1 )] for _ in range(n + 1 )]
UpperCAmelCase ... | 323 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowerCAmelCase = True
for i in range(0 , le... | 636 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils i... | 125 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 636 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case : List[str] = logging.get_logger(__name__)
class A ( lowerCAmelCase__ ):
def __init__( self : Dict ... | 22 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : int =["""torch"""]
def __init__( self , *__a , **__a ):
requ... | 636 | 0 |
'''simple docstring'''
import requests
__SCREAMING_SNAKE_CASE = "https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey="
def __a ( lowerCAmelCase__ : str ):
a__ : Tuple = requests.get(_NEWS_API + bbc_news_api_key ).json()
# each article i... | 688 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(_UpperCamelCase ... | 636 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_... | 24 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = [False] * len(_UpperCamelCase )
__lowerCAmelCase = []
queue.appe... | 636 | 0 |
import argparse
import os
import re
import zipfile
import torch
from transformers import AutoTokenizer, GPTaConfig
def lowerCAmelCase__ ( _a : Optional[int] , _a : Any , _a : Any=0 ):
if name is None:
snake_case_ : List[Any] = No... | 568 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase__ )
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstr... | 636 | 0 |
from __future__ import annotations
from collections.abc import Callable
lowerCAmelCase__ : Any =list[list[float | int]]
def __lowercase ( a__ , a__ ) -> Union[str, Any]:
__SCREAMING_SNAKE_CASE = len(_UpperCamelCase )
__SCREAMING_SNAKE_CASE ... | 148 |
"""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 _UpperCamelCase ... | 636 | 0 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_availa... | 607 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : List[str] ="""Speech2TextFeatureExtractor"""
__Up... | 636 | 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():... | 567 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load... | 636 | 0 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
a__ : str = logging.get_logger(__name__)
def __lowerCamelCase ( UpperCAmel... | 368 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentPars... | 636 | 0 |
from copy import deepcopy
class __lowercase :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ = None , lowerCAmelCase__ = None ):
"""simple docstring"""
if arr is None and size ... | 101 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A : Dict = get_logger(__name__)
A : Dict = R"\n Args:\n input_ids (`jnp.ndarray` of shape `(... | 636 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase__ )
class __magic_name__ ( lowerCAmelCase__ ):
lowercase : str =field(default='... | 323 |
"""simple docstring"""
from __future__ import annotations
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a=None ):
__lowerCAmelCase = data
__lowerCAmelCase = None
def __repr__( self )... | 636 | 0 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE ( lowerCAmelCase__ , unittest.TestCase ):
... | 125 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : Tuple =(... | 636 | 0 |
'''simple docstring'''
from math import factorial, radians
def snake_case_ (UpperCamelCase : Any , UpperCamelCase : int = 18 , UpperCamelCase : List[str] = 10 ):
'''simple docstring'''
_a = angle_in_degrees - ((angle_in_degre... | 22 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
A : List[Any] = ... | 636 | 0 |
'''simple docstring'''
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, lo... | 688 |
"""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 .token... | 636 | 0 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def _UpperCamelCase (_lowerCamelCase : Tuple )-> List[Any]:
'''simple docstring'''
def decorator(_lowerCamelCase : Optional[Any] ):
__snake_case = ge... | 24 |
"""simple docstring"""
import baseaa
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baaencode(string.encode("utf-8" ) )
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baadecode(_UpperCamelCase ).decode("utf-... | 636 | 0 |
from __future__ import annotations
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , _SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
snake_case_ : Dict = data
snake_case_ : Union[str, Any] = None
... | 568 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_t... | 636 | 0 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowerCAmelCase__ : Dict =logging.get_logger(__name__)... | 148 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a ):
__lowerCAmelCase = str(id_ )
__lowerCAmelCase = No... | 636 | 0 |
"""simple docstring"""
lowerCAmelCase: Tuple =8.3_1_4_4_5_9_8
def __snake_case ( __A ,__A ) -> List[Any]:
if temperature < 0:
raise Exception("""Temperature cannot be less than 0 K""" )
if molar_mass <= 0:
raise Exception("""Molar ... | 607 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A : Optional[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 636 | 0 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def _SCREAMING_SNAKE_CASE (__lowerCA... | 567 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Union[str, Any] = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_avail... | 636 | 0 |
'''simple docstring'''
import os
import sys
import unittest
a__ : Any = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ... | 368 |
"""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.activations import gelu_new, gelu_python, get_activation
@require_torch
class _UpperCamelCase ( unittest.Test... | 636 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowerCAmelCase__ : Union[str, Any] =logging.get_logger(__name__)
class __lowercase (lowerCAmelCase__ ):
"""simple docstring"""
def _... | 101 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mo... | 636 | 0 |
from functools import lru_cache
@lru_cache
def lowerCamelCase_(lowerCamelCase_ ) -> Optional[Any]:
if num < 0:
raise ValueError("Number should not be negative." )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__main__":
import doctest... | 323 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowerCAmelCase = True
for i in range(0 , le... | 636 | 0 |
'''simple docstring'''
import math
def SCREAMING_SNAKE_CASE ( lowerCAmelCase__ : int) -> Union[str, Any]:
'''simple docstring'''
_lowercase : Any = math.loga(math.sqrt(4 * positive_integer + 1) / 2 + 1 / 2)
return exponent == int(_UpperCamelCase)
d... | 125 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 636 | 0 |
'''simple docstring'''
def snake_case_ (UpperCamelCase : int ):
'''simple docstring'''
_a = [[0 for _ in range(_UpperCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
_a = 1
for n in range(m... | 22 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : int =["""torch"""]
def __init__( self , *__a , **__a ):
requ... | 636 | 0 |
'''simple docstring'''
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_g... | 688 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(_UpperCamelCase ... | 636 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase ( lowerCAmelCase__):
... | 24 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = [False] * len(_UpperCamelCase )
__lowerCAmelCase = []
queue.appe... | 636 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMSch... | 568 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase__ )
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstr... | 636 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Optional[Any] =logging.get_logger(__name__)
lowerCAmelCase__ : Dict ={
"alibaba-damo/mgp-str-base": "https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json",
}
class Upp... | 148 |
"""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 _UpperCamelCase ... | 636 | 0 |
"""simple docstring"""
from math import ceil
def __snake_case ( __A ,__A ) -> Any:
lowercase : str = list(range(0 ,_UpperCamelCase ) )
lowercase : Any = [item for sublist in list(device_map.values() ) for item in sublist]
... | 607 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : List[str] ="""Speech2TextFeatureExtractor"""
__Up... | 636 | 0 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase : Union[str, Any] = []
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> Optional[int]:
'''simple docstring'''
for i in range(len(_UpperC... | 567 |
"""simple docstring"""
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load... | 636 | 0 |
'''simple docstring'''
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __snake_case ( ctypes.Structure ):
__lowerCAmelCase = [("""size""", ctyp... | 368 |
"""simple docstring"""
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentPars... | 636 | 0 |
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : str = [0] * len(_UpperCamelCase )
for i in range(1, len(_UpperCamelCase ) ):
# use last results for better performance - dynamic programming
SCREAMING_SNAKE_CASE_ : str = prefix_result[i - 1]
... | 101 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
A : Dict = get_logger(__name__)
A : Dict = R"\n Args:\n input_ids (`jnp.ndarray` of shape `(... | 636 | 0 |
from __future__ import annotations
def lowerCamelCase_(lowerCamelCase_ ) -> Any:
UpperCAmelCase = str(_UpperCamelCase )
return n == n[::-1]
def lowerCamelCase_(lowerCamelCase_ = 1_000_000 ) -> str:
UpperCAmelCase = 0
for i in range(1 , _Up... | 323 |
"""simple docstring"""
from __future__ import annotations
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a=None ):
__lowerCAmelCase = data
__lowerCAmelCase = None
def __repr__( self )... | 636 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ) -> Dict:
'''simple docstring'''
return [list(range(10_00 - i , -10_00 - i , -1)) for i in range(10_00)]
A = generate_large_matrix()
A = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2... | 125 |
"""simple docstring"""
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : Tuple =(... | 636 | 0 |
'''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def snake_case_ (UpperCamelCase : Tuple , UpperCamelCase : Optional[Any]=1000 ):
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
... | 22 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
A : List[Any] = ... | 636 | 0 |
'''simple docstring'''
def __a ( lowerCAmelCase__ : str ):
if number > 0:
raise ValueError('''input must be a negative integer''' )
a__ : Dict = len(bin(_UpperCamelCase )[3:] )
a__ : str = bin(abs(_UpperCamelCase ... | 688 |
"""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 .token... | 636 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffuser... | 24 |
"""simple docstring"""
import baseaa
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baaencode(string.encode("utf-8" ) )
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
return baseaa.baadecode(_UpperCamelCase ).decode("utf-... | 636 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Optional[int] = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",... | 568 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_t... | 636 | 0 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __lowercase ( a__ ) -> int:
def wrapper(*a__ , **a__ ):
__SCREAMING_SNAKE_CASE = timeit.default_ti... | 148 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , __a ):
__lowerCAmelCase = str(id_ )
__lowerCAmelCase = No... | 636 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase: Optional[Any] ={
"configuration_mobilebert": [
... | 607 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A : Optional[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 636 | 0 |
"""simple docstring"""
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE__ ( lowerCAmelCase__ ):
lowercase__ = """Speech2TextFeatureExtractor"""
lowercase__ = """Speech2TextTokenizer"""
def __i... | 567 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A : Union[str, Any] = {
"configuration_timesformer": ["TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "TimesformerConfig"],
}
try:
if not is_torch_avail... | 636 | 0 |
'''simple docstring'''
from __future__ import annotations
class __snake_case :
def __init__( self , UpperCamelCase_=None ) -> Optional[Any]:
snake_case__ = data
snake_case__ = None
def __repr__( self ) ->... | 368 |
"""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.activations import gelu_new, gelu_python, get_activation
@require_torch
class _UpperCamelCase ( unittest.Test... | 636 | 0 |
from collections import defaultdict
def a__ ( A__ ):
SCREAMING_SNAKE_CASE_ : List[str] = 1
SCREAMING_SNAKE_CASE_ : List[Any] = True
for v in tree[start]:
if v not in visited:
ret += dfs(_UpperCamelCase )
if ret % 2 == 0:
... | 101 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, 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_mo... | 636 | 0 |
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTe... | 323 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowerCAmelCase = True
for i in range(0 , le... | 636 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowerCAmelCase__ : Any , lowerCAmelCase__ : Any) -> str:
'''simple docstring'''
return int((input_a, input_a).count(0) != 0)
def SCREAMING_SNAKE_CASE ( ) -> List[Any]:
'''simple doc... | 125 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
... | 636 | 0 |
'''simple docstring'''
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import P... | 22 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=lowerCAmelCase__ ):
'''simple docstring'''
__UpperCAmelCase : int =["""torch"""]
def __init__( self , *__a , **__a ):
requ... | 636 | 0 |
'''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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTIma... | 688 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(_UpperCamelCase ... | 636 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler... | 24 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = [False] * len(_UpperCamelCase )
__lowerCAmelCase = []
queue.appe... | 636 | 0 |
import heapq as hq
import math
from collections.abc import Iterator
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , _SCREAMING_SNAKE_CASE ) -> List[str]:
snake_case_ : Optional[Any] = str(id_ )
snake_case_ ... | 568 |
"""simple docstring"""
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase__ )
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstr... | 636 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dimens... | 148 |
"""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 _UpperCamelCase ... | 636 | 0 |
def _SCREAMING_SNAKE_CASE ( __lowercase : int ) -> "list[int]":
"""simple docstring"""
if upper_limit < 0:
raise ValueError("""Limit for the Catalan sequence must be ≥ 0""" )
__A = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__A... | 637 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer
... | 637 | 1 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 637 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__a : Any = {
"configuration_time_series_transformer": [
"TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TimeSeriesTransformerConfig",
],
}
try:... | 637 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
__a : Optional[int] = (3, 9, -11, 0, 7, 5, 1, -1)
__a : Tuple = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __lowercase :
'''simple docstring'''
... | 637 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequence... | 637 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a : Dict = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():
raise OptionalDependencyNo... | 637 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : Dict = logging.get_logger(__name__)
__a : Dict = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json",
}
class __lowercase ... | 637 | 1 |
from itertools import count
def _SCREAMING_SNAKE_CASE ( __lowercase : int = 5_0 ) -> int:
"""simple docstring"""
__A = [1] * min_block_length
for n in count(__lowercase ):
fill_count_functions.append(1 )
for block_length in range(... | 637 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __lowercase : list[int] , __lowercase : int ) -> bool:
"""simple docstring"""
if len(__lowercase ) == 0:
return False
__A = len(__lowercase ) // 2
if a_list[mi... | 637 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFM... | 637 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 637 | 1 |
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class __lowercase ( lowercase_ , unittest.TestCase ):
... | 637 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__a : List[str] = "▁"
__a : int = {"vocab_file": "spiece.model"}
__a : A... | 637 | 1 |
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
class __lowercase ... | 637 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : Optional[Any] = logging.get_logger(__name__)
__a : Dict = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/c... | 637 | 1 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __lowercase ( lowercase_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = (KDPMaDiscreteScheduler,)
SCREAMING_SNAKE... | 637 |
import argparse
import os
import re
import packaging.version
__a : Tuple = "examples/"
__a : Any = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=\s+\"([^\"]+)\"\s*$"... | 637 | 1 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
__a... | 637 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__a : List[Any] = logging.get_logger(__name__)
# TODO: upload to AWS
__a : Union[str, Any] = {
"yjernite/retribert-base-uncased": (
"https://huggingface.co/yjernite/retribert-base-uncased/r... | 637 | 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.huggingface import HuggingF... | 637 |
def _SCREAMING_SNAKE_CASE ( __lowercase : List[Any] ) -> Any:
"""simple docstring"""
stooge(__lowercase , 0 , len(__lowercase ) - 1 )
return arr
def _SCREAMING_SNAKE_CASE ( __lowercase : str , __lowercase : Dict... | 637 | 1 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__a : Any = logging.get_logger("transformers.models.speecht5")
def _SCREAMING_SNAKE_CASE ( __lowercase : List[Any] , _... | 637 |
def _SCREAMING_SNAKE_CASE ( __lowercase : str ) -> str:
"""simple docstring"""
__A = """"""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def _SCREAMING_SNAKE_CASE ... | 637 | 1 |
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,
MaxNewTokens... | 637 |
from __future__ import annotations
from typing import Any
class __lowercase :
'''simple docstring'''
def __init__( self : Dict , UpperCamelCase_ : int , UpperCamelCase_ : int , UpperCamelCase_ : float = 0 ):
... | 637 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils im... | 637 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
__a : Any = logging.get_logger(__name__)
class __lowercase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Union[str, Any] , *Upper... | 637 | 1 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__a : Optional[Any] = get_logger(__name__)
class __lowercase ( enum.Enum ):
'''simple docstring'''
SCREAMING_SNAKE_CASE = "all_ch... | 637 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator... | 637 | 1 |
import numpy as np
def _SCREAMING_SNAKE_CASE ( __lowercase : np.ndarray , __lowercase : np.ndarray , __lowercase : float = 1E-12 , __lowercase : int = 1_0_0 , ) -> tuple[float, np.ndarray]:
"""simple docstring"""
assert np.s... | 637 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__a : Optional[int] = {"configuration_xlnet": ["XLNET_PRETRAINED_CONFIG_ARCHIVE_... | 637 | 1 |
from math import ceil
def _SCREAMING_SNAKE_CASE ( __lowercase : int = 1_0_0_1 ) -> int:
"""simple docstring"""
__A = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
__A = 2 * i + 1
__A = 2 * i
... | 637 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import P... | 637 | 1 |
import torch
from diffusers import StableDiffusionPipeline
__a : str = "path-to-your-trained-model"
__a : Tuple = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")
__a : List[Any] = "A photo of sks dog in a bucket"
__a : Any... | 637 |
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 637 | 1 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils impo... | 637 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmR... | 637 | 1 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
@require_tf
... | 637 |
from __future__ import annotations
from typing import Generic, TypeVar
__a : str = TypeVar("T")
class __lowercase ( Generic[T] ):
'''simple docstring'''
def __init__( self : Any , UpperCamelCase_ : T ):
"""simple docs... | 637 | 1 |
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