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 |
|---|---|---|---|---|
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''google/pix2struct-textcaps-base''': (
'''https://huggingface.co/google/pix... | 60 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"roberta-base":... | 608 | 0 |
import sys
UpperCamelCase = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'66896648950445244523161731856403... | 61 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase__ ( lowercase , lowercase , lowercase , lowercase ):
"""sim... | 62 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
def lowerCamelCase__ ( __lowerCamelCase : list ):
if len(__lowerCamelCase ) < 2:
return collection
def circle_sort_util(__lowerCamelCase : list , __lowerCamelCase : int , __lowerCamelCase : int ) -> bool:
__UpperCAmelCase :... | 63 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
import os
def A__ ( ):
SCREAMING_SNAKE_CASE__: List[str]= os.path.dirname(os.path.realpath(snake_case_ ) )
SCREAMING_SNAKE_CASE__: Optional[int]= os.path.join(snake_case_ , '''triangle.txt''' )
with open(snake_case_ ) as f:
SCREAMING_SNAKE_CASE__: str= f.readlines()
S... | 64 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
"""simple docstring"""
import argparse
import os
# New Code #
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_w... | 65 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
from functools import lru_cache
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> set:
_lowercase : Union[str, Any] = 2
_lowercase : Optional[Any] = set()
while i * i <= n:
if n % i:
i += 1
... | 66 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_c... | 67 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
from __future__ import annotations
__A = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowercase__ ( A_: list[list[int]] , A_: list[int] , A_: list[int] , A_: int , A_: list[list[int]] , ) -> ... | 68 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
'''simple docstring'''
import enum
import shutil
import sys
a , a : List[str] = shutil.get_terminal_size()
a : str = {'''UP''': '''A''', '''DOWN''': '''B''', '''RIGHT''': '''C''', '''LEFT''': '''D'''}
class SCREAMING_SNAKE_CASE__ ( enum.Enum... | 69 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
import heapq as hq
import math
from collections.abc import Iterator
class A:
'''simple docstring'''
def __init__( self : str , A_ : List[Any] ) -> Any:
"""simple docstring"""
lowerCamelCase_ = str(id_ ... | 70 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
'''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# ... | 71 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : Any... | 72 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
imp... | 73 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
from math import factorial
def a__ ( snake_case , snake_case ):
"""simple docstring"""
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError('''Ple... | 74 |
"""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... | 608 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
UpperCamelCase__ = logging.get_logger(__name__)
class lowerCamelCase_ ( __a ):
def __init__( self : Union[str, Any] ,... | 75 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logg... | 76 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
"""simple docstring"""
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase ) -> str:
"""simple docstring"""
__UpperCAmelCase : list[list[str]] = [[] for _ in range(UpperCamelCase )]
__UpperCAmelCase : Union[str, Any] ... | 77 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_ava... | 78 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE__ : Union[str, Any] = {"""UserAgent""": UserAgent().random}
def _lowerCamelCase ( __lowerCamelCase ) -... | 79 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
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... | 80 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __lowerCamelCase ):
if len(__lowerCamelCase ) == 0:
return array
__snake_case , __snake_case : List[Any] = min(__lowerCamelCase ), max(__lowerCamelCase )
# Compu... | 81 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
"""simple docstring"""
from typing import Any
def a__ ( lowerCAmelCase__ ):
if not input_list:
return []
UpperCAmelCase_ = [input_list.count(lowerCAmelCase__ ) for value in input_list]
UpperCAmelCase_ = max(lowerCAmelCase__ ) # Gets t... | 82 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"roberta-base":... | 608 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
lowerCAmelCase__ = TypeVar('''T''')
class __snake_case ( Generic[T]):
def __init__( self : int , __lowerCAmelCase : T ):
... | 83 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
class A_ ( __lowerCamelCase ):
'''simple docstring'''
_UpperCamelCase : List[A... | 84 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ : int ... | 85 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__a :Optional[int] = '.'
if __name__ == "__main__":
__a :str = os.path.join(REPO_PATH, 'utils/documentation_tests.txt')
... | 86 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowerCamelCase : Any = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (5, 1), 6: (3... | 87 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
... | 88 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : int = {
"bert-base-... | 89 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def _snake_case ( A , A ) -> str | Literal[False]:
lowerCAmelCase__ = list(A )
lowerCAmelCase__ = list(A )
... | 90 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 91 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( __magic_name__ : int ) -> str:
lowercase : Tuple =int(__magic_name__ )
if decimal in (0, 1): # Exit cases for the recursion
return str(__magic_name__ )
lowercase , lowercase : Optiona... | 92 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils impo... | 93 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
SCREAMING_SNAKE_CASE = '\\n@inproceedings{snover-etal-2006-study,\n title = "A Study of Translation Edit Rate with Targeted Human Annotation",\n author = "Snover, Matthew ... | 94 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.u... | 95 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
"""simple docstring"""
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__lowerCamelCase = '.'
if __name__ == "__main__":
__lowerCamelCase = os.path.join(REP... | 96 |
"""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... | 608 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_au... | 97 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.ut... | 98 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
def a (lowerCAmelCase__ ):
assert column_title.isupper()
__a = 0
__a = len(lowerCAmelCase__ ) - 1
__a = 0
while index >= 0:
__a = (ord(column_title[index] ) - 64) * pow(26 , lowerCAmelCase__ )
answer += value
power += 1
index -= ... | 99 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
_A : List[Any] = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplification},
authors={Xu, W... | 100 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_nump... | 101 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
UpperCamelCase : int = list(SCREAMING_SNAKE_CASE )
U... | 102 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
"""simple docstring"""
from __future__ import annotations
def snake_case ( lowerCAmelCase_ , lowerCAmelCase_ = None , lowerCAmelCase_ = None , lowerCAmelCase_ = False , ) -> tuple[int, float, str]:
_snake_case = cipher_alphabet or [chr(lowerC... | 103 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : list[int], UpperCAmelCase_ : list[int], UpperCAmelCase_ : int ) -> bool:
"""simple docstring"""
return not any(
neighbour == 1 and colored_vertices[i] == color
... | 104 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"roberta-base":... | 608 | 0 |
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,
... | 105 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase__ : list[int] ) -> bool:
'''simple docstring'''
return len(set(lowerCAmelCase__ ) ) == len(lowerCAmelCase__ )
if __name__ == "__main__":
import doctest
doctest.testmod() | 106 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase : Tuple = logging.get_logger(__name__)
_Uppe... | 107 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__a: Tuple = logging.get_logger(__name__)
__a: Dict = {
'''vocab_file''': '''vocab.json''',
'''merges_file''': ... | 108 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase = 200 ) -> int:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = [1, 2, 5, 10, 20, 50, 100, 200]
__SCREAMING_SNAKE_CASE = [0] * (pence + 1)
__SCREAMING_SNAKE_CASE = 1 # bas... | 109 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
import numpy as np
def _A ( UpperCAmelCase ):
'''simple docstring'''
return np.maximum(0 ,__snake_case )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 531 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: int = len(__snake_case ) // 2
# choose the middle 3 elements
UpperCAmelCase__: int = lst[m - 1 : m + 2]
# if middle element is peak
if three[1] > three[0] and three[1] > three[2]:
return... | 113 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __snake_case :
_lowerCAmelCase = 42
_lowerCAmelCase = 42
clas... | 320 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ ... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
import re
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> Tuple:
snake_case__ = re.compile(
r'''^(?:0|94|\+94|0{2}94)''' r'''7(0|1|2|4|5|6|7|8)''' r'''(-| |)''' r'''\d{7}$''' )
return bool(re.search(__snake_case , __snake_case ) )
if __name__ ==... | 33 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUG... | 684 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( a , a ):
assert x is not None
assert y is not None
__snake_case = len(__snake_case )
__snake_case = len(__snake_case )
# declaring the array for storing the dp values
__snake_case ... | 356 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
... | 484 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ : List[str] = logging.get_logger(__name__)
__magic_name__ : str = {
... | 672 |
"""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... | 608 | 0 |
"""simple docstring"""
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_... | 642 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 0 |
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch
lowerCamelCase__ ... | 122 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowerCAmelCase_ = logging.get_logger(__name__)
class _snake_case( A__ ):
def __init__(self : List[str] , *a : Any , **a : str... | 531 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : int ={
"""configuration_roformer""": ["""ROFORMER_PRETRAINED_CONFIG_ARCHIVE_... | 113 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
'''simple docstring'''
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
A = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 320 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
def snake_case (UpperCAmelCase__ ) -> int:
if n_term == "":
return []
UpperCamelCase_: list = []
for temp in range(int(__snake_case ) ):
series.append(F'''1/{temp + 1}''' if series else '1' )
return series
if __name__ == "__main... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> List[Any]:
snake_case... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
def __lowerCamelCase ( _lowerCAmelCase = 1_000 ) -> Optional[Any]:
_UpperCAmelCase = 3
_UpperCAmelCase = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __name__ == "_... | 684 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"roberta-base":... | 608 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class a_ :
def __init__( self : Dict , __lowerCAmelCase : int , __lowerCAmelCase : MutableSequence[float] ):
if len(__lowerCAmelCase ) != degree... | 356 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
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,
get_constant_schedule,
... | 484 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
'''simple docstring'''
def snake_case_ ( SCREAMING_SNAKE_CASE__ = 10_00 ):
'''simple docstring'''
_snake_case = 1, 1
_snake_case = []
for i in range(1 , n + 1 ):
_snake_case = prev_numerator + 2 * prev_denominator
_snake_case = ... | 672 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMix... | 642 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __magic_name__ (A__ ):
def __init__( self , _a , _a ) -> List[Any]:
lowerCAmelCase_ = params
lowerCAmelCase_ = np.array(_a )
... | 122 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def _A ( UpperCAmelCase ):
'''simple docstring'''
return x + 2
class _snake_case( unittest.TestCase ... | 531 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Tuple = OmegaConf.load(__snake_case )
UpperCAmelCase__: Tuple = ... | 113 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def UpperCAmelCase ( UpperCAmelCase__ : Union[str, Any]):
lowerCamelCase : str = FileLock(str(tmpdir / 'foo.lock'))
lowerCamelCase ... | 320 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=A__ )
class _lowerCAmelCase( A__ ):
"""simple docstring"""
... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
import os
import pytest
from attr import dataclass
lowerCamelCase__ : int = """us-east-1""" # defaults region
@dataclass
class __magic_name__ :
'''simple docstring'''
__lowercase : List[Any] = 42
__lowercase : ... | 33 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def __lowerCamelC... | 684 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
'''simple docstring'''
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when s... | 356 |
"""simple docstring"""
def a ( __snake_case : int, __snake_case : list ):
'''simple docstring'''
_enforce_args(__snake_case, __snake_case )
if n == 0:
return 0
UpperCAmelCase_ :Optional[int] = float('''-inf''' )
for i in range(1, ... | 608 | 0 |
from __future__ import annotations
__A = list[tuple[int, int]]
__A = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, ... | 484 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _snake_case ( A__ ):
'''simple docstring'''
def __init__( self : Optional[Any] , sna... | 608 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAva... | 672 |
"""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... | 608 | 0 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCAmelCase ( A__ ):
... | 642 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( A__ ):
'''simple docstring'''
UpperCamelCase__ =(CMStochasticIterativeScheduler,)
UpperCamelCase__ =10
... | 608 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __magic_name__ :
lowerCamelCase__ = 42
lowerCamelCase__ = None
lowerCamelCase__ =... | 122 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def a ( __snake_case : float, __snake_case : float ):
'''simple docstring'''
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''' )
elif capacitance... | 608 | 0 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case( A__ ):
__snake_case: int = (CMStochasticIterativeScheduler,)
__snake_case: str = 10
def _UpperC... | 531 |
"""simple docstring"""
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def a ( __snake_case : int = 3 ):
'''simple docstring'''
if isinstance(__snake_case, __snake_case ):
raise TypeErro... | 608 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_ut... | 113 |
"""simple docstring"""
import os
import sys
import unittest
__lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_d... | 608 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCro... | 320 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def snake_case (UpperCAmelCase__ ) -> Tuple:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, a... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfo... | 608 | 0 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __magic_name__ (A__ ,A__ ):
... | 33 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}
try:
if not is_vision_available():... | 608 | 0 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokeniza... | 684 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"roberta-base":... | 608 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 356 |
"""simple docstring"""
__lowerCamelCase = {
"A": ["B", "C", "E"],
"B": ["A", "D", "E"],
"C": ["A", "F", "G"],
"D": ["B"],
"E": ["A", "B", "D"],
"F": ["C"],
"G": ["C"],
}
def a ( __snake_case : dict, __snake_case : str, __snake_case : Unio... | 608 | 0 |
def __A ( _lowercase , _lowercase ):
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(__snake_case , x % y )
def __A ( _lowercase , _lowercase ):
'''simple docstring'''
return (x * y) // greates... | 484 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state ... | 608 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia a... | 672 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class _snake_case :
'''simple docstring'''
def __init__( self : Dict , snake_case : int , snake_case : MutableSequence[float] ):
if len(snake_case ) !=... | 608 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 642 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def a ( __snake_case : Callable, __snake_case : float, __snake_case : float, __snake_case : float, __snake_case : float ):
'''simple docstring'''
UpperCAmelCase_ ... | 608 | 0 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def A(__a: int = 3 ):
if isinstance(__snake_case , __snake_case ):
raise TypeError("number of qubits must be a integer." )
if number_of_qubits <= ... | 122 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class _snake_case ( A__ , A__... | 608 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.json''',
# See ... | 531 |
"""simple docstring"""
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def a ( __snake_case : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase_ :str = FileLock(str(tmpdir / '''foo.lock''' ) )
UpperCAmelCase_ ... | 608 | 0 |
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Union[str, Any] = [1]
UpperCAmelCase__: str = 0, 0, 0
UpperCAmelCase__: Optional[int] = ugly_nums[ia] * 2
UpperCAmelCase__: Union[str, Any] = ugly_nums[ia] * 3
UpperCAmelCase__: Optional[int] = ugly_nums[ia] ... | 113 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__lowerCamelCase = [
# tf -> hf
("/", "."),
("layer_", "layers."),
("kerne... | 608 | 0 |
'''simple docstring'''
import os
import re
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 logging
A = logging.get_logger(__name__)
... | 320 |
"""simple docstring"""
import socket
def a ( ):
'''simple docstring'''
UpperCAmelCase_ :Union[str, Any] = socket.socket(socket.AF_INET, socket.SOCK_STREAM )
UpperCAmelCase_ :int = socket.gethostname()
UpperCAmelCase_ :List[Any] ... | 608 | 0 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def snake_case (UpperCAmelCase__ ) -> int:
UpperCamelCase_: str = {}
UpperCamelCase_: Union[str, Any] = job['''started_at''']
UpperCamelCase... | 57 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, Be... | 608 | 0 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def SCREAMING... | 33 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 608 | 0 |
import os
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_doctest_list.py
__lowerCAmelCase = "."
if __name__ == "__main__":
__lowerCAmelCase = os.path.join(REPO_PATH, "utils/documentation_test... | 684 |
"""simple docstring"""
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
"kakaobrai... | 608 | 0 |
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