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 numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __lowercase ( a__ ):
'''simple docstring'''
def __init__( self , _UpperCAmelCase , ... | 52 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.nu... | 633 | 0 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common im... | 296 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
a : int = numpy.array([0, 0])
a : Optional[Any] = numpy.array([0.5, 0.866_0254])
a : Tuple =... | 633 | 0 |
'''simple docstring'''
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.d... | 474 |
"""simple docstring"""
from __future__ import annotations
from statistics import mean
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] , _lowercase : list[int] , _lowercase : int ) ->list[int]:
'''simple docstring... | 633 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a = {
'''configuration_timesformer''': ['''TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TimesformerConfig'''],
}
try:
if not is_torch_available():
... | 169 |
"""simple docstring"""
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_... | 633 | 0 |
"""simple docstring"""
class lowerCamelCase__ : # Public class to implement a graph
def __init__( self : int , _lowercase : Tuple , _lowercase : Optional[Any] , _lowercase : Union[str, Any] ):
A = row
A ... | 690 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE ( _lowercase : list , _lowercase : int = 0 , _lowercase : int = 0 ) ->list:
'''simple docstring'''
a : Optional[Any] = end or l... | 633 | 0 |
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCAmelCase_ ... | 105 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a : Optional[Any] ... | 633 | 0 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAm... | 258 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : List[Any] = {
'''microsoft/unispeech-sat-base-100h-libri-ft''': (... | 633 | 0 |
def a__ ( A__, A__, A__ ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(_lowercase ) )
def a__ ( A__, A__, A__, A__ ):
if index == len(_lowercase ):
... | 101 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class __UpperCamelCase :
def __init__( self ) -> Any:
a : str = psutil.Process()
a : str = False
... | 633 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class a_ ( unittest.TestCase ):
lowerCamelCase__ : Dict ... | 263 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transforme... | 633 | 0 |
from pathlib import Path
import numpy as np
from PIL import Image
def lowerCAmelCase_ ( __A ) -> np.ndarray:
'''simple docstring'''
UpperCAmelCase__ = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2989 * r + 0.5870 * g + 0.1140 * b
... | 486 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 633 | 0 |
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import jit
from tra... | 611 |
"""simple docstring"""
import gc
import unittest
from transformers import CTRLConfig, 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... | 633 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def __A ( a_ :float , a_ :float) -> tuple:
if inductance <= 0:
raise ValueError('''Inductance cannot be 0 or negative''')
elif capacitance <= 0:
... | 52 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
a : List[Any] = '''\
'''
a : Optional[int] = '''
Perpl... | 633 | 0 |
'''simple docstring'''
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check... | 296 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_a... | 633 | 0 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Co... | 474 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTest... | 633 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available... | 169 |
"""simple docstring"""
class __UpperCamelCase : # Public class to implement a graph
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> None:
a : int = row
a : Tuple = col
... | 633 | 0 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def __snake_case ( UpperCamelCase__ , UpperCamelCase__ = 0.0 , UpperCamelCase__ = 1.0 ) -> int:
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )... | 690 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple ) ->Optional[Any]:
'''simple docstring'''
a : Any = []
a : List[str] = set({"(", "[", "{"} )
a : int = set({")", "]", "}"} ... | 633 | 0 |
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmbeddings,
BertLay... | 105 |
"""simple docstring"""
import unittest
from transformers import DonutProcessor
a : Optional[int] = '''naver-clova-ix/donut-base'''
class __UpperCamelCase ( unittest.TestCase ):
def __a ( self ) -> Dict:
a : O... | 633 | 0 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_... | 258 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
a : Optional[int] ... | 633 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __lowercase (a__ ):
"""simpl... | 101 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 633 | 0 |
'''simple docstring'''
from __future__ import annotations
from statistics import mean
def UpperCamelCase_ ( A__ , A__ , A__ ):
a_ = [0] * no_of_processes
a_ = [0] * no_of_processes
# Initialize remaining_time to waiting_time.
for i in range(_lowerc... | 263 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_u... | 633 | 0 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_... | 486 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] ) ->float:
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
a : Dict = sum(_lowercase... | 633 | 0 |
from math import factorial
def _UpperCAmelCase ( UpperCamelCase: int = 1_0_0 ):
"""simple docstring"""
return sum(int(_lowercase ) for x in str(factorial(_lowercase ) ) )
if __name__ == "__main__":
print(solution(int(input("Enter the Number: ").strip())))
| 611 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple , _lowercase : float = 0.0 , _lowercase : float = 1.0 ) ->int:
'''simple docstring'''
return 1 / sqrt(... | 633 | 0 |
"""simple docstring"""
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
... | 52 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.nu... | 633 | 0 |
'''simple docstring'''
from torch import nn
class __SCREAMING_SNAKE_CASE ( nn.Module ):
def __init__( self : Any , __lowercase : str , __lowercase : Dict ) -> Dict:
super().__init__()
SCREAMING_SNAKE_C... | 296 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
a : int = numpy.array([0, 0])
a : Optional[Any] = numpy.array([0.5, 0.866_0254])
a : Tuple =... | 633 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {}
class _UpperCamelCase ( a__ ):
'''simple docstring'''
lowerCAmelCase__ = ... | 474 |
"""simple docstring"""
from __future__ import annotations
from statistics import mean
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] , _lowercase : list[int] , _lowercase : int ) ->list[int]:
'''simple docstring... | 633 | 0 |
"""simple docstring"""
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 ... | 169 |
"""simple docstring"""
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_... | 633 | 0 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ... | 690 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE ( _lowercase : list , _lowercase : int = 0 , _lowercase : int = 0 ) ->list:
'''simple docstring'''
a : Optional[Any] = end or l... | 633 | 0 |
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, BertTokenizer, BlipImagePr... | 105 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a : Optional[Any] ... | 633 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __a , __a = None , __a = None ) -> None:
"""simple docstring"""
if start is None:
SCREAMING_SNAKE_CASE : Tuple =0
if end is None:... | 258 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : List[Any] = {
'''microsoft/unispeech-sat-base-100h-libri-ft''': (... | 633 | 0 |
import re
import subprocess
import sys
lowerCAmelCase__ : List[Any] =subprocess.check_output('git merge-base main HEAD'.split()).decode('utf-8')
lowerCAmelCase__ : List[str] =(
subprocess.check_output(F"""git diff --diff-filter=d --name-only {fork_point_sha}""".split()).de... | 101 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class __UpperCamelCase :
def __init__( self ) -> Any:
a : str = psutil.Process()
a : str = False
... | 633 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( A__ , A__ ):
return int(input_a == input_a == 0 )
def UpperCamelCase_ ( ):
print("""Truth Table of NOR Gate:""" )
print("""| Input 1 | Input 2 | Output |""" )
print(F'''| 0 | 0 | {nor_gat... | 263 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transforme... | 633 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCamelCase__ = {'''tokenization_bertweet''': ['''BertweetTokenizer''']}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
UpperCamelCase__ = _LazyMod... | 486 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 633 | 0 |
def _UpperCAmelCase ( UpperCamelCase: int = 1_0_0_0 ):
"""simple docstring"""
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 611 |
"""simple docstring"""
import gc
import unittest
from transformers import CTRLConfig, 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... | 633 | 0 |
"""simple docstring"""
def __A ( a_ :Tuple) -> Optional[Any]:
__a : Any = []
__a : List[str] = set({'''(''', '''[''', '''{'''})
__a : int = set({''')''', ''']''', '''}'''})
__a : int = {"{":... | 52 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
a : List[Any] = '''\
'''
a : Optional[int] = '''
Perpl... | 633 | 0 |
'''simple docstring'''
def _a( UpperCamelCase__ : int = 1_0_0_0_0_0_0 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Any =limit + 1
SCREAMING_SNAKE_CASE__ : Optional[Any] =[0] * limit
for first_term in range(1, _low... | 296 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_a... | 633 | 0 |
'''simple docstring'''
from graphs.minimum_spanning_tree_kruskal import kruskal
def _A ( ):
"""simple docstring"""
__lowercase =9
__lowercase =[
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1... | 474 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTest... | 633 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi
def lowercase (snake_case__ : float , snake_case__ : float , snake_case__ : float ) -> dict[str, float]:
'''simple docstring'''
if (inductance, frequency, reactance).count(0... | 169 |
"""simple docstring"""
class __UpperCamelCase : # Public class to implement a graph
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> None:
a : int = row
a : Tuple = col
... | 633 | 0 |
"""simple docstring"""
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 690 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple ) ->Optional[Any]:
'''simple docstring'''
a : Any = []
a : List[str] = set({"(", "[", "{"} )
a : int = set({")", "]", "}"} ... | 633 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase__ : Optional[Any] = {
'''configuration_owlvit''... | 105 |
"""simple docstring"""
import unittest
from transformers import DonutProcessor
a : Optional[int] = '''naver-clova-ix/donut-base'''
class __UpperCamelCase ( unittest.TestCase ):
def __a ( self ) -> Dict:
a : O... | 633 | 0 |
def lowerCAmelCase_ ( __a , __a , __a ) -> float:
"""simple docstring"""
return round(float(moles / volume ) * nfactor )
def lowerCAmelCase_ ( __a , __a , __a ) -> float:
... | 258 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
a : Optional[int] ... | 633 | 0 |
import collections
import os
import re
from pathlib import Path
lowerCAmelCase__ : List[str] ='''src/transformers'''
# Matches is_xxx_available()
lowerCAmelCase__ : str =re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase_... | 101 |
"""simple docstring"""
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 633 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ ={
'''configuration_xmod''': [
'''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XmodConfig''',
'''XmodOnnxConfig''',
],
}
tr... | 263 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_u... | 633 | 0 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, Par... | 486 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] ) ->float:
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
a : Dict = sum(_lowercase... | 633 | 0 |
def _UpperCAmelCase ( UpperCamelCase: int , UpperCamelCase: bool = False ):
"""simple docstring"""
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 1_0 not in (1, 3, 7, 9): # can quickly check last digit
return False
if n > 3_3_1_7_0_4_4_0_6_4_6_7_9_8_8_7... | 611 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple , _lowercase : float = 0.0 , _lowercase : float = 1.0 ) ->int:
'''simple docstring'''
return 1 / sqrt(... | 633 | 0 |
"""simple docstring"""
import os
def __A ( a_ :str = "input.txt") -> int:
with open(os.path.join(os.path.dirname(_lowercase) , _lowercase)) as input_file:
__a : Any = [
[int(_lowercase) for element in line.split('... | 52 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.nu... | 633 | 0 |
'''simple docstring'''
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
a_ = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( a__ ... | 296 |
"""simple docstring"""
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
a : int = numpy.array([0, 0])
a : Optional[Any] = numpy.array([0.5, 0.866_0254])
a : Tuple =... | 633 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _UpperCamelCase ( a__ ):
'''simple d... | 474 |
"""simple docstring"""
from __future__ import annotations
from statistics import mean
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] , _lowercase : list[int] , _lowercase : int ) ->list[int]:
'''simple docstring... | 633 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
a = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXJapaneseConfig'''],
... | 169 |
"""simple docstring"""
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_... | 633 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase : int = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''... | 690 |
"""simple docstring"""
import math
def _SCREAMING_SNAKE_CASE ( _lowercase : list , _lowercase : int = 0 , _lowercase : int = 0 ) ->list:
'''simple docstring'''
a : Optional[Any] = end or l... | 633 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCamelCase__ : Tuple = logging.get_logger(__name__)
Up... | 105 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a : Optional[Any] ... | 633 | 0 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentPars... | 258 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a : List[Any] = logging.get_logger(__name__)
a : List[Any] = {
'''microsoft/unispeech-sat-base-100h-libri-ft''': (... | 633 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ : Optional[Any] =logging.get_logger(__name__)
lowerCAmelCase__ : Optional[int] ={
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook... | 101 |
"""simple docstring"""
import gc
import threading
import time
import psutil
import torch
class __UpperCamelCase :
def __init__( self ) -> Any:
a : str = psutil.Process()
a : str = False
... | 633 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( A__ ):
if not nums: # Makes sure that the list is not empty
raise ValueError("""List is empty""" )
a_ = sum(_lowercase ) / len(_lowercase ) # Calculate the average
return sum(abs(x - average ) for x in nums ... | 263 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transforme... | 633 | 0 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_... | 486 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependency... | 633 | 0 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class a ( tf.keras.optimizers.schedules.LearningRateSchedule ):
def __init... | 611 |
"""simple docstring"""
import gc
import unittest
from transformers import CTRLConfig, 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... | 633 | 0 |
"""simple docstring"""
from __future__ import annotations
import bisect
def __A ( a_ :list[int] , a_ :int , a_ :int = 0 , a_ :int = -1) -> int:
if hi < 0:
__a : Optional[int] = len(_lowercase)
wh... | 52 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
a : List[Any] = '''\
'''
a : Optional[int] = '''
Perpl... | 633 | 0 |
'''simple docstring'''
import os
def _a( ):
'''simple docstring'''
with open(os.path.dirname(_lowercase ) + '''/p022_names.txt''' ) as file:
SCREAMING_SNAKE_CASE__ : Dict =str(file.readlines()[0] )
SCREAMING_SNAK... | 296 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_a... | 633 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils imp... | 474 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTest... | 633 | 0 |
"""simple docstring"""
def lowercase (snake_case__ : float ) -> float:
'''simple docstring'''
return 10 - x * x
def lowercase (snake_case__ : float , snake_case__ : float ) -> float:
'''simple docstring'''
if equation(_lowercase ... | 169 |
"""simple docstring"""
class __UpperCamelCase : # Public class to implement a graph
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> None:
a : int = row
a : Tuple = col
... | 633 | 0 |
"""simple docstring"""
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def __snake_case ( UpperCamelCase__ ) -> Dict:
"""simple docstring"""
def wrapper(*UpperCamelCase__ , ... | 690 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple ) ->Optional[Any]:
'''simple docstring'''
a : Any = []
a : List[str] = set({"(", "[", "{"} )
a : int = set({")", "]", "}"} ... | 633 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
lowercase : Optional[int] = logging.get_logger(__name__)
class A ( __snake_case ):
def __... | 634 |
'''simple docstring'''
import numpy
# List of input, output pairs
lowercase : Any = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase : str = (((5_15, 22, 13), 5_55), ((61,... | 634 | 1 |
'''simple docstring'''
import argparse
import json
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_warm... | 634 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTe... | 634 | 1 |
'''simple docstring'''
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
A : str = args.pruning_m... | 634 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesCon... | 634 | 1 |
'''simple docstring'''
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
lowercase : ... | 634 |
'''simple docstring'''
lowercase : dict[str, float] = {
"joule": 1.0,
"kilojoule": 10_00,
"megajoule": 1_00_00_00,
"gigajoule": 10_00_00_00_00,
"wattsecond": 1.0,
"watthour": 36_00,
"kilowatthour": 3_60_00_00,
"newtonmeter": 1.0,
"calorie... | 634 | 1 |
'''simple docstring'''
import math
from collections.abc import Callable
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
A : float = xa
A : float = xa
while True:
... | 634 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Optional[int] = {
'google/switch-base-8': 'https://huggingface.co/google/s... | 634 | 1 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class A ( __snake_case ):
def __lowerCAmelCase ( self ) -> Tuple:
"""simple docs... | 634 |
'''simple docstring'''
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TF... | 634 | 1 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module,... | 634 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
... | 634 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if length <= 0 or not isinstance(snake_case__ , snake_case__ ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in ran... | 634 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is... | 634 | 1 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowercase : List[Any] = Mapping[str, np.ndarray]
lowercase : ... | 634 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if len(snake_case__ ) <= 1:
return [tuple(snake_case__ )]
A : int = []
def generate(snake_case__ , snake_case__ ):
if k == 1:
... | 634 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if not isinstance(snake_case__ , snake_case__ ):
A : List[Any] = F'Input value of [number={number}] must be an integer'
raise TypeError(snake_case__ )... | 634 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__=None , **snake_case__ ):
'''simple docstring'''
A : Optional[Any] = [... | 634 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils impor... | 634 |
'''simple docstring'''
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
lowercase : int = logging.get_logger(__name__... | 634 | 1 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_avai... | 634 |
'''simple docstring'''
import math
from collections.abc import Callable
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
A : float = xa
A : float = xa
while True:
... | 634 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase : Union[str, Any] = {'configuration_plba... | 634 |
'''simple docstring'''
from random import randint, random
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = False , snake_case__ = False , snake_case__ = 5 , ):
'''simple... | 634 | 1 |
'''simple docstring'''
from random import randint, random
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = False , snake_case__ = False , snake_case__ = 5 , ):
'''simple... | 634 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_commo... | 634 | 1 |
'''simple docstring'''
import random
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
A : Union[str, Any] = num - 1
A : Union[str, Any] = 0
while s % 2 == 0:
A : Optional[int] = s // 2
t += 1
... | 634 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Tuple = {
'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
'tokenization_luke': ['Luk... | 634 | 1 |
'''simple docstring'''
import math
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
A : Any = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(snake_case__ )
def lowerCAmel... | 634 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Any = logging.get_logger(__name__)
lowercase : int = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/res... | 634 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case__ , snake_case__ = None , snake_case__ = None , snake_case__ = False , ):
'''simple docstring'''
A : Dict = cipher_a... | 634 |
'''simple docstring'''
# 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... | 634 | 1 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class A :
def __init__( self , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ,... | 634 |
'''simple docstring'''
import random
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
A : Optional[Any] = a[left_index]
A : List[str] = left_index + 1
for j in range(left... | 634 | 1 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import... | 634 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_commo... | 634 | 1 |
'''simple docstring'''
import math
class A :
def __init__( self , SCREAMING_SNAKE_CASE=0 ) -> Union[str, Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
A : Any = n
A : Tu... | 634 |
'''simple docstring'''
import random
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
A, A, A : Any = [], [], []
for element in data:
if element < pivot:
less.append(snake_case__ ... | 634 | 1 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPip... | 634 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceb... | 634 | 1 |
'''simple docstring'''
import random
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
A, A, A : Any = [], [], []
for element in data:
if element < pivot:
less.append(snake_case__ ... | 634 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Optional[Any] = logging.get_logger(__name__)
lowercase : int = {
'ut/deta': '... | 634 | 1 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowercase : List[str] = datasets.logging.get_logger(__name__)
lowercase : ... | 634 |
'''simple docstring'''
import numpy
# List of input, output pairs
lowercase : Any = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase : str = (((5_15, 22, 13), 5_55), ((61,... | 634 | 1 |
'''simple docstring'''
from __future__ import annotations
from scipy.special import comb # type: ignore
class A :
def __init__( self , SCREAMING_SNAKE_CASE ) -> Any:
"""simple docstring"""
A : Opti... | 634 |
'''simple docstring'''
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTe... | 634 | 1 |
'''simple docstring'''
lowercase : Tuple = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if not isinstance(snake_case__ , snake_case__ )... | 634 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesCon... | 634 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def lowerCAmelCase_ ( snake_case__ ):
'''sim... | 634 |
'''simple docstring'''
lowercase : dict[str, float] = {
"joule": 1.0,
"kilojoule": 10_00,
"megajoule": 1_00_00_00,
"gigajoule": 10_00_00_00_00,
"wattsecond": 1.0,
"watthour": 36_00,
"kilowatthour": 3_60_00_00,
"newtonmeter": 1.0,
"calorie... | 634 | 1 |
'''simple docstring'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderMod... | 634 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Optional[int] = {
'google/switch-base-8': 'https://huggingface.co/google/s... | 634 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : Optional[int] = {'configuration_encoder_decoder': ['Enc... | 634 |
'''simple docstring'''
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TF... | 634 | 1 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class A ( __snake_case ):
__magic_name__ = (EulerDiscreteScheduler,)
__magic_na... | 634 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
... | 634 | 1 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def lowerCAmelCase_ ( snake_case__ = "laptop" ):
'''simple docstring'''
A : Optional[Any] = F'https://www.amazon.... | 634 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is... | 634 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
if len(snake_case__ ) != len(snake_case__ ):
raise ValueError('''String lengths must match!''' )
A : int = 0
for chara, chara in ... | 634 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ ):
'''simple docstring'''
if len(snake_case__ ) <= 1:
return [tuple(snake_case__ )]
A : int = []
def generate(snake_case__ , snake_case__ ):
if k == 1:
... | 634 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
lowercase : Any = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase : str = (((5_15, 22, 13), 5_55), ((61,... | 634 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__=None , **snake_case__ ):
'''simple docstring'''
A : Optional[Any] = [... | 634 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Tuple = {
'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}
try:
if no... | 634 |
'''simple docstring'''
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
lowercase : int = logging.get_logger(__name__... | 634 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A ( __snake_case ):
@staticmethod
@abstractmethod
def __lowerCAmelCase ( SCREAMING_SNAKE_CASE ) -> int:
... | 634 |
'''simple docstring'''
import math
from collections.abc import Callable
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
A : float = xa
A : float = xa
while True:
... | 634 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils ... | 634 |
'''simple docstring'''
from random import randint, random
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = False , snake_case__ = False , snake_case__ = 5 , ):
'''simple... | 634 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase : Union[str, Any] = {
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
... | 634 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_commo... | 634 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import YolosConfig
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_commo... | 634 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Tuple = {
'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
'tokenization_luke': ['Luk... | 634 | 1 |
'''simple docstring'''
import math
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(snake_case__... | 634 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Any = logging.get_logger(__name__)
lowercase : int = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/res... | 634 | 1 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
lowercase : Union[str, Any] = logging.get_logger(__name__) #... | 634 |
'''simple docstring'''
# 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... | 634 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_commo... | 634 |
'''simple docstring'''
import random
def lowerCAmelCase_ ( snake_case__ , snake_case__ , snake_case__ ):
'''simple docstring'''
A : Optional[Any] = a[left_index]
A : List[str] = left_index + 1
for j in range(left... | 634 | 1 |
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