code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import numpy
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Optional[Any] , _snake_case : List[str] , _snake_case : Tuple ):
"""simple docstring"""
A__ = input_array
# Rando... | 713 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = args.log_outputs
A__ =... | 52 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
rene... | 714 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 52 | 0 |
def A ( __UpperCamelCase = 200 ) -> int:
A__ = [1, 2, 5, 10, 20, 50, 100, 200]
A__ = [0] * (pence + 1)
A__ = 1 # base case: 1 way to make 0 pence
for coin in coins:
for i in range(_UpperCamelCase , pence + 1 , 1 ):
number_of_ways[i... | 715 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''... | 52 | 0 |
from __future__ import annotations
def A ( __UpperCamelCase ) -> Optional[int]:
if not nums:
return 0
A__ = nums[0]
A__ = 0
for num in nums[1:]:
A__ , A__ = (
max_excluding + num,
max(__UpperCamelCas... | 716 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert im... | 52 | 0 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-research/efficientfor... | 717 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
SCREAMING_SNAKE_CASE__ = '''sshleifer/bart-tiny-random'''
... | 52 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'CLIPSegVisionC... | 718 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple... | 52 | 0 |
'''simple docstring'''
from PIL import Image
def A ( __UpperCamelCase , __UpperCamelCase ) -> int:
def brightness(__UpperCamelCase ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
raise ValueError('level must be between -255.0 (... | 719 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'''configuration_xlm_roberta'''... | 52 | 0 |
from __future__ import annotations
from PIL import Image
# Define glider example
SCREAMING_SNAKE_CASE__ = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0... | 720 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 52 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.t... | 721 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 52 | 0 |
# 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.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet imp... | 700 |
def A ( __UpperCamelCase ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 52 | 0 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __lowerCAmelCase ( ctypes.Structure ):
"""simple docstring"""
A__ : Dict = [("size", ctypes.c_... | 701 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : Any , _snake_case : str=None , _snake_case : Dict=None , _snake_case... | 52 | 0 |
import torch
from transformers import AutoModel
class __lowerCAmelCase ( torch.nn.Module ):
def __init__( self : Optional[Any] , _snake_case : int="sayef/fsner-bert-base-uncased" ):
"""simple docstring"""
super(_snake_case , ... | 702 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
Da... | 52 | 0 |
import pytest
import datasets
# Import fixture modules as plugins
SCREAMING_SNAKE_CASE__ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def A ( __UpperCamelCase , __UpperCamelCase ) -> Optional[int]:
# Mark tests as "un... | 703 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 52 | 0 |
def A ( __UpperCamelCase ) -> int:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise TypeError('only integers accepted as input' )
else:
A__ = str(abs(__UpperCamelCase ) )
A__ = [list(__UpperCamelCase ) for char in ... | 704 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))
... | 52 | 0 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
A__ : int = (DDPMScheduler,)
def _a ( self : Optional[Any] , ... | 705 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INP... | 52 | 0 |
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = '''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_... | 706 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
SCREAMING_SNAKE_CASE__ = r'''
Args:
input_ids (`jnp.ndarray` of shape `(batch_... | 52 | 0 |
def A ( __UpperCamelCase , __UpperCamelCase ) -> tuple[float, float]:
# Check if the input is valid
if not len(__UpperCamelCase ) == len(__UpperCamelCase ) == 3:
raise ValueError('Please enter a valid equation.' )
if equationa[0] == equationa[1] == equationa[0] =... | 707 |
import argparse
import struct
import unittest
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[str] , _snake_case : bytes ):
"""simple docstring"""
A__ = data
# Initialize hash values
... | 52 | 0 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 708 |
import math
import random
def A ( __UpperCamelCase , __UpperCamelCase = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
SCREAMING_SNAKE_CASE__ = 0.02
def A ( __UpperCamelCase , __UpperCamel... | 52 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def A ( __UpperCamelCase ) -> Optional[int]:
# A local function to see if a dot lands in the circle.
def is_in_circle(__UpperCamelCase , __UpperCamelCase ) -> b... | 709 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 52 | 0 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE__ = logging.getLogger(__name__)
@dataclass
class __lowerCAmelCase ( UpperCAmelCase_ ):
... | 710 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-base''': '''https:/... | 52 | 0 |
from typing import List
from .keymap import KEYMAP, get_character
def A ( __UpperCamelCase ) -> Any:
def decorator(__UpperCamelCase ):
A__ = getattr(__UpperCamelCase , 'handle_key' , [] )
handle += [key]
setattr(__UpperCamelCase , 'handle_key' , __U... | 711 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_co... | 52 | 0 |
'''simple docstring'''
from __future__ import annotations
def A ( __UpperCamelCase ) -> bool:
A__ = str(__UpperCamelCase )
return n == n[::-1]
def A ( __UpperCamelCase = 1_000_000 ) -> Dict:
A__ = 0
for i in range(1 , __Up... | 712 |
import pytest
import datasets
# Import fixture modules as plugins
SCREAMING_SNAKE_CASE__ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def A ( __UpperCamelCase , __UpperCamelCase ) -> Optional[int]:
# Mark tests as "unit" by default... | 52 | 0 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docst... | 713 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = args.log_outputs
A__ =... | 52 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def A ( __UpperCamelCase ) -> bool:
A__ = int(number**0.5 )
return number == sq * sq
def A ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCa... | 714 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 52 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def A ( __UpperCamelCase , __UpperCamelCase ) -> np.array:
A__ = f'''{sampling_rate}'''
A__ = '1'
A__ = 'f32le'
A__ = [
'f... | 715 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''... | 52 | 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__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-base... | 716 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert im... | 52 | 0 |
from __future__ import annotations
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , _snake_case : str , _snake_case : str ):
"""simple docstring"""
A__ , A__ = text, pattern
... | 717 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
SCREAMING_SNAKE_CASE__ = '''sshleifer/bart-tiny-random'''
... | 52 | 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
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
... | 718 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple... | 52 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Ba... | 719 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'''configuration_xlm_roberta'''... | 52 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 720 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 52 | 0 |
import math
def A ( __UpperCamelCase ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes nu... | 721 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 52 | 0 |
from math import factorial
SCREAMING_SNAKE_CASE__ = {str(digit): factorial(digit) for digit in range(1_0)}
def A ( __UpperCamelCase ) -> int:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise TypeError('Parameter number must be int' )
if numbe... | 700 |
def A ( __UpperCamelCase ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 52 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {'''configuration_reformer''': ['''REFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''... | 701 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : Any , _snake_case : str=None , _snake_case : Dict=None , _snake_case... | 52 | 0 |
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
req... | 702 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
Da... | 52 | 0 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
A__ : Union[str, Any] = (UnCLIPScheduler,)
def _a ( s... | 703 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 52 | 0 |
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 as sp
from digital_image_proc... | 704 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))
... | 52 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __lowerCAmelCase ( nn.Module ):
"""simple docstring"""
def __init__( self : Optional[int] , _snake_case : int = 16 , ... | 705 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INP... | 52 | 0 |
'''simple docstring'''
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(... | 706 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
SCREAMING_SNAKE_CASE__ = r'''
Args:
input_ids (`jnp.ndarray` of shape `(batch_... | 52 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ = {
'''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '... | 707 |
import argparse
import struct
import unittest
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[str] , _snake_case : bytes ):
"""simple docstring"""
A__ = data
# Initialize hash values
... | 52 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['... | 708 |
import math
import random
def A ( __UpperCamelCase , __UpperCamelCase = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
SCREAMING_SNAKE_CASE__ = 0.02
def A ( __UpperCamelCase , __UpperCamel... | 52 | 0 |
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_comm... | 709 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 52 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig''',
... | 710 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-base''': '''https:/... | 52 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {}
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
A__ : Optional[Any] ... | 711 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_co... | 52 | 0 |
'''simple docstring'''
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = arg... | 712 |
import pytest
import datasets
# Import fixture modules as plugins
SCREAMING_SNAKE_CASE__ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def A ( __UpperCamelCase , __UpperCamelCase ) -> Optional[int]:
# Mark tests as "unit" by default... | 52 | 0 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if... | 713 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = args.log_outputs
A__ =... | 52 | 0 |
from collections import defaultdict
def A ( __UpperCamelCase , __UpperCamelCase ) -> bool:
A__ = first_str.lower().strip()
A__ = second_str.lower().strip()
# Remove whitespace
A__ = first_str.replace(' ' , '' )
A__ = second_str.replac... | 714 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 52 | 0 |
from pathlib import Path
import fire
from tqdm import tqdm
def A ( __UpperCamelCase="ro" , __UpperCamelCase="en" , __UpperCamelCase="wmt16" , __UpperCamelCase=None ) -> None:
try:
import datasets
except (ModuleNotFoundError, ImportError):
raise ImportError('run pip inst... | 715 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''... | 52 | 0 |
from __future__ import annotations
import os
from collections.abc import Mapping
SCREAMING_SNAKE_CASE__ = tuple[int, int]
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Tuple , _snake_case : set[int] ... | 716 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert im... | 52 | 0 |
def A ( __UpperCamelCase , __UpperCamelCase ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def A ( ) -> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or_gate(1 , 0 ) == 1
assert or_gate(1 , 1 ) ==... | 717 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
SCREAMING_SNAKE_CASE__ = '''sshleifer/bart-tiny-random'''
... | 52 | 0 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Conf... | 718 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple... | 52 | 0 |
'''simple docstring'''
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def A ( __UpperCamelCase... | 719 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'''configuration_xlm_roberta'''... | 52 | 0 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def A ( __UpperCamelCase ,... | 720 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 52 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelTes... | 721 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 52 | 0 |
def A ( __UpperCamelCase ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 700 |
def A ( __UpperCamelCase ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 52 | 0 |
import baseaa
def A ( __UpperCamelCase ) -> bytes:
return baseaa.baaencode(string.encode('utf-8' ) )
def A ( __UpperCamelCase ) -> str:
return baseaa.baadecode(__UpperCamelCase ).decode('utf-8' )
if __name__ == "__main__":
SCREAMIN... | 701 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : Any , _snake_case : str=None , _snake_case : Dict=None , _snake_case... | 52 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InformerConfig''',
... | 702 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
Da... | 52 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/reso... | 703 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 52 | 0 |
import os
def A ( ) -> Any:
with open(os.path.dirname(__UpperCamelCase ) + '/grid.txt' ) as f:
A__ = [] # noqa: E741
for _ in range(20 ):
l.append([int(__UpperCamelCase ) for x in f.readline().split()] )
A__ = 0
# ri... | 704 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))
... | 52 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversat... | 705 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INP... | 52 | 0 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 706 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
SCREAMING_SNAKE_CASE__ = r'''
Args:
input_ids (`jnp.ndarray` of shape `(batch_... | 52 | 0 |
import os
import sys
import unittest
SCREAMING_SNAKE_CASE__ = 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_dummy_object, fin... | 707 |
import argparse
import struct
import unittest
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[str] , _snake_case : bytes ):
"""simple docstring"""
A__ = data
# Initialize hash values
... | 52 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, slow
from ..test_modeling... | 708 |
import math
import random
def A ( __UpperCamelCase , __UpperCamelCase = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
SCREAMING_SNAKE_CASE__ = 0.02
def A ( __UpperCamelCase , __UpperCamel... | 52 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''google/bit-50''': '''h... | 709 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 52 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class __lowerCAmelCase (... | 710 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-base''': '''https:/... | 52 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFeat... | 711 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_co... | 52 | 0 |
'''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 __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def __init__( self : ... | 712 |
import pytest
import datasets
# Import fixture modules as plugins
SCREAMING_SNAKE_CASE__ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def A ( __UpperCamelCase , __UpperCamelCase ) -> Optional[int]:
# Mark tests as "unit" by default... | 52 | 0 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar('''KEY''')
SCREAMING_SNAKE_CASE__ = TypeVar('''VAL''')
@dataclass(frozen=UpperCAmelCase_ , slots=UpperCAmelCase_ )
class... | 713 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = args.log_outputs
A__ =... | 52 | 0 |
from __future__ import annotations
def A ( __UpperCamelCase ) -> list[int]:
return [ord(__UpperCamelCase ) - 96 for elem in plain]
def A ( __UpperCamelCase ) -> str:
return "".join(chr(elem + 96 ) for elem in encoded )
def A ( ) ... | 714 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 52 | 0 |
from random import randint, random
def A ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase = False , __UpperCamelCase = False , __UpperCamelCase = 5 , ) -> list:
A__ = [[-1] * number_of_cells] # Create a highway without any car
A__ = 0
A__... | 715 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''... | 52 | 0 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __lowerCAm... | 716 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert im... | 52 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_... | 717 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
SCREAMING_SNAKE_CASE__ = '''sshleifer/bart-tiny-random'''
... | 52 | 0 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
... | 718 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple... | 52 | 0 |
'''simple docstring'''
import math
class __lowerCAmelCase :
"""simple docstring"""
def _a ( self : List[Any] , _snake_case : list[list[float]] , _snake_case : list[int] ):
"""simple docstring"""
A__... | 719 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'''configuration_xlm_roberta'''... | 52 | 0 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def A ( ) -> Tuple:
A__ ... | 720 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 52 | 0 |
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditionalGeneration, BartTokeniz... | 721 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 52 | 0 |
from __future__ import annotations
import time
SCREAMING_SNAKE_CASE__ = list[tuple[int, int]]
SCREAMING_SNAKE_CASE__ = [
[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, ... | 700 |
def A ( __UpperCamelCase ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 52 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
loggi... | 701 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : Any , _snake_case : str=None , _snake_case : Dict=None , _snake_case... | 52 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __lowerCAmelCase ( UpperCAmelCase_ ):
def __init__( self : str , _snake_case : int , _snake_case : List[Any] ):
"""simple do... | 702 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
Da... | 52 | 0 |
from __future__ import annotations
def A ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , ) -> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less than 2 values' )
elif electron_conc < 0:... | 703 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 52 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple... | 704 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))
... | 52 | 0 |
import re
def A ( __UpperCamelCase ) -> str:
if len(re.findall('[ATCG]' , __UpperCamelCase ) ) != len(__UpperCamelCase ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' , 'TAGC' ) )
if __name__ == "__main__":
imp... | 705 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_INP... | 52 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require... | 706 |
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
SCREAMING_SNAKE_CASE__ = r'''
Args:
input_ids (`jnp.ndarray` of shape `(batch_... | 52 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert impor... | 707 |
import argparse
import struct
import unittest
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : List[str] , _snake_case : bytes ):
"""simple docstring"""
A__ = data
# Initialize hash values
... | 52 | 0 |
import random
def A ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase = False ) -> dict:
A__ = {i: [] for i in range(__UpperCamelCase )}
# if probability is greater or equal than 1, then generate a complete graph
if probability >= 1:
return complete_gra... | 708 |
import math
import random
def A ( __UpperCamelCase , __UpperCamelCase = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
SCREAMING_SNAKE_CASE__ = 0.02
def A ( __UpperCamelCase , __UpperCamel... | 52 | 0 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, Pro... | 709 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoToke... | 52 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils impo... | 710 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''roberta-base''': '''https:/... | 52 | 0 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def __init__( self : str , ... | 711 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_co... | 52 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class __lowerCAmelCase :
"""simple docstring"""
A__ : int
A__ : Node | None ... | 712 |
import pytest
import datasets
# Import fixture modules as plugins
SCREAMING_SNAKE_CASE__ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def A ( __UpperCamelCase , __UpperCamelCase ) -> Optional[int]:
# Mark tests as "unit" by default... | 52 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ... | 713 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A ( __UpperCamelCase , __UpperCamelCase ) -> Tuple:
A__ = args.log_outputs
A__ =... | 52 | 0 |
from __future__ import annotations
def A ( __UpperCamelCase ) -> float:
if not nums:
raise ValueError('List is empty' )
return sum(__UpperCamelCase ) / len(__UpperCamelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 714 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNA... | 52 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 715 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'''... | 52 | 0 |
from __future__ import annotations
from random import choice
def A ( __UpperCamelCase ) -> Optional[Any]:
return choice(__UpperCamelCase )
def A ( __UpperCamelCase , __UpperCamelCase ) -> int:
A__ = random_pivot(__UpperCamelCase... | 716 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_rembert im... | 52 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : Any , _snake_case : str=None , _snake_case : Dict=None , _snake_case... | 717 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
SCREAMING_SNAKE_CASE__ = '''sshleifer/bart-tiny-random'''
... | 52 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'''transfo-xl-wt103''': '''https://huggingface.co/transfo-xl-wt103/resolve/main/config.json''',
}
class __lowerCAmelCas... | 718 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple... | 52 | 0 |
'''simple docstring'''
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGE... | 719 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
'''configuration_xlm_roberta'''... | 52 | 0 |
import math
import random
def A ( __UpperCamelCase , __UpperCamelCase = False ) -> float:
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
SCREAMING_SNAKE_CASE__ = 0.02
def A ( __UpperCamelCase , __UpperCamel... | 720 |
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_logging
sys.path.append(os.p... | 52 | 0 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers i... | 721 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 52 | 0 |
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def A ( __UpperCamelCase , ... | 700 |
def A ( __UpperCamelCase ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 52 | 0 |
from manim import *
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : List[Any] ):
"""simple docstring"""
A__ = Rectangle(height=0.5 , width=0.5 )
A__ = Rectangl... | 701 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCAmelCase ( UpperCAmelCase_ ):
"""simple docstring"""
def _a ( self : Any , _snake_case : str=None , _snake_case : Dict=None , _snake_case... | 52 | 0 |
from PIL import Image
def A ( __UpperCamelCase ) -> Image:
A__ , A__ = image.size
A__ = 0
A__ = image.load()
for i in range(__UpperCamelCase ):
for j in range(__UpperCamelCase ):
A__ = pixels[j, i]
mean +=... | 702 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
Da... | 52 | 0 |
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