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 json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONF... | 366 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.nu... | 650 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, is... | 317 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
... | 539 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 0 |
'''simple docstring'''
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case ( lowercase , unittest.TestCase ):
... | 675 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
def __magic_name__ ( lowercase_ , lowercase_ ) -> Any:
'''simple docstring'''
if not isinstance(lowercase_ , lowercase_ ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(lowercase_ , lowercase_ )... | 606 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
from manim import *
class __magic_name__ ( _a):
def _UpperCAmelCase ( self : int ):
UpperCAmelCase = Rectangle(height=0.5 ,width=0.5 )
UpperCAmelCase = Rectangle(height=0.46 ,width=0.46 ).set_stroke(width=0 )
UpperCAmelCase =... | 333 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
SCREAMING_SNAKE_CASE__ = r'''\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control th... | 47 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def _a ( __lowercase , __lowercase=1000 ) -> Dict:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
__UpperCamelCas... | 383 |
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_common import ConfigTester
... | 625 | 0 |
'''simple docstring'''
UpperCamelCase_ = {
"""Pillow""": """Pillow<10.0.0""",
"""accelerate""": """accelerate>=0.20.3""",
"""av""": """av==9.2.0""",
"""beautifulsoup4""": """beautifulsoup4""",
"""black""": """black~=23.1""",
"""codecarbon""": """codecarbon==1.2.0""",
""... | 92 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
'''simple docstring'''
import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
# Fitting Polynomial Regression to the dataset
from sklearn.prep... | 404 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
_SCREAMING_SNAKE_CASE = TypeVar("T")
_SCREAMING_SNAKE_CASE = TypeVar("U")
class __UpperCAmelCase ( Generic[T, U] ):
'''simple docstring'''
... | 366 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
from math import factorial
def SCREAMING_SNAKE_CASE_ ( snake_case : str = 20 )-> str:
_lowerCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
_lowerCamelCase = n // 2
... | 650 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...t... | 317 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_f... | 539 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
... | 675 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class __UpperCAmelCase :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> List[str]:
... | 606 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...t... | 333 |
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_ = {
'configuration_owlvit':... | 625 | 0 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
... | 47 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
from __future__ import annotations
def _a ( __lowercase ) -> Union[str, Any]:
"""simple docstring"""
if len(__lowercase ) == 0:
return []
__UpperCamelCase , __UpperCamelCase = min(__lowercase ), max(__lowercase )
__UpperCame... | 383 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require... | 92 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ... | 404 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
def lowerCamelCase( SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ) -> Dict:
if index == r:
for j in range(SCREAMING_SNAKE_CASE_ ):
p... | 366 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A_ : Optional[int] ={
"""configuration_lilt""": ["""LILT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LiltConfig"""],
}
try:
if not is_torch_available():
... | 650 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def UpperCAmelCase__ ( __snake_case ) -> Optional[Any]:
_A = prime_factors(__snake_case )
if is_square_free(__snake_case ):
return -1 if len(__snake_case ) % 2 else 1
re... | 317 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
'''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, Swin... | 539 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 0 |
'''simple docstring'''
from math import sqrt
def __snake_case ( UpperCAmelCase_ : Union[str, Any] ):
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 prim... | 675 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a : Tuple = {
"""configuration_mask2former""": [
"""MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Mask2FormerConfig""",
... | 606 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
def __UpperCamelCase ( _lowerCAmelCase ):
"""simple docstring"""
for i in range(len(_lowerCAmelCase ) - 1 , 0 , -1 ):
UpperCAmelCase = False
for j in range(_lowerCAmelCase , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
... | 333 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import argparse
import os
import re
SCREAMING_SNAKE_CASE__ = '''src/transformers/models/auto'''
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
SCREAMING_SNAKE_CASE__ = re.compile(r'''[A-Z_... | 47 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
def _a ( __lowercase , __lowercase = False ) -> List[Any]:
"""simple docstring"""
if not isinstance(__lowercase , __lowercase ):
__UpperCamelCase = F"""Expected string as input, found {type(__lowercase )}"""
raise ValueError(_... | 383 |
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_common import ConfigTester
... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
from cmath import sqrt
def _lowerCAmelCase ( __magic_name__ : int , __magic_name__ : str , __magic_name__ : List[Any] ) -> Dict:
if a == 0:
raise ValueError('''Coefficient \'a\' mus... | 92 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowerCamelCase : Dict = logging.get_logger(__name__)
__lowerCamelCase : Tuple = {
'ut/deta': 'https://huggingface.co/ut/deta/resolve/mai... | 404 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
'''simple docstring'''
def lowerCamelCase( SCREAMING_SNAKE_CASE_ ) -> int:
if not numbers:
return 0
if not isinstance(SCREAMING_SNAKE_CASE_ ,(list, tuple) ) or not all(
isinstance(SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ ) for number in numbers ):
... | 366 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __a ( lower... | 650 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
def UpperCAmelCase__ ( __snake_case = 1_000 ) -> int:
_A = 3
_A = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __name__ == "__main__":
print(f'''{solution() = }''') | 317 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
UpperCAmelCase_ = logging.get_logger(__name__)
class __lowercase ( __magic_name__ ):
_a = ... | 539 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a_ : Any = {
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 675 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transforme... | 606 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __magic_name__ :
_UpperCAmelCase : Optional[int] = 42 # [batch_size x 3]
_UpperCAmelCase : List[str] = 42 # [batch_size x 3]
_UpperCAmelCase : List[Any] = 42 # [batch... | 333 |
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_ = {
'configuration_owlvit':... | 625 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=__lowercase ):
UpperCAmelCase__ = ['''note_seq''']
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ ):
"""simple docstri... | 626 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 626 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 626 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttentio... | 626 | 1 |
"""simple docstring"""
# 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
#
# ... | 626 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case ( __lowercase ):
UpperCAmelCase__ = (UnCLIPScheduler,)
def _lowercase (self , **SCREAMING_SNAKE_CASE_ ):
""... | 626 | 1 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {'vocab_file': 'vocab.json'}
lowerCAmelCase__ = {
'voca... | 626 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqa... | 626 | 1 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# - g... | 626 |
"""simple docstring"""
from __future__ import annotations
import math
def _lowerCamelCase ( __a ):
if num <= 0:
SCREAMING_SNAKE_CASE_ = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__a )
SCREAMING_SNAKE_CASE_ = [True] * (num + 1)
... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
if len(__a ) < 2:
return collection
def circle_sort_util(__a, __a, __a ) -> bool:
SCREAMING_SNAKE_CASE_ = False
if low == high:
return swapped
SCREAMING_SNAKE_CASE_ = low
SCREAMING_SNA... | 626 |
"""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
#
# ... | 626 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( __a, __a ):
if partitions <= 0:
raise ValueError('''partitions must be a positive number!''' )
if partitions > number_of_bytes:
raise ValueError('''partitions can not > number_of_bytes!''' )
S... | 626 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=__lowercase ):
UpperCAmelCase__ = ['''note_seq''']
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ ):
"""simple docstri... | 626 | 1 |
"""simple docstring"""
class snake_case ( __lowercase ):
pass
class snake_case ( __lowercase ):
pass
class snake_case :
def __init__(self ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = [
[],
[],... | 626 |
"""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
if is_tf_available():
import numpy as np
import tensorflow as tf
from transfor... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod() | 626 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_SNAKE_CASE_ = 1
while repunit:
SCREAMING_SNAKE_CASE_ = (10 * repunit + 1) % divisor
repunit_index += 1
return repuni... | 626 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {'configuration_vit': ['VIT_PRETRAINED_CONFIG_ARCHIVE_MAP',... | 626 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( __a, __a = None ):
SCREAMING_SNAKE_CASE_ = word_bank or []
# create a table
SCREAMING_SNAKE_CASE_ = len(__a ) + 1
SCREAMING_SNAKE_CASE_ = []
for _ in range(__a ):
tabl... | 626 | 1 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run ... | 626 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNL... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7: [6, 8],
8: [5, 7],
},
{
0: [6],... | 626 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def _lowerCamelCase ( __a, __a, __a, __a = 100, ):
SCREAMING_SNAKE_CASE_ = x_start
SCREAMING_SNAKE_CASE_ = fnc(__a )
SCREAMING_SNAKE_CASE_ = 0.0
for _ in ran... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( __a, __a ):
SCREAMING_SNAKE_CASE_ = ''''''
for i in table:
res += inp[i - 1]
return res
def _lowerCamelCase ( __a ):
return data[1:] + data[0]
def _lowerCamelCase ( __a, __a ):
SCREAMING_SNAK... | 626 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 626 | 1 |
"""simple docstring"""
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase__ = version.parse(importlib_metadata.version('nltk'))
if NLTK_VERSION >= version.Version('3.6.4'):
from nltk import word_tokenize
... | 626 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCamelCase ( __a = "isbn/0140328726" ):
SCREAMING_SNAKE_CASE_ = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if n... | 626 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _lowerCamelCase ( __a )... | 626 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.di... | 626 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def _lowerCamelCase ( __a, __a, __a, __a = 100, ):
SCREAMING_SNAKE_CASE_ = x_start
SCREAMING_SNAKE_CASE_ = fnc(__a )
SCREAMING_SNAKE_CASE_ = 0.0
for _ in ran... | 626 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case ( __lowercase , ... | 626 | 1 |
"""simple docstring"""
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowerCAmelCase__ = logging.get_logger(__na... | 626 |
"""simple docstring"""
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def _lowerCamelCase ( __a ):
return input_array.reshape((input_array.size, 1) )
def _lowerCamelCase ( __a, __... | 626 | 1 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case ( __lowercase ):
UpperCAmelCase__ = (UnCLIPScheduler,)
def _lowercase (self , **SCREAMING_SNAKE_CASE_ ):
""... | 626 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class snake_case :
def __init__(self ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = [2, 1, 2, -1]
SCREAMING_SNAKE_CASE_ = [1, 2, 3, 4]
def... | 626 | 1 |
"""simple docstring"""
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerCamelCase ... | 626 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import pat... | 626 | 1 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available()... | 626 |
"""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 OptionalDependencyNotAvailable:
... | 626 | 1 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from... | 626 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowerCAmelCase__ = r'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the m... | 626 | 1 |
"""simple docstring"""
import inspect
import unittest
class snake_case ( unittest.TestCase ):
def _lowercase (self ):
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert False
def ... | 626 |
"""simple docstring"""
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
... | 626 | 1 |
"""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
#
# ... | 626 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 626 | 1 |
"""simple docstring"""
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeli... | 626 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttentio... | 626 | 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 ( __a ):
# encoder.embeddings are double copied in origina... | 626 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case ( __lowercase ):
UpperCAmelCase__ = (UnCLIPScheduler,)
def _lowercase (self , **SCREAMING_SNAKE_CASE_ ):
""... | 626 | 1 |
"""simple docstring"""
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeach... | 626 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqa... | 626 | 1 |
"""simple docstring"""
import argparse
import json
import subprocess
def _lowerCamelCase ( __a, __a ):
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = (
F'curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'
''' https://api.githu... | 626 |
"""simple docstring"""
from __future__ import annotations
import math
def _lowerCamelCase ( __a ):
if num <= 0:
SCREAMING_SNAKE_CASE_ = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__a )
SCREAMING_SNAKE_CASE_ = [True] * (num + 1)
... | 626 | 1 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
... | 626 |
"""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
#
# ... | 626 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
lowerCAmelCase__ = logging.getLogger(__name__)
@dataclass
class snake_case ( __lowercase ):
... | 626 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=__lowercase ):
UpperCAmelCase__ = ['''note_seq''']
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ ):
"""simple docstri... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( ):
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = 1
while len(__a ) < 1E6:
constant.append(str(__a ) )
i += 1
SCREAMING_SNAKE_CASE_ = ''''''.join(__a )
return (
int(constant[0] )
... | 626 |
"""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
if is_tf_available():
import numpy as np
import tensorflow as tf
from transfor... | 626 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
A... | 626 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_SNAKE_CASE_ = 1
while repunit:
SCREAMING_SNAKE_CASE_ = (10 * repunit + 1) % divisor
repunit_index += 1
return repuni... | 626 | 1 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowerCAmelCase__ = importlib.util.find_spec('s3fs') is not None
if _has_safs:
from .safi... | 626 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( __a, __a = None ):
SCREAMING_SNAKE_CASE_ = word_bank or []
# create a table
SCREAMING_SNAKE_CASE_ = len(__a ) + 1
SCREAMING_SNAKE_CASE_ = []
for _ in range(__a ):
tabl... | 626 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTester... | 626 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNL... | 626 | 1 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNL... | 626 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def _lowerCamelCase ( __a, __a, __a, __a = 100, ):
SCREAMING_SNAKE_CASE_ = x_start
SCREAMING_SNAKE_CASE_ = fnc(__a )
SCREAMING_SNAKE_CASE_ = 0.0
for _ in ran... | 626 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'XCLIPVi... | 626 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 626 | 1 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert ... | 626 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCamelCase ( __a = "isbn/0140328726" ):
SCREAMING_SNAKE_CASE_ = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if n... | 626 | 1 |
"""simple docstring"""
class snake_case :
def __init__(self ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = 0
SCREAMING_SNAKE_CASE_ = {}
def _lowercase (self , SCREAMING_SNAKE_C... | 626 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.di... | 626 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline... | 626 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case ( __lowercase , ... | 626 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'... | 626 |
"""simple docstring"""
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def _lowerCamelCase ( __a ):
return input_array.reshape((input_array.size, 1) )
def _lowerCamelCase ( __a, __... | 626 | 1 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def _lowerCamelCase ( __a ):
return np.dot(__a, __a )
class snake_case :
def __init__(self , *,
SCREAMING_SNAKE_CASE_ ... | 626 |
"""simple docstring"""
import doctest
from collections import deque
import numpy as np
class snake_case :
def __init__(self ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ = [2, 1, 2, -1]
SCREAMING_SNAKE_CASE_ = [1, 2, 3, 4]
def... | 626 | 1 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
lowerCAmelCase__ = '1'
lowerCAmelCase__ = '0'
lowerCAmelCase__ = '1'
lowerCAmelCase__ = ort.SessionOptions()
lowerCAmelCase__ = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('Create i... | 626 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import pat... | 626 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda... | 626 |
"""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 OptionalDependencyNotAvailable:
... | 626 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case ( __lowercase , ... | 626 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowerCAmelCase__ = r'\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control the m... | 626 | 1 |
"""simple docstring"""
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
... | 626 |
"""simple docstring"""
from typing import Dict, Iterable, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
... | 626 | 1 |
"""simple docstring"""
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase__ = 'src/transformers'
# Matches is_xxx_available()
lowerCAmelCase__ = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase__ ... | 626 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 626 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import (
... | 626 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttentio... | 626 | 1 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def _lowerCamelCase ( __a ):
return ConvertCommand(
args.model_type, args.tf_checkpoint, args.pytorch_dump_output, args.config, args.fine... | 626 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case ( __lowercase ):
UpperCAmelCase__ = (UnCLIPScheduler,)
def _lowercase (self , **SCREAMING_SNAKE_CASE_ ):
""... | 626 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _lowerCamelCase ( __a ):
SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ = analyze_text(__a )
SCREAMING_SNAKE_CASE_ = list(''' ''' +... | 626 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqa... | 626 | 1 |
"""simple docstring"""
import argparse
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import ... | 626 |
"""simple docstring"""
from __future__ import annotations
import math
def _lowerCamelCase ( __a ):
if num <= 0:
SCREAMING_SNAKE_CASE_ = F'{num}: Invalid input, please enter a positive integer.'
raise ValueError(__a )
SCREAMING_SNAKE_CASE_ = [True] * (num + 1)
... | 626 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( __a, __a, __a, __a ): # noqa: E741
while r - l > 1:
SCREAMING_SNAKE_CASE_ = (l + r) // 2
if v[m] >= key:
SCREAMING_SNAKE_CASE_ = m
else:
SCREAMING_SNAKE_CASE_ ... | 626 |
"""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
#
# ... | 626 | 1 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input('Enter image url: ').strip()
print(f'''Downloading image from {url} ...''')
lowerCAmelCase__ = BeautifulSoup(requests.get(url).con... | 626 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=__lowercase ):
UpperCAmelCase__ = ['''note_seq''']
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ ):
"""simple docstri... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_SNAKE_CASE_ = 2
while i * i <= n:
SCREAMING_SNAKE_CASE_ = 0
while n % i == 0:
n //= i
multiplicity += 1
n_divisors *= multiplicity + 1
i += 1
if n > 1:
... | 626 |
"""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
if is_tf_available():
import numpy as np
import tensorflow as tf
from transfor... | 626 | 1 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.di... | 626 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_SNAKE_CASE_ = 1
while repunit:
SCREAMING_SNAKE_CASE_ = (10 * repunit + 1) % divisor
repunit_index += 1
return repuni... | 626 | 1 |
"""simple docstring"""
def _lowerCamelCase ( __a ):
if len(__a ) <= 1:
return lst
SCREAMING_SNAKE_CASE_ = 1
while i < len(__a ):
if lst[i - 1] <= lst[i]:
i += 1
else:
SCREAMING_SNAKE_CASE_ ,SCREAMING_SNAKE_CASE_ = lst[i], lst[i - 1]
i -... | 626 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( __a, __a = None ):
SCREAMING_SNAKE_CASE_ = word_bank or []
# create a table
SCREAMING_SNAKE_CASE_ = len(__a ) + 1
SCREAMING_SNAKE_CASE_ = []
for _ in range(__a ):
tabl... | 626 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 626 |
"""simple docstring"""
import datasets
from .evaluate import evaluate
lowerCAmelCase__ = '\\n@inproceedings{Rajpurkar2016SQuAD10,\n title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},\n author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},\n booktitle={EMNL... | 626 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase__ = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that gene... | 626 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def _lowerCamelCase ( __a, __a, __a, __a = 100, ):
SCREAMING_SNAKE_CASE_ = x_start
SCREAMING_SNAKE_CASE_ = fnc(__a )
SCREAMING_SNAKE_CASE_ = 0.0
for _ in ran... | 626 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( __a, __a, __a, __a, __a, ):
SCREAMING_SNAKE_CASE_ = len(__a )
# If row is equal to the size of the board it means there are a queen in each row in
# the current board (possible_board)
i... | 626 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 626 | 1 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSequence... | 626 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCamelCase ( __a = "isbn/0140328726" ):
SCREAMING_SNAKE_CASE_ = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if n... | 626 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
lowerCAmelCase__ = datasets.utils.logging.get_logger(__name__)
@dataclass
class snak... | 626 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.di... | 626 | 1 |
"""simple docstring"""
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require... | 626 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class snake_case ( __lowercase , ... | 626 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.