code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
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... | 123 |
from collections import deque
def A__ ( __A : Optional[Any] ) ->Tuple:
__A =len(__A )
__A =deque()
__A =[False for _ in range(__A )]
__A =[-1 for _ in range(__A )]
__A =index_of[:]
def strong_connect(__A : Union[str, Any] ... | 184 | 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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import... | 720 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_model... | 534 | 0 |
'''simple docstring'''
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_con... | 421 |
'''simple docstring'''
from math import pi
def UpperCamelCase__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 270 | 0 |
"""simple docstring"""
import torch
from diffusers import StableDiffusionPipeline
__snake_case : Tuple = 'path-to-your-trained-model'
__snake_case : Dict = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to('cuda')
__snake_case : Optional[A... | 719 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViT... | 128 | 0 |
'''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 TokenizerTest... | 42 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_att... | 42 | 1 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transform... | 710 |
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
is_pipeline_test,
... | 284 | 0 |
import os
def __SCREAMING_SNAKE_CASE ( ) -> int:
__A : Optional[Any] = os.path.join(os.path.dirname(a__ ) ,"""num.txt""" )
with open(a__ ) as file_hand:
return str(sum(int(a__ ) for line in file_hand ) )[:10]
if __name__ == "__main__":
print(... | 17 | import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def SCREAMING_SNAKE_CASE_ ( snake_case__ , snake_case__=() , snake_case__=None , snake_case__="no" , snake_case__="... | 312 | 0 |
from __future__ import annotations
def A_ ( a , a , a , a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : int = []
SCREAMING_SNAKE_CASE_ : List[Any] = input_list[low:mid], input_list[mid : high + 1]
while left and right:
... | 717 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase : str = {
'microsoft/git-base': 'https://huggingface.co/microsoft/git-b... | 353 | 0 |
"""simple docstring"""
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
fr... | 341 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a : List[Any] = logging.get_logger(__name__)
__a : List[Any] = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c... | 534 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE... | 557 |
def _snake_case (_snake_case : str , _snake_case : str) -> float:
def get_matched_characters(_snake_case : str , _snake_case : str) -> str:
_lowercase =[]
_lowercase =min(len(_stra) , len(_stra)) // 2
... | 557 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
"""feature_extraction_mctct... | 630 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ): # This function is recursive
_lowerCamelCase : Optional[Any] = len(lowercase__ )
# If the array contains only one element, we return it (it's t... | 630 | 1 |
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 712 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
UpperCAmelCase = 299_792_458
# Symbols
UpperCAmelCase , UpperCAmelCase , UpperCAmelCase , UpperCAmelCase = symbols("""ct x y z""")
def A_ ( __a ... | 351 | 0 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_snake_case = get_tests_dir() + "/te... | 500 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common ... | 525 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase = '▁'
__UpperCAmelCase = {'vocab_file': 'sp... | 717 |
"""simple docstring"""
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset,... | 194 | 0 |
"""simple docstring"""
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..... | 177 |
"""simple docstring"""
def __lowercase ( snake_case_ : int ,snake_case_ : int ) ->int:
'''simple docstring'''
return int((input_a, input_a).count(0 ) == 0 )
def __lowercase ( ) ->None:
'''simple docstring'''
assert and_gate(0 ... | 177 | 1 |
from sklearn.metrics import matthews_corrcoef
import datasets
lowerCamelCase_ = '''
Compute the Matthews correlation coefficient (MCC)
The Matthews correlation coefficient is used in machine learning as a
measure of the quality of binary and multiclass classifications. It takes
into account true and false pos... | 702 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 86 | 0 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_lowerCamelCase : int = """\
"""
_lowerCamelCase : int = """
Perplexity (PPL) is one of the most com... | 87 |
'''simple docstring'''
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
a__ : Optional[int] = version.parse(version.parse(torch.__version__).base_version) < version.... | 368 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : ... | 720 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
_snake_case : int = {
"debug... | 203 | 0 |
def __a ( __lowerCAmelCase ) -> list:
if n_term == "":
return []
SCREAMING_SNAKE_CASE : list = []
for temp in range(int(__lowerCAmelCase ) ):
series.append(F'''1/{temp + 1}''' if series else '1' )
return series
if __... | 352 |
_lowerCamelCase : Optional[Any] = 256
# Modulus to hash a string
_lowerCamelCase : Optional[Any] = 1_000_003
def __a ( __lowerCAmelCase , __lowerCAmelCase ) -> bool:
SCREAMING_SNAKE_CASE : Tuple = len(__lowerCAmelCase )
S... | 352 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
_lowerCAmelCase = TypeVar("""T""")
_lowerCAmelCase = TypeVar("""U""")
class UpperCAmelCase__ ( Generic[T, U] ):
def __init__( self , A__ , ... | 306 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.json""",
"""tokenizer_config_fil... | 306 | 1 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __a ( __a ):
'''simple docstring'''
_lowerCamelCase : List[str] = (DDIMParallelScheduler,)
... | 118 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.d... | 118 | 1 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
_lowerCamelCase = {
'''facebook/maskformer-swin-base-ade''': (
'''http... | 321 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.data import DataLoader, Ra... | 321 | 1 |
import enum
import shutil
import sys
__a ,__a = shutil.get_terminal_size()
__a = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class __a( enum.Enum ):
"""simple docstring"""
lowerCAmelCase = 0
lowerCAmelCase = 1
def lowe... | 30 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPipeline,
... | 269 | 0 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def A_ ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ):
... | 718 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 38 | 0 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
... | 39 |
'''simple docstring'''
def UpperCAmelCase ( lowerCamelCase_ :Union[str, Any] ):
'''simple docstring'''
snake_case_ : str = len(lowerCamelCase_ )
while cur > 1:
# Find the maximum number in arr
snake_case_ : Optional[Any] = arr.index(max(arr[0:... | 334 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
A_ : Dict =[int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def snake_case_ ( ) -> Union[str, Any]:
lowerCAmelCase_ = os.path.dirname(os.path.realpath(__snake_case))
lowerCAmelCase... | 700 | '''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,... | 606 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokeni... | 277 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils im... | 466 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowerCAmelCase__ ( metaclass=_snake_case ):
'''simple docstring'''
lowerCamelCase__ = ['note_seq']
def __init__( self , *lowercase , **lowercase ... | 713 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch... | 492 | 0 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def _SCREAMING_SNAKE_CASE ( _lowercase : str , _lowercase : float | Decimal , _lowercase : ... | 633 |
'''simple docstring'''
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def __a(SCREAMING_SNAKE_CASE_ : Any , SCREAMING_SNAKE_CASE_ : Tuple=None ):
'''simple docstring'''
... | 18 | 0 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def _lowerCAmelCase ( lowercase : int = 1_0_0_0_0_0_0 , lowercase : int = 1_0 ) ->int:
"""simple docstring"""
lowercase__ = defaultd... | 700 |
'''simple docstring'''
def _lowerCAmelCase ( lowercase : int , lowercase : int ) ->str:
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError('''the value of both inputs must be positive''' )
lowercase__ = st... | 318 | 0 |
'''simple docstring'''
class _lowercase :
'''simple docstring'''
def __init__( self ,lowerCamelCase_ ) -> None:
'''simple docstring'''
UpperCAmelCase__ : List[Any] = len(lowerCamelCase_ )
UpperCAmelCase__ : Dict ... | 614 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase__ : List[str] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
... | 614 | 1 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 720 |
# limitations under the License.
# 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 .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
dep... | 115 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
SCREAMING_SNAKE_CASE_ ... | 34 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
EN... | 532 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
if is_torch_av... | 703 |
"""simple docstring"""
from itertools import permutations
def A__ ( UpperCamelCase ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
A = [7, 11... | 524 | 0 |
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgumentParser, TrainingArguments... | 81 |
def UpperCAmelCase_ ( __UpperCamelCase, __UpperCamelCase ):
return 1 if input_a == input_a else 0
def UpperCAmelCase_ ( ):
assert xnor_gate(0, 0 ) == 1
assert xnor_gate(0, 1 ) == 0
assert xnor_gate(1, 0 ) == 0
asse... | 151 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
... | 44 |
'''simple docstring'''
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
exc... | 44 | 1 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def UpperCAmelCase__ ( __magic_name__ : str = "isbn/0140328726" ):
'''simple docstring'''
lowerCAmelCase : Optional[Any] = olid.strip().strip('''/''' ) # Remove leading/... | 348 |
from ..utils import DummyObject, requires_backends
class __magic_name__ ( metaclass=snake_case ):
_lowerCAmelCase = ["flax"]
def __init__( self : Any , *lowerCamelCase__ : Any , **lowerCamelCase__ : Any ):
requires_backends(self , ['''flax''']... | 348 | 1 |
from __future__ import annotations
import numpy as np
def A ( lowercase ) -> str:
'''simple docstring'''
return np.maximum(0 , lowercase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 3 |
def A ( lowercase , lowercase ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
UpperCamelCase = str(bin(lowercase ) )[2:] # remove the leading "0b"
UpperCamelCase = str(bin(lowercase ) )[... | 3 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
class SCREAMING_SNAKE_CASE :
def __init__( self , _UpperCAmelCase):
'''simple docstring'''
__A : int = size
# approximate the overall ... | 8 |
'''simple docstring'''
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class SCREAMING_SNAKE_CASE :
def __init_... | 8 | 1 |
from __future__ import annotations
import time
import numpy as np
UpperCAmelCase__ : List[str] = [8, 5, 9, 7]
UpperCAmelCase__ : List[str] = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
UpperCAmelCase__ : Union[str, An... | 707 |
def __lowercase ( _A , _A ) -> int:
assert x is not None
assert y is not None
SCREAMING_SNAKE_CASE : int = len(_A )
SCREAMING_SNAKE_CASE : Union[str, Any] = len(_A )
# declaring the array for storing the dp values
... | 446 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _SCREAMING_SNAKE_CASE ( __UpperCamelCase ):
_A : Tuple = ['image_processor', 'tokenizer']
_A : str = 'ViTImageProcessor'
_A : str... | 276 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer
__ma... | 276 | 1 |
"""simple docstring"""
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def lowercase (_snake_case ,_snake_case ,_snake_case=1024 ,_snake_case=1024 ,_snake_case=False ,**_snake_case ) ->... | 228 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
s... | 228 | 1 |
'''simple docstring'''
class UpperCamelCase__ :
def __init__( self : Dict ):
'''simple docstring'''
a__ = {} # Mapping from char to TrieNode
a__ = False
def __a ( self : Optional[Any] , lowerCamelCase : Dic... | 489 |
'''simple docstring'''
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create s... | 8 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_atte... | 383 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"facebook/convnextv2-tiny-1k-2... | 383 | 1 |
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
_A : Optional[Any] = logging.get_logger(__name... | 315 |
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
AutoModelForMaskedLM... | 315 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...... | 702 |
'''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_SCREAMING_SNAKE_CASE = "src/t... | 489 | 0 |
'''simple docstring'''
def lowercase__( __UpperCamelCase: str ):
"""simple docstring"""
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 28 |
'''simple docstring'''
__lowercase : List[Any] = {
'''meter''': '''m''',
'''kilometer''': '''km''',
'''megametre''': '''Mm''',
'''gigametre''': '''Gm''',
'''terametre''': '''Tm''',
'''petametre''': '''Pm''',
'''exametre''': '''Em''',
'''zettametre''': '''Zm''',
'''yo... | 422 | 0 |
from __future__ import annotations
def _lowercase ( lowercase__ ):
if len(a_ ) == 0:
return []
__lowerCAmelCase : Optional[Any] = min(a_ ), max(a_ )
__lowerCAmelCase : Optional[Any] = int(max_value - min_value ) + 1
__lowerCAmelCase ... | 713 |
def _lowercase ( lowercase__ , lowercase__ ):
__lowerCAmelCase : Union[str, Any] = len(lowercase__ )
__lowerCAmelCase : Any = len(lowercase__ )
__lowerCAmelCase : str = [[False for _ in range(m + 1 )] for _ in range(n + 1 )]
__low... | 583 | 0 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
T... | 550 |
'''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.dat... | 98 | 0 |
'''simple docstring'''
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class _UpperCAmelCase ( unittest.TestCase ):
def lowerCAmelCase__ ( sel... | 708 |
'''simple docstring'''
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 _UpperCAmelCase ( snake_case... | 640 | 0 |
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class __UpperCAmelCase ( unittest.TestCase ):
"""simple ... | 99 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ : List[Any] = {
'''configuration_m2m_100''': ['''M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''M2M100Config''', ''... | 497 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
__lowerCamelCase = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned'
' Distillation'
... | 721 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import... | 328 | 0 |
from __future__ import annotations
def UpperCAmelCase_ ( _UpperCAmelCase :float , _UpperCAmelCase :float , _UpperCAmelCase :float , ) -> tuple:
'''simple docstring'''
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise Val... | 188 |
from __future__ import annotations
def UpperCAmelCase_ ( _UpperCAmelCase :list[float] , _UpperCAmelCase :list[float] ) -> float:
'''simple docstring'''
A_ = sorted(numsa + numsa )
A_ , A_ = divmod(len(_UpperCAmelCase ) ... | 188 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE__ = {
'configuration_efficientformer': [
... | 707 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 35 | 0 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
while a != 0:
__snake_case , __snake_case = b % a, a
return b
def __UpperCamelCase ( SCREAMING_SNAKE... | 163 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_SCREAMING_SNAKE_CASE = {
"""configuration_maskformer""": ["""MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MaskFormerConfig"""... | 163 | 1 |
import math
def __a ( __UpperCAmelCase , __UpperCAmelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensity
if angle < 0 or angle > 360:
raise ValueError('''In Malus Law, the a... | 709 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ : Union[str, Any] = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():
raise OptionalDependen... | 148 | 0 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_bytes
... | 354 |
from collections.abc import Sequence
from queue import Queue
class __a :
def __init__( self : str , snake_case_ : List[str] , snake_case_ : Tuple , snake_case_ : Tuple , snake_case_ : Optional[Any]=None , snake_case_ ... | 354 | 1 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class _A ( __UpperCamelCase... | 702 | import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _A ( unittest.TestCase ):
... | 469 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
SCREAMING_SNAKE_CASE__ : Optional[int] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[str] = {
"Intel/dpt-large": "https://hugg... | 85 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, ... | 431 | 0 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __SCREAMING_SNAKE_CASE ( __UpperCamelCase , unittest.TestCase ):
'''simple d... | 368 |
'''simple docstring'''
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
__magic_name__ : List[str] = (
"""This metric will be removed... | 368 | 1 |
'''simple docstring'''
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device... | 685 |
def UpperCamelCase ( snake_case__ : int ) -> str:
if isinstance(snake_case__ , snake_case__ ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(snake_case__ , snake_case__ ):
raise TypeError('\'str\' object can... | 40 | 0 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class UpperCAmelCase_ :
UpperCamelCase =42
UpperCamelCase =None
UpperCamelCase =None
def __UpperCAmelCase ( __UpperCamelCase ):
... | 523 |
"""simple docstring"""
a_ = [
9_9_9,
8_0_0,
7_9_9,
6_0_0,
5_9_9,
5_0_0,
4_0_0,
3_9_9,
3_7_7,
3_5_5,
3_3_3,
3_1_1,
2_8_8,
2_6_6,
2_4_4,
2_2_2,
2_0_0,
1_9_9,
1_7_7,
1_5_5,
1_3_3,
1_1... | 523 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemantic... | 182 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsk... | 182 | 1 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ : List[str] = TypeVar('''T''')
def a ( UpperCamelCase_ : Tuple ) -> int:
return (position - 1) // 2
def a ( ... | 701 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def a ( UpperCamelCase_ : Union[str, Any] , UpperCamelCase_ : Union[str, Any] , UpperCamelCase_ : Optional[int] , UpperCamelCase_ : Dict ) ... | 581 | 0 |
"""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_uti... | 104 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstri... | 104 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase = {}
try:
if not is_sentencepiece_available():
raise OptionalD... | 454 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowerCamelCase = logging.get_logger(__name__)
class _UpperCamelCase ( A ):
'''simple docstring'''
def __init__( self : Optional[int] , *_... | 454 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
lowerCAmelCase = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"... | 292 |
'''simple docstring'''
def lowerCamelCase_ ( __UpperCamelCase : int ) -> bool:
"""simple docstring"""
if num < 0:
return False
_A = num
_A = 0
while num > 0:
_A = rev_num * 1_0 + (num % 1_0)
... | 292 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE_ (UpperCamelCase , UpperCamelCase ) -> float:
lowerCamelCase__ : Union[str, Any] = u
for i in range(1 , UpperCamelCase ):
... | 631 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_t... | 631 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__A : Tuple = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
'KD 6S 9D TH AD... | 16 |
"""simple docstring"""
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,... | 674 | 0 |
'''simple docstring'''
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 data... | 513 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_util... | 513 | 1 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
a__ = False
class snake_case ( unittest.TestCase ):
... | 477 |
"""simple docstring"""
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
SCREAMING_SNAKE_CASE_ = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deform... | 465 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
__snake_case : Optional[int] = {
"configuration_sp... | 701 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Tuple = logging.get_logger(__name__)
__snake_case : int = {
"facebook/wav2vec2-base-960h": "https://huggingface.c... | 691 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datas... | 475 | """simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
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 Co... | 473 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable(... | 106 |
import math
import os
import sys
def _a ( SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
UpperCamelCase__ : Any = ''''''
try:
with open(SCREAMING_SNAKE_CASE , '''rb''' ) as binary_file:
UpperCamelCase__ : int = binary_file.read()
for... | 106 | 1 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 619 |
def lowerCamelCase__ ( __A :int ,__A :int ):
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
__snake_case = str(bin(__A ) )[2:] # remove the leading "0b"
__sna... | 268 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
__lowerCA... | 713 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team and The OpenBMB 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/l... | 396 | 0 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
__UpperCAmelCase = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""feature request""",
"""new model""",
"""wip""",
]
def __A ( ):
... | 379 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=lowercase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = ['''flax''']
def __init__( self : Optional[int] , *lowerCamelCase_ : An... | 379 | 1 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils im... | 423 |
def snake_case__ ( lowerCamelCase_ ):
A : Optional[Any] = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def snake_case__ ( lowerCamelCase_ ):
A : Optional[Any] = 0
while number > 0:
... | 423 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, ... | 633 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def _SCREAMING_SNAKE_CASE ( _lowercase : Tuple , _lowercase : float = 0.0 , _lowercase : float = 1.0 ) ->int:
'''simple docstring'''
return 1 / sqrt(... | 633 | 1 |
from random import randint
from tempfile import TemporaryFile
import numpy as np
def A ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Dict = 0
if start < end:
... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snake_case = logging.get_logger(__name__)
_snake_case = {
"microsoft/focalnet-tiny": "https://huggingface.co/microsof... | 658 | 0 |
'''simple docstring'''
import math
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
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 mult... | 565 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
_lowerCamelCase : int = {
'''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}
t... | 686 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, float... | 716 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a : List[str] = logging.get_logger(__name__)
_a : Any = {
"kssteven/ibe... | 10 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import f... | 360 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE: Optional[int] = {
'''configuration_roformer''': ... | 360 | 1 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 711 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prep... | 669 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, ... | 319 |
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_configuration_common im... | 319 | 1 |
from typing import List
import numpy as np
def lowerCAmelCase_ (_SCREAMING_SNAKE_CASE : dict ):
UpperCamelCase_ : Optional[Any] = {key: len(_SCREAMING_SNAKE_CASE ) for key, value in gen_kwargs.items() if isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )}
... | 717 | from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCamelCase ( ... | 138 | 0 |
def snake_case_ ( _SCREAMING_SNAKE_CASE ):
assert isinstance(__lowerCAmelCase , __lowerCAmelCase ), F"""The input value of [n={number}] is not an integer"""
if number == 1:
return 2
elif number < 1:
__lowercase = F"""The input value of [n={number}] has to be > 0"""
raise ValueEr... | 402 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
"htt... | 369 | 0 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def UpperCAmelCase_ ( _UpperCAmelCase ):
lowerCamelCase_: List[s... | 584 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase : Tuple = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",
"""Grou... | 584 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available... | 11 |
'''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,
BartFor... | 689 | 0 |
# 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
#
# Unless require... | 702 |
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase_ : List[Any] = '\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n'
UpperCAmelCase_ : Optional[Any] ... | 443 | 0 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
UpperCamelCase = 2_9979_2458
# Symbols
UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase = symbols('ct x y z')
def _A ( lowerCAmelCase_ : ... | 61 |
from __future__ import annotations
def _A ( lowerCAmelCase_ : list , lowerCAmelCase_ : int , lowerCAmelCase_ : int , lowerCAmelCase_ : int ):
"""simple docstring"""
lowerCAmelCase__ = []
lowerCAmelCase__ , lowerCAmelCas... | 61 | 1 |
'''simple docstring'''
from __future__ import annotations
def __lowercase (_lowercase ) -> List[str]:
"""simple docstring"""
__lowerCamelCase : Union[str, Any] = 2
__lowerCamelCase : Optional[int] = []
while i * i <= n:
if n ... | 714 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class SCREAMING_SNAKE_CASE ( metaclass=lowerCAmelCase_ ):
snake_case__ : Union[str, Any] = ['torch', 'torchsde']
def __init__( self : int , *A__ : Optional[Any] , **A__ ... | 483 | 0 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_a... | 410 |
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch... | 431 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowerCAmelCase ( unittest.TestCase ):
def a__ ( self ):
_A= inspect.getfile(accelerate.test_utils )
... | 701 | import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'''BridgeTower/bridgetower-base''': '''https://huggingface.co/BridgeTower/bridge... | 476 | 0 |
import baseaa
def _lowercase ( __UpperCamelCase : str ):
return baseaa.aaaencode(string.encode("""utf-8""" ) )
def _lowercase ( __UpperCamelCase : bytes ):
return baseaa.aaadecode(__UpperCamelCase ).decode("""utf-8""" )
if __name__ == "__main__":
... | 214 |
from math import ceil
def _lowercase ( __UpperCamelCase : int = 1001 ):
snake_case__ = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
snake_case__ = 2 * i + 1
snake_case__ = 2 * i
snake_case__ = tot... | 214 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCAmelCase : Any = logging.get_logger(__name__)
_UpperCAmelCase : Optional[Any] ... | 108 |
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class lowercase :
__SCREAMING_SNAKE_CASE : int
__SCREAMING_SNAKE_CASE : Node | None = None
__SC... | 108 | 1 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
SCREAMING_SNAKE_CASE :str = logging.getLo... | 55 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGEN... | 89 | 0 |
def __UpperCAmelCase( ):
_lowerCamelCase : int = []
_lowerCamelCase : Union[str, Any] = 1
while len(lowercase_ ) < 1e6:
constant.append(str(lowercase_ ) )
i += 1
_lowerCamelCase : str = ''''''.join(lo... | 613 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 1 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
class SCREAMING_SNAKE_CASE ( sn... | 225 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
lowerCAmelCase_ : Tuple = 'docs/source/en/_toctree.yml'
def UpperCAmelCase ( A : Union[str, Any] ):
SCREAMING_SNAKE_CASE : Dict = defaultdi... | 527 | 0 |
import gc
import threading
import time
import psutil
import torch
class __UpperCamelCase :
def __init__( self: List[Any] ):
'''simple docstring'''
__magic_name__ = psutil.Process()
__magic_name__ = False
def _SCREAMING_SNAKE_CASE ( ... | 704 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
@register_to_config
def __init__( self: Optional[Any] , *,
__UpperCamelCas... | 184 | 0 |
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