code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import 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 __snake_case ( lowerCAmelCase_ ) -> Optional[Any]:
SCREAMING_SNAKE_CASE__ = int(l... | 100 |
def __snake_case ( ) -> int:
return 1
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) +... | 100 | 1 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def __snake_case ( ) -> Union[str, Any]:
SCREAMING_SNAKE_CASE__ = ArgumentParser(
description=(
... | 100 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : List[str] = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 100 | 1 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformers.utils import log... | 100 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 | 1 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 100 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_A : Dict = get_tests_dir("""fixtures/test_sentencepiece_bpe.... | 100 | 1 |
from __future__ import annotations
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ ) -> list[tuple[int, int]]:
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = position
SCREAMING_SNAKE_CASE__ = [
(y + 1, x + 2),
(y - 1, x + ... | 100 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...... | 100 | 1 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
_A : Optional[int] = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input("""Search: """)))
pri... | 100 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __snake_case ( ) -> Any:
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 100 | 1 |
from __future__ import annotations
class __snake_case :
'''simple docstring'''
def __init__( self , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = order
# a_{0} ... a_{k}
SCREAMING_SNAKE_CASE__ = [1.0] + ... | 100 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 100 | 1 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKI... | 100 |
from torch import nn
def __snake_case ( lowerCAmelCase_ ) -> Tuple:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported acti... | 100 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : List[str] = 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... | 100 |
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.utils import logg... | 100 | 1 |
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 __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simpl... | 100 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCamelCase__ : ... | 100 | 1 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def __snake_case ( lowerCAmelCase_ ) -> Dict:
SCREAMING_SNAKE_CASE__ = {}
SCREAMING_SNAKE_CAS... | 100 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 100 | 1 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_=None , A_=None ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = data
SCREAMING_SNAKE_CASE__ = previous
SCREAMING_SNAKE_CASE__ ... | 100 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_A : Optional[int] = object()
# For specifying empty leaf dict `{}`
_A : Tuple = object()
def __snake_case... | 100 | 1 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __SCREAMING_SNAKE_CASE , unittest.TestC... | 100 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __SCREAMING_SNAKE_CASE , unittest.TestC... | 100 | 1 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def __snake_case ( lowerCAmelCase_ ) -> None:
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = analyze_text(lowerCAmelCase_ )
SCREAMING_SNAKE_CASE__... | 100 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Any = {"""configuration_xglm""": ["""XGLM_PRETRAINED_C... | 100 | 1 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAme... | 100 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from trans... | 100 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_A : Tuple = logging.get_logger(__name__)
_A : Optional[int... | 100 |
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 __snake_case ( lowerCAmelCase_ ) -> Optional[Any]:
SCREAMING_SN... | 100 | 1 |
import requests
_A : str = """YOUR API KEY"""
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ = giphy_api_key ) -> list:
SCREAMING_SNAKE_CASE__ = '''+'''.join(query.split() )
SCREAMING_SNAKE_CASE__ = f'''https://api.giphy.com/v1/gif... | 100 |
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:
from ..utils.dummy_pt_objects impo... | 100 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import Fla... | 100 |
import operator as op
def __snake_case ( lowerCAmelCase_ ) -> str:
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNAKE_CASE__ ... | 100 | 1 |
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.utils.testing_utils impor... | 100 |
import torch
from torch import nn
class __snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self , A_ , A_ , A_ , A_ , A_=1 , A_=False ):
'''simple docstring'''
super().__init__()
SCREAMING_SNAKE_CASE_... | 100 | 1 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 100 |
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 M... | 100 | 1 |
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCamelCase__ : str = ["""keras_nlp"""]
def __init__( self , *A_ , **A_ ):
'''simple docstring'''
... | 100 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 100 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequen... | 100 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_I... | 100 | 1 |
def __snake_case ( lowerCAmelCase_ = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
try:
SCREAMING_SNAKE_CASE__ = int(lowerCAmelCase_ )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <= 0:
raise V... | 100 |
def __snake_case ( ) -> int:
return 1
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) +... | 100 | 1 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_I... | 100 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : List[str] = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 100 | 1 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TOKEN, USER,... | 100 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 100 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_A : Dict = get_tests_dir("""fixtures/test_sentencepiece_bpe.... | 100 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_A : List[str] = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaC... | 100 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...... | 100 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_ten... | 100 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __snake_case ( ) -> Any:
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 100 | 1 |
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.utils import logg... | 100 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 100 | 1 |
_A : List[str] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_A : Optional[int] = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_A : int = {
0: """Sunday""",
1: """Monday""",
2: """Tuesday""",
3: """Wednesday""",
4: """Thursday""",
5: """Friday""",
6: """Saturday"""... | 100 |
from torch import nn
def __snake_case ( lowerCAmelCase_ ) -> Tuple:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported acti... | 100 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertConf... | 100 |
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.utils import logg... | 100 | 1 |
# 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 required by app... | 100 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCamelCase__ : ... | 100 | 1 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import ConfigTester... | 100 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 100 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : str = {
"""configuration_albert""": ["""ALBERT_PRE... | 100 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_A : Optional[int] = object()
# For specifying empty leaf dict `{}`
_A : Tuple = object()
def __snake_case... | 100 | 1 |
def __snake_case ( lowerCAmelCase_ ) -> bool:
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(lowerCAmelCase_ ) == 0:
raise ValueError('''Input list must be a non empty ... | 100 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __SCREAMING_SNAKE_CASE , unittest.TestC... | 100 | 1 |
import string
def __snake_case ( lowerCAmelCase_ ) -> str:
SCREAMING_SNAKE_CASE__ = ''''''
for i in sequence:
SCREAMING_SNAKE_CASE__ = ord(lowerCAmelCase_ )
if 6_5 <= extract <= 9_0:
output += chr(1_5_5 - extract )
elif ... | 100 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Any = {"""configuration_xglm""": ["""XGLM_PRETRAINED_C... | 100 | 1 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# sinc... | 100 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from trans... | 100 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils imp... | 100 |
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 __snake_case ( lowerCAmelCase_ ) -> Optional[Any]:
SCREAMING_SN... | 100 | 1 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_A : str = (
"""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... | 100 |
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:
from ..utils.dummy_pt_objects impo... | 100 | 1 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
_A... | 100 |
import operator as op
def __snake_case ( lowerCAmelCase_ ) -> str:
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNAKE_CASE__ ... | 100 | 1 |
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, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils import ... | 100 |
import torch
from torch import nn
class __snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self , A_ , A_ , A_ , A_ , A_=1 , A_=False ):
'''simple docstring'''
super().__init__()
SCREAMING_SNAKE_CASE_... | 100 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
_A : List[Any] = 6_37_81_37.0
_A : str = 6_35_67_52.31_42_45
_A : Union[str, Any] = 6_37_81_37
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_... | 100 |
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 M... | 100 | 1 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def __snake_case ( lowerCAmelCase_ ) -> List[Tuple[int, ...]]:
SCREAMIN... | 100 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 100 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Any = {"""configuration_xglm""": ["""XGLM_PRETRAINED_C... | 100 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_I... | 100 | 1 |
def __snake_case ( ) -> int:
return 1
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) +... | 100 |
def __snake_case ( ) -> int:
return 1
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) +... | 100 | 1 |
def __snake_case ( lowerCAmelCase_ ) -> str:
if number > 0:
raise ValueError('''input must be a negative integer''' )
SCREAMING_SNAKE_CASE__ = len(bin(lowerCAmelCase_ )[3:] )
SCREAMING_SNAKE_CASE__ = bin(abs(lowerCAmelCase_ ) - (1 << binary_numbe... | 100 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : List[str] = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 100 | 1 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..... | 100 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 | 1 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
FlaxForcedBOSToken... | 100 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_A : Dict = get_tests_dir("""fixtures/test_sentencepiece_bpe.... | 100 | 1 |
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
_A : Optional[int] = _sy... | 100 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...... | 100 | 1 |
from __future__ import annotations
from math import ceil, floor, sqrt
def __snake_case ( lowerCAmelCase_ = 2_0_0_0_0_0_0 ) -> int:
SCREAMING_SNAKE_CASE__ = [0]
SCREAMING_SNAKE_CASE__ = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ):
... | 100 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __snake_case ( ) -> Any:
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 100 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_A : Union[str, Any] = {
"""configuration_blip""": [
"""BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""... | 100 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 100 | 1 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import torch
from ..... | 100 |
from torch import nn
def __snake_case ( lowerCAmelCase_ ) -> Tuple:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported acti... | 100 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Tuple = logging.get_logger(__name__)
_A : int = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_is_uniform/resolve/main/config.json... | 100 |
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.utils import logg... | 100 | 1 |
def __snake_case ( lowerCAmelCase_ ) -> bool:
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''') )
def __snake_case ( lowerCAmelCase_ ) -> bool:
SCREAMING_SNAKE_CASE__ = credit_card_number
SCREAMI... | 100 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCamelCase__ : ... | 100 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : List[str] = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 100 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 100 | 1 |
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_A : Union[str, Any] = logging.get_logger(__name__)
_A : Optional[int] = {
"""nielsr/canine-s""": 20_48,
}
# Unicode defines 1,114,112 total “cod... | 100 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_A : Optional[int] = object()
# For specifying empty leaf dict `{}`
_A : Tuple = object()
def __snake_case... | 100 | 1 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_A : Dict = l... | 100 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __SCREAMING_SNAKE_CASE , unittest.TestC... | 100 | 1 |
import operator as op
def __snake_case ( lowerCAmelCase_ ) -> str:
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNAKE_CASE__ ... | 100 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Any = {"""configuration_xglm""": ["""XGLM_PRETRAINED_C... | 100 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFe... | 100 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from trans... | 100 | 1 |
from collections.abc import Callable
import numpy as np
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> np.array:
SCREAMING_SNAKE_CASE__ = int(np.ceil((x_end - xa) / step_size ) )
... | 100 |
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 __snake_case ( lowerCAmelCase_ ) -> Optional[Any]:
SCREAMING_SN... | 100 | 1 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Co... | 100 |
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:
from ..utils.dummy_pt_objects impo... | 100 | 1 |
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
from ... | 100 |
import operator as op
def __snake_case ( lowerCAmelCase_ ) -> str:
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNAKE_CASE__ ... | 100 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_A : str = {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoXConfig"""]}
try:
if not is_to... | 100 |
import torch
from torch import nn
class __snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self , A_ , A_ , A_ , A_ , A_=1 , A_=False ):
'''simple docstring'''
super().__init__()
SCREAMING_SNAKE_CASE_... | 100 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_A : List[str] = {
"""configuration_encodec""": [
"""ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""EncodecConfig""",
],
"""feature_extrac... | 100 |
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 M... | 100 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_A : Any = logging.get_logger(__name__)
_A : Union[str, Any] = {
"""microsoft/focalnet-tiny""": """htt... | 100 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 100 | 1 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 100 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_I... | 100 | 1 |
from __future__ import annotations
import requests
def __snake_case ( lowerCAmelCase_ ) -> dict:
SCREAMING_SNAKE_CASE__ = f'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty'''
return requests.get(lowerCAmelCase_ ).json()
def __snake_... | 100 |
def __snake_case ( ) -> int:
return 1
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) +... | 100 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 100 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : List[str] = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 100 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenization_c... | 100 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 | 1 |
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, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_available():
import torch
from... | 100 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_A : Dict = get_tests_dir("""fixtures/test_sentencepiece_bpe.... | 100 | 1 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 100 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...... | 100 | 1 |
_A : str = """0.18.2"""
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_available,
... | 100 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __snake_case ( ) -> Any:
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 100 | 1 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils im... | 100 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 100 | 1 |
from __future__ import annotations
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> int | float:
if len(lowerCAmelCase_ ) == 0:
raise ValueError('''find_max() arg is an empty sequence''' )
if (
left >= len(lowerCAmelCase_ )
... | 100 |
from torch import nn
def __snake_case ( lowerCAmelCase_ ) -> Tuple:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported acti... | 100 | 1 |
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class __snake_case ( unittest.Te... | 100 |
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.utils import logg... | 100 | 1 |
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.data import Dataset
from t... | 100 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCamelCase__ : ... | 100 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)
... | 100 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 100 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResa... | 100 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_A : Optional[int] = object()
# For specifying empty leaf dict `{}`
_A : Tuple = object()
def __snake_case... | 100 | 1 |
from __future__ import annotations
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> list:
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = input_list[low:mid], ... | 100 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __SCREAMING_SNAKE_CASE , unittest.TestC... | 100 | 1 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
_A : List[Any] = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Aror... | 100 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_A : Any = {"""configuration_xglm""": ["""XGLM_PRETRAINED_C... | 100 | 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
_A : Dict = logging.get_logger(__name__)
_A : Optional[int] = {
"""sail/pool... | 100 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from trans... | 100 | 1 |
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
from ...test_backbone_com... | 100 |
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 __snake_case ( lowerCAmelCase_ ) -> Optional[Any]:
SCREAMING_SN... | 100 | 1 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from trans... | 100 |
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:
from ..utils.dummy_pt_objects impo... | 100 | 1 |
def __snake_case ( lowerCAmelCase_ = 1_0_0_0 ) -> int:
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ = 1, 1
SCREAMING_SNAKE_CASE__ = []
for i in range(1 , n + 1 ):
SCREAMING_SNAKE_CASE__ = prev_numerator + 2 * prev_denomin... | 100 |
import operator as op
def __snake_case ( lowerCAmelCase_ ) -> str:
SCREAMING_SNAKE_CASE__ = []
SCREAMING_SNAKE_CASE__ = lambda lowerCAmelCase_ , lowerCAmelCase_ : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNAKE_CASE__ ... | 100 | 1 |
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
from ...test_... | 100 |
import torch
from torch import nn
class __snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self , A_ , A_ , A_ , A_ , A_=1 , A_=False ):
'''simple docstring'''
super().__init__()
SCREAMING_SNAKE_CASE_... | 100 | 1 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTokenizer
else:
_A... | 100 |
import unittest
from transformers import AutoTokenizer, FalconConfig, 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 M... | 100 | 1 |
import torch
from torch import nn
class __snake_case ( nn.Module ):
'''simple docstring'''
def __init__( self , A_ , A_ , A_ , A_ , A_=1 , A_=False ):
'''simple docstring'''
super().__init__()
SCREAMING_SNAKE_CASE_... | 100 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTes... | 100 | 1 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 100 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_I... | 100 | 1 |
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 100 |
def __snake_case ( ) -> int:
return 1
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __snake_case ( lowerCAmelCase_ ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) +... | 100 | 1 |
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_attention_mask
from ...test... | 100 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : List[str] = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvai... | 100 | 1 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from urll... | 100 |
class __snake_case :
'''simple docstring'''
def __init__( self , A_ , A_ , A_ ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = name
SCREAMING_SNAKE_CASE__ = value
SCREAMING_SNAKE_CASE__ = wei... | 100 | 1 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_availab... | 100 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_A : Dict = get_tests_dir("""fixtures/test_sentencepiece_bpe.... | 100 | 1 |
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 ModelTesterMixin, ids_tensor
... | 100 |
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ...... | 100 | 1 |
import qiskit
def __snake_case ( lowerCAmelCase_ = 2 ) -> qiskit.result.counts.Counts:
SCREAMING_SNAKE_CASE__ = qubits
# Using Aer's simulator
SCREAMING_SNAKE_CASE__ = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acti... | 100 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __snake_case ( ) -> Any:
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 100 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.p... | 100 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 100 | 1 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_A : Optional[int] = logging.get_logger(__name__)
_A : Any = {"""vocab_file""": """vocab.json""", """m... | 100 |
from torch import nn
def __snake_case ( lowerCAmelCase_ ) -> Tuple:
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported acti... | 100 | 1 |
# Function to print upper half of diamond (pyramid)
def __snake_case ( lowerCAmelCase_ ) -> List[Any]:
for i in range(0 , lowerCAmelCase_ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(''' ''' , end='''''' )
for _ in range(0 ... | 100 |
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.utils import logg... | 100 | 1 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Conf... | 100 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE )
class __snake_case ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowerCamelCase__ : ... | 100 | 1 |
import argparse
from collections import defaultdict
def __snake_case ( lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ) -> Optional[int]:
SCREAMING_SNAKE_CASE__ = f'''{file}_{class_name}_{test_name}'''
d... | 100 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 100 | 1 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __snake_case ( ) -> Any:
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
... | 100 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_A : Optional[int] = object()
# For specifying empty leaf dict `{}`
_A : Tuple = object()
def __snake_case... | 100 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.