code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowerCamelCase__ : str = TypeVar("KT")
lowerCamelCase__ : Union[str, Any] = TypeVar("VT")
class lowercase__( Generic[KT, VT] ):
'''simple doc... | 698 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
... | 698 | 1 |
"""simple docstring"""
lowerCamelCase__ : Tuple = {"a": ["c", "b"], "b": ["d", "e"], "c": [], "d": [], "e": []}
lowerCamelCase__ : List[Any] = ["a", "b", "c", "d", "e"]
def __A ( a_ : Dict , a_ : Any , a_ : List[Any] )-> str:
'''simple docs... | 698 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", ... | 698 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections import Counter
from random import random
class lowercase__:
'''simple docstring'''
def __init__( self :List[Any] ) -> Optional[Any]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : D... | 698 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn... | 698 | 1 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.j... | 698 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPR... | 698 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", ... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-bas... | 698 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
... | 698 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feature... | 698 | 1 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
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_... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : List[Any] = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-... | 698 | 1 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. 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... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/... | 698 | 1 |
"""simple docstring"""
from __future__ import annotations
def __A ( a_ : int | float | str , a_ : int | float | str )-> list[str]:
'''simple docstring'''
if nth_term == "":
return [""]
SCREAMING_SNAKE_CASE : str = int(a_ )
SCREAMING_SNAKE_CASE : ... | 698 |
"""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,
PNDMScheduler,
Stabl... | 698 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase__ : Dict = {
"weiweishi/roc-bert-base-zh": "https://huggingface.co/weiweishi/roc-bert... | 698 |
"""simple docstring"""
def __A ( a_ : list , a_ : int = 0 )-> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = length or len(a_ )
SCREAMING_SNAKE_CASE : List[Any] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:... | 698 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCamelCase__ : Dict = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 698 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( _UpperCAmelCa... | 698 | 1 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowerCamelCase__ : str = 50000
lowerCamelCase__ : List[Any] = 5000
lowerCamelCase__ , lowerCamelCase__ : Optional[int] = ... | 698 |
"""simple docstring"""
import qiskit
def __A ( a_ : int , a_ : int )-> qiskit.result.counts.Counts:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Union[str, Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q regist... | 698 | 1 |
"""simple docstring"""
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import Neste... | 698 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow... | 698 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenc... | 698 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 698 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Dict = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLIPCo... | 698 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Any =... | 698 | 1 |
"""simple docstring"""
def __A ( a_ : int )-> bool:
'''simple docstring'''
SCREAMING_SNAKE_CASE : List[str] = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : int = logging.get_logger(__name__)
lowerCamelCase__ : str = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main... | 698 | 1 |
"""simple docstring"""
from __future__ import annotations
class lowercase__:
'''simple docstring'''
def __init__( self :Optional[Any] , lowerCamelCase_ :int = 0 ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Optional[int] = key
... | 698 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def __A ( a_ : Dict , a_ : int , a_ : str , a_ : Optional[Any]=None )-> List[Any]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Optional[Any] = (path or []) + [u]
for v in gr... | 698 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Any = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
"huggingface/informer-tourism-monthly... | 698 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeni... | 698 | 1 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase__( _UpperCAmelCase ):
'''simple docstring'''
def __lowerCAmelCase ( self :Union[str, Any] ) -> str:
'''simple doc... | 698 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase__( _UpperCAmelCase ):
'''simple docstring'''
def __lowerCAmelCase ( self :Union[str, Any] ) -> str:
'''simple doc... | 698 | 1 |
"""simple docstring"""
def __A ( a_ : list , a_ : int = 0 )-> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = length or len(a_ )
SCREAMING_SNAKE_CASE : List[Any] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:... | 698 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def __A ( a_ : Callable[[int | float], int | float] , a_ : int | float , a_ : int | float , a_ : int = 1_00 , )-> float:
'''simple docstring'''
SCREAMIN... | 698 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTest... | 698 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 698 | 1 |
"""simple docstring"""
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,
... | 698 |
"""simple docstring"""
def __A ( a_ : int = 10 , a_ : int = 10_00 , a_ : bool = True )-> int:
'''simple docstring'''
assert (
isinstance(a_ , a_ )
and isinstance(a_ , a_ )
and isinstance(a_ , a_ )
), "Invalid type of value(s) specified to funct... | 698 | 1 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
lowerCamelCase__ : Any = True
except (ImportError, ModuleNotFoundError):
lowerCamelCase__ : str = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.do... | 698 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
... | 698 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def __A ( a_ : np.ndarray , a_ : np.ndarray )-> float:
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(a_ , a_ ) ) )
... | 698 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", ... | 698 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokeni... | 698 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn... | 698 | 1 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeature... | 698 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPR... | 698 | 1 |
"""simple docstring"""
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_va... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-bas... | 698 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase__( _UpperCAmelCase , unitte... | 698 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feature... | 698 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class ... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : List[Any] = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-... | 698 | 1 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/... | 698 | 1 |
"""simple docstring"""
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optim... | 698 |
"""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,
PNDMScheduler,
Stabl... | 698 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase__ : Optional[Any] = ... | 698 |
"""simple docstring"""
def __A ( a_ : list , a_ : int = 0 )-> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = length or len(a_ )
SCREAMING_SNAKE_CASE : List[Any] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:... | 698 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase__( metaclass=_UpperCAmelCase ):
'''simple docstring'''
UpperCamelCase = ["""transformers""", """torch""", """note_seq"""]
def __init__( self :List[str] , *lowerCamelCase_ :int , **l... | 698 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( _UpperCAmelCa... | 698 | 1 |
"""simple docstring"""
import os
def __A ( )-> str:
'''simple docstring'''
with open(os.path.dirname(a_ ) + '''/grid.txt''' ) as f:
SCREAMING_SNAKE_CASE : Union[str, Any] = [] # noqa: E741
for _ in range(20 ):
l.append([int(a_ ) for x in f.readline().split... | 698 |
"""simple docstring"""
import qiskit
def __A ( a_ : int , a_ : int )-> qiskit.result.counts.Counts:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Union[str, Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q regist... | 698 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : List[str] = {
"configuration_graphormer": ["GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "GraphormerConfi... | 698 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow... | 698 | 1 |
"""simple docstring"""
import cmath
import math
def __A ( a_ : float , a_ : float , a_ : float , a_ : float )-> complex:
'''simple docstring'''
SCREAMING_SNAKE_CASE : str = math.radians(a_ )
SCREAMING_SNAKE_CASE : Union[str, Any] = ... | 698 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 698 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def __A ( a_ : float , a_ : int )-> float:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = u
for i in range(1 , a_ ):
SCREAMING_SNAKE_CASE : List[Any] = temp * (u - ... | 698 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Any =... | 698 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowerCamelCase__ : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase__ : ... | 698 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : int = logging.get_logger(__name__)
lowerCamelCase__ : str = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main... | 698 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction... | 698 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def __A ( a_ : Dict , a_ : int , a_ : str , a_ : Optional[Any]=None )-> List[Any]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Optional[Any] = (path or []) + [u]
for v in gr... | 698 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Dict = logging.get_logger(__name__)
lowerCamelCase__ : str = {
"microsoft/swinv2-tiny-patch4-window8-256": (
"https://huggingface.co/micros... | 698 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeni... | 698 | 1 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import P... | 0 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase__( _UpperCAmelCase ):
'''simple docstring'''
def __lowerCAmelCase ( self :Union[str, Any] ) -> str:
'''simple doc... | 698 | 0 |
from __future__ import annotations
from collections import namedtuple
def _A ( _lowercase , _lowercase , _lowercase ) -> tuple:
"""simple docstring"""
__UpperCamelCase = namedtuple('result' , 'name value' )
if (voltage, current, power).count(0 ) !... | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def __A ( a_ : Callable[[int | float], int | float] , a_ : int | float , a_ : int | float , a_ : int = 1_00 , )-> float:
'''simple docstring'''
SCREAMIN... | 698 | 0 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
UpperCAmelCase_ = Path(__file__).resolve().parents[3] / """src"""
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io ... | 2 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 698 | 0 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
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 ..pipeli... | 3 |
"""simple docstring"""
def __A ( a_ : int = 10 , a_ : int = 10_00 , a_ : bool = True )-> int:
'''simple docstring'''
assert (
isinstance(a_ , a_ )
and isinstance(a_ , a_ )
and isinstance(a_ , a_ )
), "Invalid type of value(s) specified to funct... | 698 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase : List[Any] = logging.get_logger(__name__)
__UpperCamelCase : List[str] = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ous... | 4 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
... | 698 | 0 |
'''simple docstring'''
from math import factorial
_lowercase = {str(d): factorial(d) for d in range(10)}
def A (__lowerCamelCase :int ):
return sum(DIGIT_FACTORIAL[d] for d in str(__lowerCamelCase ) )
def A ():
_lowerCAmelCase = 7 * factorial(9 ) + 1
... | 5 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", ... | 698 | 0 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 6 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn... | 698 | 0 |
"""simple docstring"""
a = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(100_000)]
def _snake_case ( _snake_case : int ) -> int:
'''simple docstring'''
_A = 0
while number:
# Increased Speed Slightly by checking every... | 7 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPR... | 698 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : int = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig... | 8 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-bas... | 698 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageResamp... | 9 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feature... | 698 | 0 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
Aut... | 10 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : List[Any] = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-... | 698 | 0 |
'''simple docstring'''
def lowerCAmelCase (__A):
"""simple docstring"""
for i in range(len(__A) - 1 , 0 , -1):
_a = False
for j in range(__A , 0 , -1):
if unsorted[j] < unsorted[j - 1]:
_a ... | 11 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/... | 698 | 0 |
def UpperCamelCase ( lowercase_ , lowercase_ , lowercase_ , lowercase_ ) -> List[str]:
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
lowercase__ : str = mf_knapsack(i - 1 , lowercase_ , ... | 12 |
"""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,
PNDMScheduler,
Stabl... | 698 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
A__ : Any = logging.get_logger(__name__) # pylint: disable=invalid-name
def U... | 13 |
"""simple docstring"""
def __A ( a_ : list , a_ : int = 0 )-> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = length or len(a_ )
SCREAMING_SNAKE_CASE : List[Any] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:... | 698 | 0 |
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 im... | 14 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( _UpperCAmelCa... | 698 | 0 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class A :
'''simple docstring'''
A__ = None
A__ = False
A__ = False
A__ = False
A__ = ... | 15 |
"""simple docstring"""
import qiskit
def __A ( a_ : int , a_ : int )-> qiskit.result.counts.Counts:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Union[str, Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q regist... | 698 | 0 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__A : Optional[Any] = ... | 16 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow... | 698 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ : List[str] = logging.get_logger(__name__)
UpperCAmelCase_ : List[Any] = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sense... | 17 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 698 | 0 |
'''simple docstring'''
import math
class lowerCAmelCase_ :
def __init__( self , _lowerCAmelCase=0 ) -> str: # a graph with Node 0,1,...,N-1
_lowerCAmelCase = n
_lowerCAmelCase = [
[math.inf for j in range(0 , _lowerCAmelCase )] for ... | 18 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Any =... | 698 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
... | 19 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : int = logging.get_logger(__name__)
lowerCamelCase__ : str = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main... | 698 | 0 |
import argparse
from collections import defaultdict
def _lowercase( __a : Union[str, Any] , __a : Dict , __a : Union[str, Any] , __a : Optional[int] , __a : Optional[int] ):
a__ =f"""{file}_{class_name}_{test_name}"""
... | 20 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def __A ( a_ : Dict , a_ : int , a_ : str , a_ : Optional[Any]=None )-> List[Any]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Optional[Any] = (path or []) + [u]
for v in gr... | 698 | 0 |
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
UpperCAmelCase_ : List[str] = "sr... | 21 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeni... | 698 | 0 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class A ( unittest.TestCase ):
def __lowerCAmelCase ( self : Union[str, Any] ) -> int:
"""simple docstring"""
_a... | 22 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase__( _UpperCAmelCase ):
'''simple docstring'''
def __lowerCAmelCase ( self :Union[str, Any] ) -> str:
'''simple doc... | 698 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class _a ( UpperCAmelCase__ ):
"""simple docstring"""
def __init__( self , _UpperCAmelCase , _UpperCAmelCase , _UpperCAme... | 23 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def __A ( a_ : Callable[[int | float], int | float] , a_ : int | float , a_ : int | float , a_ : int = 1_00 , )-> float:
'''simple docstring'''
SCREAMIN... | 698 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ : List[str] = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'... | 24 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 698 | 0 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_timm... | 25 |
"""simple docstring"""
def __A ( a_ : int = 10 , a_ : int = 10_00 , a_ : bool = True )-> int:
'''simple docstring'''
assert (
isinstance(a_ , a_ )
and isinstance(a_ , a_ )
and isinstance(a_ , a_ )
), "Invalid type of value(s) specified to funct... | 698 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCamelCase = {"configuration_reformer": ["REFORM... | 26 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
... | 698 | 0 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from f... | 27 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", ... | 698 | 0 |
'''simple docstring'''
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 ... | 28 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn... | 698 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ ,lowerCAmelCase__ ):
return int((input_a, input_a).count(0 ) == 0 )
def lowercase ( ):
assert and_gate(0 ,0 ) == 0
assert and_gate(0 ,1 ) == 0
assert and_gate(1 ,0 ) == 0
assert and_gate(1 ,1 )... | 29 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPR... | 698 | 0 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import logging... | 30 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-bas... | 698 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Dict = {
'roberta... | 31 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feature... | 698 | 0 |
import unittest
from transformers import 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 ModelTesterMixin, ids_tensor
f... | 32 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : List[Any] = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-... | 698 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available()... | 33 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/... | 698 | 0 |
"""simple docstring"""
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
fro... | 34 |
"""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,
PNDMScheduler,
Stabl... | 698 | 0 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
a_ :Any = TypeVar('T')
class lowercase ( Generic[T] ):
def __init__( self : ... | 35 |
"""simple docstring"""
def __A ( a_ : list , a_ : int = 0 )-> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = length or len(a_ )
SCREAMING_SNAKE_CASE : List[Any] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:... | 698 | 0 |
import os
from datetime import datetime as dt
from github import Github
__lowercase : List[str] = [
'''good first issue''',
'''feature request''',
'''wip''',
]
def lowercase ( ) -> Any:
'''simple docstring'''
snake_case : List[str] = ... | 36 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( _UpperCAmelCa... | 698 | 0 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
loggin... | 37 |
"""simple docstring"""
import qiskit
def __A ( a_ : int , a_ : int )-> qiskit.result.counts.Counts:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Union[str, Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q regist... | 698 | 0 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version imp... | 38 |
"""simple docstring"""
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow... | 698 | 0 |
from __future__ import annotations
from collections import deque
class snake_case_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _UpperCamelCase : list[str] ) ->Optional[int]:
snake_case_ = []
self.ad... | 39 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMo... | 698 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMode... | 40 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Any =... | 698 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.util... | 41 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : int = logging.get_logger(__name__)
lowerCamelCase__ : str = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main... | 698 | 0 |
'''simple docstring'''
import math
class UpperCAmelCase :
'''simple docstring'''
def UpperCamelCase( self , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> int:
'''simple docstring'''
lowerCamelCase_ = 0.0
lowerCamelCase_ = 0... | 42 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def __A ( a_ : Dict , a_ : int , a_ : str , a_ : Optional[Any]=None )-> List[Any]:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Optional[Any] = (path or []) + [u]
for v in gr... | 698 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
def is_in_circle(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> bool:
lowercase__ = sqrt((x*... | 43 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeni... | 698 | 0 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline #... | 44 |
"""simple docstring"""
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class lowercase__( _UpperCAmelCase ):
'''simple docstring'''
def __lowerCAmelCase ( self :Union[str, Any] ) -> str:
'''simple doc... | 698 | 0 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowercase ):
"""simple docstring"""
... | 45 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def __A ( a_ : Callable[[int | float], int | float] , a_ : int | float , a_ : int | float , a_ : int = 1_00 , )-> float:
'''simple docstring'''
SCREAMIN... | 698 | 0 |
"""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 (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
Condi... | 46 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 698 | 0 |
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_available, log... | 47 |
"""simple docstring"""
def __A ( a_ : int = 10 , a_ : int = 10_00 , a_ : bool = True )-> int:
'''simple docstring'''
assert (
isinstance(a_ , a_ )
and isinstance(a_ , a_ )
and isinstance(a_ , a_ )
), "Invalid type of value(s) specified to funct... | 698 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
UpperCAmelCase__ : str = logging.get_logg... | 48 |
"""simple docstring"""
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
... | 698 | 0 |
"""simple docstring"""
_lowercase : int = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
_lowercase : List[str] = [{'type': 'co... | 49 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", ... | 698 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_commo... | 50 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn... | 698 | 0 |
'''simple docstring'''
from __future__ import annotations
a__ : Union[str, Any] = 'Muhammad Umer Farooq'
a__ : Dict = 'MIT'
a__ : Optional[Any] = '1.0.0'
a__ : Tuple = 'Muhammad Umer Farooq'
a__ : Any ... | 51 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPR... | 698 | 0 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
A = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
author = "Snover, Matthew ... | 52 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-bas... | 698 | 0 |
import numpy
# List of input, output pairs
_snake_case : Optional[int] = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
_snake_case : List[str] = (((515, 22, 13), 555), ((61, 35, 49), 150))
_snake_case :... | 53 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_feature... | 698 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class A ( __lowercase ):
_snake_case ... | 54 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : List[Any] = {
"uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-... | 698 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE :int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE :str = {
'camembert-base... | 55 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/... | 698 | 0 |
'''simple docstring'''
# 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... | 56 |
"""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,
PNDMScheduler,
Stabl... | 698 | 0 |
from __future__ import annotations
class _lowerCAmelCase:
"""simple docstring"""
def __init__( self , _lowerCamelCase ):
UpperCamelCase_: Union[str, Any] = order
# a_{0} ... a_{k}
UpperCamelC... | 57 |
"""simple docstring"""
def __A ( a_ : list , a_ : int = 0 )-> list:
'''simple docstring'''
SCREAMING_SNAKE_CASE : int = length or len(a_ )
SCREAMING_SNAKE_CASE : List[Any] = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:... | 698 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__lowerCAmelCase : Union[str, Any] ... | 58 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase__( _UpperCAmelCa... | 698 | 0 |
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_bart import BartTokenizer
__A ... | 59 |
"""simple docstring"""
import qiskit
def __A ( a_ : int , a_ : int )-> qiskit.result.counts.Counts:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Union[str, Any] = qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q regist... | 698 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.