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 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 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 612 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ : Tuple =logging.get_logger(__name__)
lowerCAmelCase__ : str ={'vocab_file': 'vocab.json'}
lowerCAmelCase__ : ... | 101 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE=() ... | 102 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
"""simple docstring"""
import random
from typing import Any
def snake_case ( lowerCAmelCase_ ) -> list[Any]:
for _ in range(len(lowerCAmelCase_ ) ):
_snake_case = random.randint(0 , len(lowerCAmelCase_ ) - 1 )
_snake_case = random.randint(0 ... | 103 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def A_ ( a ) -> Union[str, Any]:
'''simple docstring'''
raise NotImplementedError()
... | 612 | 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.multicontrolnet import MultiControlNetModel # noqa: F... | 104 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 612 | 0 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase ( lowerCamelCase_ : Dict , lowerCamelCase_ : Any , lo... | 105 |
def __A(lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
_UpperCamelCase = str(lowerCAmelCase )
_UpperCamelCase = """""".join(sort... | 612 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 106 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowercase ):
UpperCamelCase_ : int = (KDPMaDiscreteScheduler,)
UpperCamelCase_ : Optional[int... | 612 | 0 |
'''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 ... | 107 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __A(lowerCAmelCase , lowerCAmelCase ) -> np.array:
"""simple docstring"""
_UpperCamelCase = F'{sampling_rate}'
_UpperCamelCase = """1"""
_UpperCam... | 612 | 0 |
from __future__ import annotations
from collections.abc import Iterator
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : Optional[Any] , lowerCamelCase : int ) -> None:
"""simple docstring"""
_UpperCAmelCase = va... | 108 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
a = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\n booktitle = \"Pro... | 109 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__magic_name__ : List[str] ={
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'Vi... | 664 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-ba... | 612 | 0 |
'''simple docstring'''
class __lowercase :
def __init__( self , UpperCamelCase ) -> None:
__a = len(UpperCamelCase )
__a = [0] * len_array
if len_array > 0:
__a = array[0]
for i in range... | 539 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
sk... | 612 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
_lowerCamelCase : Any = TypeVar("KT")
_lowerCamelCase : List[Any] = TypeVar("VT")
class SCREAMING_SNAKE_CASE ( Generic[KT, VT] ... | 430 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittest.TestCase ):
@pr... | 612 | 0 |
from collections import deque
from math import floor
from random import random
from time import time
class __A :
'''simple docstring'''
def __init__( self ):
_lowerCAmelCase : Any = {}
def SCREAMING_SNAKE_CASE__ ( self , _snake_case , _snake_case ... | 424 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 612 | 0 |
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import from_bytes, to_byt... | 385 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __A(lowerCAmelCase ) -> Dict:
"""simple docstring"""
_UpperCamelCase = os.path.join(args.tf_model_dir , """parameters.json""" )
_UpperCamelC... | 612 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSeqL... | 585 |
import warnings
from .generation import TFGenerationMixin
class lowerCAmelCase__ ( __lowercase ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transform... | 612 | 0 |
def _lowerCAmelCase ( A__ , A__ ):
lowercase__ = len(A__ )
lowercase__ = []
for i in range(len(A__ ) - pat_len + 1 ):
lowercase__ = True
for j in range(A__ ):
if s[i + j] != pattern[j]:
lowercase__... | 622 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 612 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ :Optional[int] = logging.get_logger(__name__)
UpperCamelCase__ :Optional[int] = {
"""facebook/s2t-small-librispeech-asr""": (
"""https://huggingface.co/faceboo... | 355 |
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,
)
from ... | 612 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCAmelCase_ ( ) -> Optional[int]:
a_ : Dict = ArgumentParser(
description=(
"... | 237 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impo... | 612 | 0 |
import math
def lowerCAmelCase ( UpperCamelCase__ : List[str] , UpperCamelCase__ : str ) -> Union[str, Any]:
"""simple docstring"""
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa... | 202 |
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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
IMA... | 612 | 0 |
"""simple docstring"""
from __future__ import annotations
_lowerCAmelCase = """#"""
class __UpperCamelCase :
def __init__( self ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = {}
def __lowerCamelCase ( self ... | 259 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("T")
lowerCamelCase__ = TypeVar("U")
class lowerCAmelCase__ ( Generic[T, U] ):
def __init__( self , a , a ) ... | 612 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Any =logging.get_logger(__name__)
__magic_name__ : Union[str, Any] ={
'huggingface/informer-tourism-monthly': (
'https://huggingfac... | 664 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@req... | 612 | 0 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_modul... | 539 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 612 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase : Any = {
"configuration_resnet": ["RESNET_PRETRAINE... | 430 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
import math
def UpperCamelCase_ ( lowerCAmelCase__ ):
"""simple docstring"""
_lowerCAmelCase : Optional[int] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowerCAmelCase__ )
def UpperCamelCase_ ( lowerC... | 424 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : Tuple = logging.get_logger(__name__)
__lowerCamelCase : str = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/gi... | 385 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def A_ ( a ) -> Union[str, Any]:
'''simple docstring'''
raise NotImplementedError()
... | 612 | 0 |
'''simple docstring'''
import numpy
# List of input, output pairs
__lowerCAmelCase = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
__lowerCAmelCase = (((515, 22, 13), 555), ((61, 35, 49), 150))
__lowerCAmelCase = [2, 4, 1, 5]
__lowe... | 585 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 612 | 0 |
def _lowerCAmelCase ( A__ , A__ ):
lowercase__ = int(A__ )
# Initialize Result
lowercase__ = []
# Traverse through all denomination
for denomination in reversed(A__ ):
# Find denominations
while int(A__ ) >= int(A__ ):
... | 622 |
def __A(lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
_UpperCamelCase = str(lowerCAmelCase )
_UpperCamelCase = """""".join(sort... | 612 | 0 |
"""simple docstring"""
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def A_ ( snake_case__ ) -> float:
return np.dot(snake_case__ , snake_case__ )
class A:
"""simple docstring"""
def __init__( s... | 355 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowercase ):
UpperCamelCase_ : int = (KDPMaDiscreteScheduler,)
UpperCamelCase_ : Optional[int... | 612 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE__ ) -> int:
if not nums:
return 0
a_ : Any = nums[0]
a_ : Optional[int] = 0
for num in nums[1:]:
a_ , a_ : Optional[int] = (
... | 237 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __A(lowerCAmelCase , lowerCAmelCase ) -> np.array:
"""simple docstring"""
_UpperCamelCase = F'{sampling_rate}'
_UpperCamelCase = """1"""
_UpperCam... | 612 | 0 |
import os
def lowerCAmelCase ( UpperCamelCase__ : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Any = len(grid[0] )
__SCREAMING_SNAKE_CASE: Any = len(UpperCamelCase__ )
__SCREAMING_SNAK... | 202 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_lowerCAmelCase = logging.get_logger(__name__)
class __UpperCamelCase ( __lowercas... | 259 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
'''simple docstring'''
__magic_name__ : Optional[int] =6_55_21
def __snake_case ( lowerCamelCase_ : Optional[Any] ):
'''simple docstring'''
__magic_name__ = 1
__magic_name__ = 0
for plain_chr in plain_text:
__magic_name__ = (a + ord(l... | 664 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-ba... | 612 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"tanreinama/GPTSAN-2.8B-spout_is_uniform": (
"https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_i... | 539 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
sk... | 612 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 430 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittest.TestCase ):
@pr... | 612 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
snake_case = {
"configuration_audio_spectrogram_transformer": [
"AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ASTConfig",
]
}
t... | 424 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 612 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 385 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __A(lowerCAmelCase ) -> Dict:
"""simple docstring"""
_UpperCamelCase = os.path.join(args.tf_model_dir , """parameters.json""" )
_UpperCamelC... | 612 | 0 |
'''simple docstring'''
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs('hub/hopper-medium-v2/unet/hor32', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/unet/hor128', exist_ok=True)
os.makedirs('hub/hopper-medium-v2/value_function', exist_ok=True)
def __SCREAMING_SNAKE_... | 585 |
import warnings
from .generation import TFGenerationMixin
class lowerCAmelCase__ ( __lowercase ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transform... | 612 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_bird i... | 622 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 612 | 0 |
"""simple docstring"""
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPP... | 355 |
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,
)
from ... | 612 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
SCREAMING_SNAKE_CAS... | 237 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impo... | 612 | 0 |
def lowerCAmelCase ( UpperCamelCase__ : str ) -> list:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Dict = int(UpperCamelCase__ )
if n_element < 1:
__SCREAMING_SNAKE_CASE: Any = ValueError('''a should be a positive number''... | 202 |
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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
IMA... | 612 | 0 |
"""simple docstring"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
_lowerCAmelCase = None
try:
import msvcrt
except ImportError:
_lowerCAmelCase = None
try:
import fcntl
except ImportError:
_lowerC... | 259 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("T")
lowerCamelCase__ = TypeVar("U")
class lowerCAmelCase__ ( Generic[T, U] ):
def __init__( self , a , a ) ... | 612 | 0 |
'''simple docstring'''
import inspect
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_config_docstrings.py
__magic_name__ : List[str] ='src/transformers'
# This ... | 664 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@req... | 612 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __lowercase ( metaclass=__lowercase ):
_a = ["onnx"]
def __init__( self , *UpperCamelCase , **UpperCamelCase ) -> List[str]:
requires_backends(s... | 539 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 612 | 0 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LI... | 430 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ ):
"""simple docstring"""
return [ord(lowerCAmelCase__ ) - 96 for elem in plain]
def UpperCamelCase_ ( lowerCAmelCase__ ):
"""simple docstring"""
return "".join(chr(elem + 9... | 424 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transform... | 385 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def A_ ( a ) -> Union[str, Any]:
'''simple docstring'''
raise NotImplementedError()
... | 612 | 0 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
_snake_case = len(_SCREAMING_SNAKE_CASE )
_snake_case = sum(_SCREAMING_SNAKE_CASE )
_snake_case = [[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n + 1 ):
... | 585 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 612 | 0 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
a__ : Opt... | 622 |
def __A(lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
_UpperCamelCase = str(lowerCAmelCase )
_UpperCamelCase = """""".join(sort... | 612 | 0 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax impo... | 355 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowercase ):
UpperCamelCase_ : int = (KDPMaDiscreteScheduler,)
UpperCamelCase_ : Optional[int... | 612 | 0 |
"""simple docstring"""
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_configurati... | 237 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __A(lowerCAmelCase , lowerCAmelCase ) -> np.array:
"""simple docstring"""
_UpperCamelCase = F'{sampling_rate}'
_UpperCamelCase = """1"""
_UpperCam... | 612 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
lowerCAmelCase : List[str] = logging.get_logger(__name__)
... | 202 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __... | 259 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
'''simple docstring'''
def __snake_case ( lowerCamelCase_ : List[Any] , lowerCamelCase_ : List[Any] ):
'''simple docstring'''
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk mod... | 664 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-ba... | 612 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e impo... | 539 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
sk... | 612 | 0 |
'''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, ... | 430 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittest.TestCase ):
@pr... | 612 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"kssteven/ibert-roberta-base": "https://huggingface.co/kssteven/... | 424 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 612 | 0 |
from ...configuration_utils import PretrainedConfig
__lowerCamelCase : str = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https://hugging... | 385 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __A(lowerCAmelCase ) -> Dict:
"""simple docstring"""
_UpperCamelCase = os.path.join(args.tf_model_dir , """parameters.json""" )
_UpperCamelC... | 612 | 0 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_comm... | 585 |
import warnings
from .generation import TFGenerationMixin
class lowerCAmelCase__ ( __lowercase ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transform... | 612 | 0 |
import unittest
from transformers import XLMConfig, 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... | 622 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 612 | 0 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
UpperCamelCase__ :Dict = """\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Sim... | 355 |
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,
)
from ... | 612 | 0 |
"""simple docstring"""
from math import pow, sqrt
def lowerCAmelCase_ ( *SCREAMING_SNAKE_CASE__ ) -> bool:
a_ : Union[str, Any] = len(SCREAMING_SNAKE_CASE__ ) > 0 and all(value > 0.0 for value in values )
return result
def lowerCAmelCase_ ( SCREAMI... | 237 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impo... | 612 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet imp... | 202 |
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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
IMA... | 612 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase = {"""configuration_fnet""": ["""FNET_PRE... | 259 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("T")
lowerCamelCase__ = TypeVar("U")
class lowerCAmelCase__ ( Generic[T, U] ):
def __init__( self , a , a ) ... | 612 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from tr... | 664 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@req... | 612 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokeni... | 539 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 612 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
_lowerCamelCase : List[Any] = {
"susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json"... | 430 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"google/mobilenet_v2_1.4_224": "h... | 424 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 385 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def A_ ( a ) -> Union[str, Any]:
'''simple docstring'''
raise NotImplementedError()
... | 612 | 0 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( __lowercase ):
'''simple docstring'''
lowerCAmelCase_ = (PNDMScheduler,)
lowerCAmelCase_ = (("num... | 585 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 612 | 0 |
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionScheduler
from ...utils... | 622 |
def __A(lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
_UpperCamelCase = str(lowerCAmelCase )
_UpperCamelCase = """""".join(sort... | 612 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase__ :List[str] = TypeVar("""T""")
UpperCamelCase__ :Union[str, Any] = TypeVar("""U""")
class A( Generic[T, U] ):
"""simple docstring"... | 355 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowercase ):
UpperCamelCase_ : int = (KDPMaDiscreteScheduler,)
UpperCamelCase_ : Optional[int... | 612 | 0 |
"""simple docstring"""
import fire
from utils import calculate_rouge, save_json
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__=None, **SCREAMING_SNAKE_CASE__ ) -> Any:
a_ : Any = [x.strip() for x in open(SCREAMING_SNAKE_CAS... | 237 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __A(lowerCAmelCase , lowerCAmelCase ) -> np.array:
"""simple docstring"""
_UpperCamelCase = F'{sampling_rate}'
_UpperCamelCase = """1"""
_UpperCam... | 612 | 0 |
lowerCAmelCase : Dict = """Alexander Joslin"""
import operator as op
from .stack import Stack
def lowerCAmelCase ( UpperCamelCase__ : str ) -> int:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: List[str] = {'''*''': op.mul, '''/''': op.... | 202 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = get_failure_array(_lowerCamelCase )
# 2) Step through text searching for pattern
_lo... | 259 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate... | 664 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-ba... | 612 | 0 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffusers imp... | 539 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
sk... | 612 | 0 |
'''simple docstring'''
import math
def __lowerCamelCase ( A__ ) -> list:
"""simple docstring"""
UpperCamelCase = [True] * n
UpperCamelCase = False
UpperCamelCase = False
UpperCamelCase ... | 430 |
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittest.TestCase ):
@pr... | 612 | 0 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import conv... | 424 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 612 | 0 |
import os
from collections.abc import Iterator
def A__ ( _a : Optional[int] = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(_a ):
snake_case__ : Any =[d for d in dir_names if d != """scripts""" and d[0] not in """._"""]... | 385 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __A(lowerCAmelCase ) -> Dict:
"""simple docstring"""
_UpperCamelCase = os.path.join(args.tf_model_dir , """parameters.json""" )
_UpperCamelC... | 612 | 0 |
'''simple docstring'''
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,
)
__lowerCAmelCase = {'configuration_mbart': ['MB... | 585 |
import warnings
from .generation import TFGenerationMixin
class lowerCAmelCase__ ( __lowercase ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be removed in Transform... | 612 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
a__ : str = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2s... | 622 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 612 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ :Optional[Any] = logging.get_logger(__name__)
UpperCamelCase__ :Union[str, Any] = {
"""google/canine-s""": """https://huggingface.co/google/canine-s/resolve/main/confi... | 355 |
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,
)
from ... | 612 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistepI... | 237 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers impo... | 612 | 0 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class a ( __lowercase ):
SCREAMING_SNAKE_CASE__ : Dict = ""
SCREAMING_SNAKE_CASE__ : str = (
Non... | 202 |
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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDARD_MEAN,
IMA... | 612 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils... | 259 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("T")
lowerCamelCase__ = TypeVar("U")
class lowerCAmelCase__ ( Generic[T, U] ):
def __init__( self , a , a ) ... | 612 | 0 |
'''simple docstring'''
__magic_name__ : List[Any] ='Input must be a string of 8 numbers plus letter'
__magic_name__ : Dict ='TRWAGMYFPDXBNJZSQVHLCKE'
def __snake_case ( lowerCamelCase_ : Any ):
'''simple docstring'''
if not isinstance(lowerCamelCase_ , lowerCamelCa... | 664 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@req... | 612 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transform... | 539 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 612 | 0 |
'''simple docstring'''
def __lowerCamelCase ( ) -> Tuple:
"""simple docstring"""
UpperCamelCase = 0
for i in range(1 , 1_001 ):
total += i**i
return str(A__ )[-10:]
if __name__ == "__main__":
print(solution()... | 430 |
from collections.abc import Sequence
def __A(lowerCAmelCase = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
_UpperCamelCase = nums[0]
for i in range(1 , len(lowerCAmelCase ) ):
_U... | 612 | 0 |
from __future__ import annotations
import requests
snake_case = set(
"approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories created_utc downs\nedited ... | 424 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
from PIL import Image
def A__ ( _a : Tuple , _a : Optional[Any] ):
'''simple docstring'''
snake_case__ : List[str] =(259 * (level + 255)) / (255 * (259 - level))
def contrast(_a : int ) -> int:
return int(128 + factor * (c - 128) ... | 385 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( __lowercase ):
@staticmethod
@abstractmethod
def A_ ( a ) -> Union[str, Any]:
'''simple docstring'''
raise NotImplementedError()
... | 612 | 0 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
... | 585 |
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_device
from transformers.ut... | 612 | 0 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import A... | 622 |
def __A(lowerCAmelCase ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
raise ValueError("""check_bouncy() accepts only integer arguments""" )
_UpperCamelCase = str(lowerCAmelCase )
_UpperCamelCase = """""".join(sort... | 612 | 0 |
"""simple docstring"""
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
UpperCamelCase__ :Optional[Any] = get_logger(__name__)
class A( enum.Enum ):
"""simple docstring"""
A = "all_check... | 355 |
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( __lowercase ):
UpperCamelCase_ : int = (KDPMaDiscreteScheduler,)
UpperCamelCase_ : Optional[int... | 612 | 0 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
SCREAMING_SNAKE_CASE_ = """us-east-1""" # defaults region
@dataclass
class snake_case_ :
__lowerCAmelCase = 42
__lowerCAmelCase = "arn:aws:iam::558105141721:role/sa... | 237 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def __A(lowerCAmelCase , lowerCAmelCase ) -> np.array:
"""simple docstring"""
_UpperCamelCase = F'{sampling_rate}'
_UpperCamelCase = """1"""
_UpperCam... | 612 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate... | 202 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 259 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSp... | 664 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"google/pix2struct-textcaps-base": (
"https://huggingface.co/google/pix2struct-textcaps-ba... | 612 | 0 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAIN... | 539 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
sk... | 612 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.