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 copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase )
class lowerCamelCase_ ( lowerCamelCase ):
a__ = field(default='''audio-classi... | 0 |
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 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = '''▁'''
__snake_case = {'''vocab_file''': '''spiece.m... | 1 |
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 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin... | 2 |
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 |
'''simple docstring'''
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
lowerCAmelCase : Optional[Any] = re.compile(r'^(?P<major>\d+)' r'\.(?P<minor>\d+)' r'\.(?P<patch>\d+)$')
@to... | 3 |
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 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__UpperCamelCase : Optional[Any] = {
'''configuration_falcon''': ['''FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FalconConfig''... | 4 |
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 functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
"""microsoft/wavlm-base""": """https://huggingface.co/microsoft/wavlm-base/resolve/mai... | 5 |
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
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "encoder-decoder"
lowerCamelCase_ = ... | 6 |
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 typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
a = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailabl... | 7 |
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 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 .tokeniz... | 8 |
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 argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import AutoC... | 9 |
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 |
# 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: F401
from ..controlnet.pipeline_controlnet import ... | 10 |
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'''
def lowerCAmelCase (__A , __A):
"""simple docstring"""
while a != 0:
_a , _a = b % a, a
return b
def lowerCAmelCase (__A , __A):
"""simple docstring"""
if gcd(__A , __A) != 1:
... | 11 |
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 |
def UpperCamelCase ( lowercase_ ) -> list:
'''simple docstring'''
for i in range(len(lowercase_ ) - 1 , 0 , -1 ):
lowercase__ : Union[str, Any] = False
for j in range(lowercase_ , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
lower... | 12 |
# 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 decimal import Decimal, getcontext
from math import ceil, factorial
def UpperCAmelCase__ ( UpperCAmelCase_ : int ) -> str:
if not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise TypeError('Undefined for non-integers' ... | 13 |
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 pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __UpperCAmelCase ( __a : str ,__a : Optional[int] ... | 14 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import require_elast... | 15 |
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 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
... | 16 |
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 pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def __SCREAMING_SNAKE_CASE ( a__ : Optional[int] ) -> int:
monkeypatch.setattr("""datasets.utils.deprecation_utils._emitted_deprecation_warnings""" ,set() )
@pytest.fixture
def ... | 17 |
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 ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class lowerCAmelCase_ ( __magic_name__... | 18 |
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 baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class _UpperCAmelCase:
def __init__( self , __a) -> Optional[int]:
... | 19 |
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 unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import to... | 20 |
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 |
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.num... | 21 |
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'''
class A :
def __init__( self : int , lowerCAmelCase_ : Union[str, Any] , lowerCAmelCase_ : Dict , lowerCAmelCase_ : List[str] ) -> Dict:
"""simple docstring"""
... | 22 |
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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
snake_case__ : Tuple = {
"""configuration_audio_spectrogram_transformer""": [
"""AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CO... | 23 |
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 unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.util... | 24 |
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 math
def lowerCamelCase__ ( _a = 100):
SCREAMING_SNAKE_CASE : Tuple = sum(i * i for i in range(1 , n + 1))
SCREAMING_SNAKE_CASE : Optional[int] = int(math.pow(sum(range(1 , n + 1)) , 2))
return square_of_sum - sum_of_squares
if __name__ == "_... | 25 |
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 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from .... | 26 |
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 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class lowerCamelCase( __snake_case ):
'''simple docstring'''
__magic_name__ = ''
__magic_name__ = ... | 27 |
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 |
'''simple docstring'''
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transf... | 28 |
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
A_ = logging.get_logger(__name__)
A_ = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/decision-transformer-gym-hopper-m... | 29 |
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 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
__a = {
'configuration_ernie': ['ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ErnieConfig', 'ErnieOnnxConfig'],
}
try:
if not is_torch_available(... | 30 |
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 UpperCAmelCase_ ( ) -> Tuple:
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def UpperCAmelCase_ ( __UpperCAmelCase : Union[str, Any] ) -> Union[str, Any]:
SCREAMING_SNAKE_CASE_ = 1
SCREAMING_SNAKE_CASE_ = ... | 31 |
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 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"facebook/lev... | 32 |
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 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class __magic_name__ (yaml.SafeLoader ):
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( self:Union[str, Any] , _a:List[str] ):
snake_cas... | 33 |
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 inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTe... | 34 |
# 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 |
from collections import Counter
from timeit import timeit
def a ( A__ = "" , ) -> bool:
'''simple docstring'''
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def a ( A__ = "" ) -> b... | 35 |
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 ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowercase : Dict = logging.get_logger(__name__)
__lowercase : Tuple = {
'''shi-labs/nat-mini-in1k-... | 36 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class A__ ( A__ ):
"""simple docstring"""
_lowercase = (PNDMScheduler,)
_lowercase = (('num_inference_steps', 5_0),)
def _UpperCamelCase( self : int ,... | 37 |
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 logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
A_ : Dict = logging.getLogger(__name__)
if is_torch_tpu_ava... | 38 |
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 logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelF... | 39 |
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 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
__Up... | 40 |
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 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_module, resolve_trus... | 41 |
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 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from tra... | 42 |
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 |
def _a ( SCREAMING_SNAKE_CASE ):
"""simple docstring"""
if number < 0:
raise ValueError('''number must not be negative''' )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 43 |
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 math import sqrt
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
assert isinstance(_lowerCAmelCase , _lowerCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
_lowerCamelCas... | 44 |
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 |
def A ( lowercase__ : int , lowercase__ : float , lowercase__ : float ) -> float:
return round(float(moles / volume ) * nfactor )
def A ( lowercase__ : float , lowercase__ : float , lowercase__ : float ) -> float:
return round(float((moles * 0.0821 * temperature) / (... | 45 |
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 typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
... | 46 |
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 math
import tensorflow as tf
from packaging import version
def UpperCAmelCase__ ( lowerCamelCase_ : Tuple ):
__a : Any = tf.convert_to_tensor(lowerCamelCase_ )
__a : Any = 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sqrt(... | 47 |
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 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase__ : List[str] = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
raise... | 48 |
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 numpy as np
import datasets
_lowercase : Tuple = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the E... | 49 |
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 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffuser... | 50 |
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'''
def __snake_case ( SCREAMING_SNAKE_CASE_ : int = 1_000_000 ) -> int:
"""simple docstring"""
UpperCAmelCase = set(range(3 , SCREAMING_SNAKE_CASE_ , 2 ) )
primes.add(2 )
for p in range(3 , SCREAMING_SNAKE_CASE_ , 2 ):
... | 51 |
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 typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
A = {
'''configuration_perceiver''': ['''PERCEIVER_PRETR... | 52 |
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 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if i... | 53 |
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 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__lowercase : Optional[Any] =TypeVar("""T""")
class A ( Generic[T] ):
def __init__( self: List[Any] , _lowerCAmelCase: T ) -> Unio... | 54 |
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 |
from __future__ import annotations
import math
import random
from typing import Any
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : Tuple ):
__A = []
__A = 0
__A = 0
def UpperCamelCase_ ( self : Li... | 55 |
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 is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
... | 56 |
# 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 |
from __future__ import annotations
def snake_case (UpperCAmelCase__ ) -> float:
UpperCamelCase_: Optional[Any] = 0.00
UpperCamelCase_: List[Any] = 0
for resistor in resistors:
if resistor <= 0:
UpperCamelCase_: Union[str, Any] ... | 57 |
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"""
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... | 58 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def lowerCAmelCase_ ( __a , __a ) -> Any:
"""simple docstring"""
lowerCamelCase__: Dict =k_si... | 59 |
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 |
import math
import sys
def lowerCamelCase_ ( _UpperCamelCase ) -> str:
"""simple docstring"""
snake_case_ : Any = ''''''
try:
with open(_UpperCamelCase , '''rb''' ) as binary_file:
snake_case_ : Dict ... | 60 |
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 collections.abc import Callable
def _A ( lowerCAmelCase_ : Callable[[float], float] , lowerCAmelCase_ : float , lowerCAmelCase_ : float ):
"""simple docstring"""
lowerCAmelCase__ = a
lowerCAmelCase__ = b
if funct... | 61 |
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 |
import argparse
import struct
import unittest
class SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self : int , UpperCAmelCase_ : bytes ):
SCREAMING_SNAKE_CASE : Dict = data
# Initialize hash values
... | 62 |
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 |
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 ConfigTester
from ...test_modeling... | 63 |
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 subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class _lowerCamelCase ( UpperCamelCase_ ):
@require_torch
def UpperCamelCase_ ( self ) -> Any:
# this tes... | 64 |
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
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simp... | 65 |
from __future__ import annotations
def __A(lowerCAmelCase , lowerCAmelCase ) -> list[list[int]]:
"""simple docstring"""
_UpperCamelCase = []
_UpperCamelCase = []
_UpperCamelCase = 0
_UpperCamelCase = sum(lowerCAmelCase )
create_st... | 612 | 0 |
from math import isqrt
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(SCREAMING_SNAKE_CASE ) + 1 ) )
def __magic_name__ ( SCREAMING_SNAKE_CASE = 10**6 ) -> int:
_lowerc... | 66 |
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 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
... | 67 |
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 |
from __future__ import annotations
def lowercase__ ( A_: list[int] , A_: list[int] , A_: list[int] , A_: list[list[str]] , A_: int , ) -> None:
"""simple docstring"""
__UpperCAmelCase =len(A_ )
... | 68 |
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 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
a : Union[str, Any] = logging.get_logger(__name__)
def __UpperCAmelCase ( _UpperCAmelCase : int , _UpperCAm... | 69 |
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 gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils im... | 70 |
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'''
def a__ ( _SCREAMING_SNAKE_CASE : Any , _SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_SNAKE_CASE : Union[str, Any] ) -> List[str]:
"""simple docstring"""
if n == 0:
return 1
elif n % 2 == 1:
return (binary_expone... | 71 |
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 |
'''simple docstring'''
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_F... | 72 |
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 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class _snake_case ( unittest.TestCase ):
def SCREAMING_SNAKE_CASE__ ( self) -> Optional[Any]:
SCREA... | 73 |
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 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...t... | 74 |
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 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_tor... | 75 |
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 os
import sys
a_ = os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
Au... | 76 |
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 __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
A = TypeVar("""T""")
class a__ ( Generic[T] ):
lowercase_ = 42 # Cache store of keys
lowercase_ = 42 # References of the keys in c... | 77 |
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'''
SCREAMING_SNAKE_CASE_: List[str] ={
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', '... | 78 |
# 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 subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class UpperCAmelCase_ ( __lowerCamelCase ):
@require_torch
def __UpperCAmelCase ( sel... | 79 |
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 numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__UpperCamelCase : Optional[int] = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Version("""3.6.4"""):
from nltk import word_t... | 80 |
from __future__ import annotations
lowerCamelCase__ = "#"
class lowerCAmelCase__ :
def __init__( self ) -> None:
'''simple docstring'''
_UpperCamelCase = {}
def A_ ( self , a ) -> None:
''... | 612 | 0 |
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case : Dict = logging.get_logger(__name__)
_snake_case : Optional[Any] = {
"vocab_file": "vo... | 81 |
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 flax.linen as nn
import jax
import jax.numpy as jnp
class lowercase__ ( nn.Module ):
'''simple docstring'''
UpperCamelCase = 42
UpperCamelCase = jnp.floataa
def lowercase__ ( self : Uni... | 82 |
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 |
"""simple docstring"""
def snake_case_ ( A_ : int, A_ : list ):
'''simple docstring'''
_enforce_args(A_, A_ )
if n == 0:
return 0
_lowerCamelCase : Tuple = float('''-inf''' )
for i in range(1, ... | 83 |
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 |
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = '''▁'''
UpperCAmelCase = {'''... | 84 |
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 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class snake_case ... | 85 |
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
from collections.abc import Iterator
from itertools import takewhile
def __snake_case ( __UpperCamelCase : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 86 |
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 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class UpperCamelCase_ ( enum.Enum ):
... | 87 |
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 datasets
from .evaluate import evaluate
UpperCAmelCase = """\
@inproceedings{Rajpurkar2016SQuAD10,
title={SQuAD: 100, 000+ Questions for Machine Comprehension of Text},
author={Pranav Rajpurkar and Jian Zhang and Konstantin Lopyrev and Percy Liang},
booktitle={... | 88 |
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 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class _lowerCamelCase( unittest.TestCase ):
def UpperCamelCase ( ... | 89 |
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 shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import... | 90 |
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 |
"""simple docstring"""
from copy import deepcopy
class lowerCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[Any] ,A_ : list[int] | None = None ,A_ : int | None = None ) -> None:
if arr is None and size is not None:
A = size
... | 91 |
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 |
'''simple docstring'''
import numpy as np
def _lowerCAmelCase ( __magic_name__ : str , __magic_name__ : Optional[Any] , __magic_name__ : Optional[int] , __magic_name__ : int , __magic_name__ : str ) -> List[str]:
lowercase : ... | 92 |
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"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
__A = re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")
@total_ordering
@da... | 93 |
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 |
'''simple docstring'''
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # 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 six # no... | 94 |
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 ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 95 |
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
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
__lowerCamelCase = logging.get_logger(__name__)
def a ( __UpperCAmel... | 96 |
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 numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a ( snake_case__: int , snake_case__: int , snake_case__: int , snake_case__: int , snake_case__: int , snake_case__: int ):
'''simple docstring'''
#... | 97 |
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'''
# 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
#
... | 98 |
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 |
import collections
import os
import re
from pathlib import Path
SCREAMING_SNAKE_CASE = 'src/transformers'
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
SCREAMING_SNAKE_CASE ... | 99 |
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 |
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