code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class __A ( lowerCamelCase__ ):
"""simple docstring"""
UpperCAmelCase__ = """EncodecFeatureExtractor"""
UpperCAmelCase__ ... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
... | 719 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 613 | 0 |
'''simple docstring'''
def __UpperCAmelCase( lowercase_ , lowercase_ ):
if density <= 0:
raise ValueError('''Impossible fluid density''' )
if bulk_modulus <= 0:
raise ValueError('''Impossible bulk modulus''' )
return (bulk_modulus /... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase__ )
class __A ( lowerCamelCase__ ):
"""simple docstring"""
UpperC... | 721 |
import pytest
import datasets
# Import fixture modules as plugins
_lowerCamelCase = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __UpperCAmelCase( lowercase_ , lowercase_ ):
# Mark tests as "unit" by default if not marked as "integration" ... | 613 | 0 |
'''simple docstring'''
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available(... | 700 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 613 | 0 |
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@req... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 0 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIV... | 613 | 0 |
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : list[list[int]] = [[0 for _ in range(lowercase_ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
_lowerCamelCase : List[Any] = 1
for n in range(m + 1 ):
... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig'... | 613 | 0 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CO... | 613 | 0 |
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to V and v to U. We can also say tha... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_t... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
def __UpperCAmelCase( ):
_lowerCamelCase : Any = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
_lowerCamelCase : Dict = 6
_lowerCamelCase : List[Any] = 1
_lowerCamelCase : List[Any] = 19_01
_low... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
def __UpperCAmelCase( lowercase_ ):
stooge(lowercase_ , 0 , len(lowercase_ ) - 1 )
return arr
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
if i >= h:
return
# If first element is smaller than the last t... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_avail... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_lowerCamelCase = re.compile(r'\b(a|an|the)\b', re.UNICODE)
_lowerCamelCase = None
def __UpperCAmelCase( ):
_lowerCamelCase : Union[str, Any] ... | 710 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 613 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import j... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCamelCase = {
'configuration_graphormer': ['GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GraphormerConfig'],
}
try:
if not is_torch_avail... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator,... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Im... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prep... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 0 |
from math import factorial
_lowerCamelCase = {str(d): factorial(d) for d in range(10)}
def __UpperCAmelCase( lowercase_ ):
return sum(DIGIT_FACTORIAL[d] for d in str(lowercase_ ) )
def __UpperCAmelCase( ):
_lowerCamelCase : Any = 7 * f... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 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
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {'vocab_file': 'sp... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_informer': [
'INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InformerConfig',
],
}
try:... | 719 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 613 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class __A ( datasets.BuilderConfig ):
"""simple docstring"""
... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_efficientformer': [
'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 721 |
import pytest
import datasets
# Import fixture modules as plugins
_lowerCamelCase = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __UpperCAmelCase( lowercase_ , lowercase_ ):
# Mark tests as "unit" by default if not marked as "integration" ... | 613 | 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.... | 700 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requi... | 613 | 0 |
_lowerCamelCase = {
'meter': 'm',
'kilometer': 'km',
'megametre': 'Mm',
'gigametre': 'Gm',
'terametre': 'Tm',
'petametre': 'Pm',
'exametre': 'Em',
'zettametre': 'Zm',
'yottametre': 'Ym',
}
# Exponent of the factor(meter)
_lowerCamelCase ... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 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... | 702 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_roberta_prelayernorm': [
'ROBERTA_PRELAYERNORM_PRETRAINED_CONFIG_ARCHIV... | 613 | 0 |
from pathlib import Path
import fire
from tqdm import tqdm
def __UpperCAmelCase( lowercase_="ro" , lowercase_="en" , lowercase_="wmt16" , lowercase_=None ):
try:
import datasets
except (ModuleNotFoundError, ImportError):
raise ImportError('''run... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_opt': ['OPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'OPTConfig'... | 613 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
_lowerCamelCase = {
'configuration_audio_spectrogram_transformer': [
'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'ASTCo... | 704 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CO... | 613 | 0 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 705 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 613 | 0 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 706 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from ... | 613 | 0 |
'''simple docstring'''
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.dat... | 707 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __A ( lowerCamelCase__ ):... | 708 |
_lowerCamelCase = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase = {
0: 'Sunday',
1: 'Monday',
2: 'Tuesday',
3: 'Wednesday',
4: 'Thursday',
5: 'Friday',
6: 'Saturday',
}
def __... | 613 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'facebook/s2t-small-librispeech-asr': (
'https://huggingface.co/facebook/s2t-small-librispeech-asr/resolve/main/config.json... | 709 |
import math
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = len(lowercase_ )
_lowerCamelCase : Optional[int] = int(math.floor(math.sqrt(lowercase_ ) ) )
_lowerCamelCase : Tuple = 0
w... | 613 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxModelT... | 710 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 613 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase... | 711 |
def __UpperCAmelCase( lowercase_ ):
# if the collection is empty, returns empty
if collection == []:
return []
# get some information about the collection
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : List[str]... | 613 | 0 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __A ... | 712 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
... | 613 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {'vocab_file': 'vocab.json', 'mer... | 713 |
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
return round(float((moles * 0.0_8_2_1 * temperature) / (volume) ) ... | 613 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConf... | 714 |
import qiskit
def __UpperCAmelCase( lowercase_ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Optional[int] = qiskit.Aer.get_backend('''aer_simulator''' )
# Creating a Quantum Circuit acting on the... | 613 | 0 |
_lowerCamelCase = 256
# Modulus to hash a string
_lowerCamelCase = 100_0003
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : Tuple = len(lowercase_ )
_lowerCamelCase : int = len(lowercase_ )
if p... | 715 |
import unittest
from knapsack import knapsack as k
class __A ( unittest.TestCase ):
"""simple docstring"""
def __snake_case ( self):
"""simple docstring"""
_lowerCamelCase : Dict = 0
_lowerCamelCase ... | 613 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.s... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__... | 717 |
import warnings
from .generation import TFGenerationMixin
class __A ( lowerCamelCase__ ):
"""simple docstring"""
warnings.warn(
"""Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will """
"""be removed... | 613 | 0 |
import math
from collections.abc import Callable
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
_lowerCamelCase : float = xa
_lowerCamelCase : float = xa
while True:
if x_n == x_na or function(lowercase_ ) == funct... | 718 |
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ...utils import loggin... | 613 | 0 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_lowerCamelCase = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
'KD 6S 9D TH AD',
'... | 719 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 613 | 0 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_lowerCamelCas... | 720 |
def __UpperCAmelCase( lowercase_ = 10_00 ):
_lowerCamelCase : Optional[int] = 2**power
_lowerCamelCase : Optional[int] = 0
while n:
_lowerCamelCase, _lowerCamelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__... | 613 | 0 |
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available,
)
from . import Ba... | 721 |
import pytest
import datasets
# Import fixture modules as plugins
_lowerCamelCase = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def __UpperCAmelCase( lowercase_ , lowercase_ ):
# Mark tests as "unit" by default if not marked as "integration" ... | 613 | 0 |
"""simple docstring"""
import argparse
import json
import subprocess
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> List[Any]:
"""simple docstring"""
__snake_case = []
__snake_case = (
F'''curl -H ... | 614 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,... | 614 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 1 |
"""simple docstring"""
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __magic_name__ ( lowercase__ ):
@require_torch
def lowerCAmelCase ... | 614 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
_SCREAMING_SNAKE_CASE = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
... | 614 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
_SCREAMING_SNAKE_CASE = """\
@inproceedings{popovic-2015-chrf,
title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",
author = \"Popovi{\'c}, Maja... | 614 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 1 |
"""simple docstring"""
_SCREAMING_SNAKE_CASE = 65_521
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
__snake_case = 1
__snake_case = 0
for plain_chr in plain_text:
__snake_case ... | 614 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForConditi... | 614 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import Ba... | 614 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_transfo_xl""": ["""TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TransfoXLConfig"""],
... | 614 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[float | int, list[tuple[int, int]]]:
"""simp... | 614 | 1 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.... | 614 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
d... | 614 | 1 |
"""simple docstring"""
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> Optional[Any]:
"""simple docstring"""
monkeypatch.setattr("datasets.utils.deprecation_utils._emitted_deprecati... | 614 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],... | 614 | 1 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
"""simple docstring"""
def decorator(SCREAMING_SNAKE_CASE ):
__snake_case = getattr(SCREAMING... | 614 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 1_00 , ) -> float:
"""simple docstring... | 614 | 1 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 1 , SCREAMING_SNAKE_CASE = 10_00 ) -> int:
"""simple docstring"""
__snake_case = 1
__snake_case = 0
for divide_by_number in range(SCREAMING_SNAKE_CASE ... | 614 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> List[Any]:... | 614 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 1 |
"""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,
)
_SCREAMING_SNAKE_CASE = {"""config... | 614 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 614 | 1 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
Auto... | 614 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConf... | 614 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_fla... | 614 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__snake_case = ... | 614 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_SCREAMING_SNAKE_CASE = TypeVar("""T""")
class __magic_name__ ( Generic[T] ):
def __init__( self : str , snake_cas... | 614 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 614 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_m2m_100""": ["""M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP""", """M2M100Config""", """M2M... | 614 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import Backbone... | 614 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ... | 614 | 1 |
"""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 accel... | 614 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vis... | 614 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 10_00 , SCREAMING_SNAKE_CASE = True ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
... | 614 | 1 |
"""simple docstring"""
from __future__ import annotations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> dict[str, float]:
"""simple docstring"""
if (voltage, current, resistance).count(0 ) != 1:
... | 614 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 1 |
"""simple docstring"""
_SCREAMING_SNAKE_CASE = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
... | 614 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 1 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 1 |
"""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__)
_SCREAMING_SNAKE_CASE = {
... | 614 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 1 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hparam into the config
# ... | 614 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 1 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_avai... | 614 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 1 |
"""simple docstring"""
import math
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
__snake_case = F'''Input value of [number={number}] must be an ... | 614 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREA... | 614 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import Ba... | 614 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glu... | 614 |
"""simple docstring"""
from heapq import heappop, heappush
import numpy as np
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[float | int, list[tuple[int, int]]]:
"""simp... | 614 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
d... | 614 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_SCREAMING_SNAKE_CASE = logging.get_logger(__nam... | 614 |
"""simple docstring"""
from __future__ import annotations
_SCREAMING_SNAKE_CASE = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],... | 614 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tenso... | 614 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 1_00 , ) -> float:
"""simple docstring... | 614 | 1 |
"""simple docstring"""
from math import pow
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , ) -> tuple[int, int]:
"""simple docstring"""
if c... | 614 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
__snake_case = {"+", "-", "*", "/"}
__sna... | 614 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class __magic_name__ :
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNAKE_CASE : TreeNode... | 614 | 1 |
"""simple docstring"""
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
_SCREAMING_SNAKE_CASE = logging.getLogger(__name__)
_SCREAMING_... | 614 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list:
"""simple docstring"""
__snake_case = len(SCREAMING_SNAKE_CASE )
for i in range(1 , SCREAMING_SNAKE_CASE ):
__snake_case = collection[i]
... | 614 | 1 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __magic_name__ ( lowercase__ ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = (CMStochasticIterativeScheduler,)
_SCR... | 614 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConf... | 614 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if no... | 614 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = None ) -> int:
"""simple docstring"""
if nums is None or not nums:
raise ValueError("Input sequence should not be empty" )
__snake_case = ... | 614 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@da... | 614 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_to... | 614 | 1 |
"""simple docstring"""
from itertools import permutations
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] ... | 614 |
"""simple docstring"""
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .s... | 614 | 1 |
"""simple docstring"""
import inspect
import unittest
class __magic_name__ ( unittest.TestCase ):
def lowerCAmelCase ( self : Union[str, Any] ):
try:
import diffusers # noqa: F401
except ImportError:
... | 614 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ... | 614 | 1 |
"""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 import (
Autoenc... | 614 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 614 | 1 |
"""simple docstring"""
from random import randint, random
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = False , SCREAMING_SNAKE_CASE = False , SCREAMING_SNAKE_CASE = 5 , ) -> l... | 614 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE = 10 , SCREAMING_SNAKE_CASE = 10_00 , SCREAMING_SNAKE_CASE = True ) -> int:
"""simple docstring"""
assert (
isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE )
... | 614 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler... | 614 |
"""simple docstring"""
import baseaa
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
... | 614 | 1 |
"""simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 614 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Conf... | 614 | 1 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
if number > 0:
raise ValueError("input must be a negative integer" )
__snake_case = len(bin(SCREAMING_SNAKE_CASE )[3:] )
__snake_case ... | 614 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-... | 614 | 1 |
"""simple docstring"""
from math import isqrt
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> bool:
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(SCREAMING_SNAKE_CASE ) + 1 ) )
def __UpperCamelCase ( SCREAMING_SNAKE_C... | 614 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_SCREAMING_SNAKE_CASE = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_... | 614 | 1 |
"""simple docstring"""
def __UpperCamelCase ( SCREAMING_SNAKE_CASE ) -> list[int]:
"""simple docstring"""
__snake_case = [0 for i in range(len(SCREAMING_SNAKE_CASE ) )]
# initialize interval's left pointer and right pointer
__snake_case , __sna... | 614 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availabl... | 614 | 1 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_SCREAMING_SNAKE_CASE = 6_378_137.0
_SCREAMING_SNAKE_CASE = 6_356_752.314_245
_SCREAMING_SNAKE_CASE = 6_378_137
def __UpperCamelCase ( SCREAMING_S... | 614 |
"""simple docstring"""
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __magic_name__ ( lowercase__ ):
def ... | 614 | 1 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
_SCREAMING_SNAKE_CASE = """
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Sim... | 614 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 1 |
"""simple docstring"""
import numpy as np
_SCREAMING_SNAKE_CASE = [
["""a""", """b""", """c""", """d""", """e"""],
["""f""", """g""", """h""", """i""", """k"""],
["""l""", """m""", """n""", """o""", """p"""],
["""q""", """r""", """s""", """t""", """u"""],
["""v""", """w""", """x... | 614 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import Ba... | 614 | 1 |
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