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 |
|---|---|---|---|---|
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __UpperCamelCase :
__snake_case :int
__snake_case :int
class __UpperCamelCase :
def __init__( self : Any ... | 80 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 630 | 0 |
import string
def lowerCAmelCase_ ( __lowerCamelCase ):
for key in range(len(string.ascii_uppercase ) ):
__snake_case : Optional[int] = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 81 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
pa... | 630 | 0 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def a__ ( lowerCAmelCase__ ):
return getitem, k
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return setitem, k, v
... | 82 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""... | 630 | 0 |
"""simple docstring"""
from __future__ import annotations
def snake_case_ ( A_ : list[list[int]] ):
'''simple docstring'''
for i in range(1, len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i ... | 83 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-singl... | 630 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accelerat... | 84 |
"""simple docstring"""
import re
def _snake_case ( lowercase__ ):
if len(re.findall('[ATCG]' , lowercase__ ) ) != len(lowercase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ... | 630 | 0 |
def _a ( lowercase__ : int = 1_00 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : str = 0
SCREAMING_SNAKE_CASE__ : str = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 -... | 85 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffuse... | 630 | 0 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class _a ( snake_case_ ):
"""simple docstring"""
_lowerCamelCase : Tuple = (IPNDMScheduler,)
_lowerCamelCase : List[st... | 86 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torc... | 630 | 0 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 87 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 630 | 0 |
"""simple docstring"""
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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase ... | 88 |
"""simple docstring"""
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 ... | 630 | 0 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...tes... | 89 |
"""simple docstring"""
from typing import Any
def _snake_case ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ , ):
_validation(
lowercase__ , lowercase__ , lowercase__ ,... | 630 | 0 |
'''simple docstring'''
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def _snake_case ( A , A , A ) -> Union[str, Any]:
lowerCAmelCase__ = OmegaConf.load(A )
... | 90 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.l... | 630 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokeni... | 91 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase__ :
'''simple docstring'''
pass | 630 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, pre... | 92 |
"""simple docstring"""
import qiskit
def _snake_case ( lowercase__ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Dict = qiskit.Aer.get_backend('aer_simulator' )
... | 630 | 0 |
"""simple docstring"""
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->Optional[int]:
... | 93 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 630 | 0 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from tra... | 94 |
"""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 ...... | 630 | 0 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class UpperCamelCase_ (__A ):
__magic_... | 95 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = int(number**0.5 )
return number == sq * sq
... | 630 | 0 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils ... | 96 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class lowerCAmelCase__ ... | 630 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DD... | 97 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ): # This function is recursive
_lowerCamelCase : Optional[Any] = len(lowercase__ )
# If the array contains only one element, we return it (it's t... | 630 | 0 |
'''simple docstring'''
from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
MaskedBertForMultipleChoice,
MaskedBertForQuestionAnswering,
MaskedBertForSequenceClassification,
MaskedBertForTokenClassification,
MaskedBertModel,
)
from .modules import *
| 98 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = len(lowercase__ )
# We need to create solution object to save path.
_lowerCamelCase : Tuple = [[0 f... | 630 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE = {
'configuration_clip... | 99 |
"""simple docstring"""
import operator as op
def _snake_case ( lowercase__ ):
_lowerCamelCase : Dict = []
_lowerCamelCase : List[str] = lambda lowercase__ , lowercase__ : int(x / y ) # noqa: E731 integer ... | 630 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_A : Optional[int] = {"""configuration_plbart""": ["""PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PLBar... | 100 |
"""simple docstring"""
def _snake_case ( lowercase__ = 1 , lowercase__ = 1000 ):
_lowerCamelCase : Optional[int] = 1
_lowerCamelCase : List[Any] = 0
for divide_by_number in range(lowercase__ , digit + 1 ):
... | 630 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowercase (__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
_UpperCAmelCase = """ClapFeatureExtractor"""
_UpperCAmelCase =... | 101 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_... | 630 | 0 |
"""simple docstring"""
# 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/li... | 102 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 630 | 0 |
"""simple docstring"""
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from diffuse... | 103 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
pa... | 630 | 0 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"""The `inpainting.py` script is outdated. Please use directly `from diffusers import"""
""" StableDiffusionInpaintPipeline` ... | 104 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""... | 630 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase__ : Union[str, Any] = {'''configuration_encoder_decoder''': ['''EncoderDecoderConfig''']}
try:
if ... | 105 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-singl... | 630 | 0 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
__snake_case :Tuple ='https://www.indeed.co.in/jobs?q=mobile+app+development&l='
def lowerCamelCase_ ( lowerCAmelCase__ : str = "mumbai" ) -> Generator[tu... | 106 |
"""simple docstring"""
import re
def _snake_case ( lowercase__ ):
if len(re.findall('[ATCG]' , lowercase__ ) ) != len(lowercase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ... | 630 | 0 |
'''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _SCREAMING_SNAKE_CASE ( __snake_case : Optional[Any] , __snake_case : A... | 107 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffuse... | 630 | 0 |
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( __snake_case , __snake_case , __snake_case ) -> float:
if days_between_payments <= 0:
raise ValueError("""days_between_payments must be > 0""" )
if daily_interest_rate < 0:
... | 108 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torc... | 630 | 0 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a = logging.get_logger(__name__)
# TODO Update this
a = {
"facebook/esm-1b": "https://huggingface.co/facebook/esm-1b/re... | 109 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 630 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ = 1 ,lowerCAmelCase__ = 1_000 ):
lowerCamelCase_ = 1
lowerCamelCase_ = 0
for divide_by_number in range(lowercase__ ,digit + 1 ):
lowerCamelCase_ = []
lowerCamelCase_ = numerator
for _ in range(1 ,d... | 29 |
"""simple docstring"""
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 ... | 630 | 0 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
a : ... | 633 |
"""simple docstring"""
from typing import Any
def _snake_case ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ , ):
_validation(
lowercase__ , lowercase__ , lowercase__ ,... | 630 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_lowerCAmelCase : Tuple = {
'microsoft/unispeech-sat-base-100h-libri-ft': (
'https://hug... | 246 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.l... | 630 | 0 |
import argparse
from ...utils.dataclasses import (
ComputeEnvironment,
DistributedType,
DynamoBackend,
PrecisionType,
SageMakerDistributedType,
)
from ..menu import BulletMenu
_lowerCamelCase : Tuple = [
'EAGER',
'AOT_EAGER',
'INDUCTOR',
'N... | 121 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase__ :
'''simple docstring'''
pass | 630 | 0 |
'''simple docstring'''
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from ... | 664 |
"""simple docstring"""
import qiskit
def _snake_case ( lowercase__ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Dict = qiskit.Aer.get_backend('aer_simulator' )
... | 630 | 0 |
'''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
Dist... | 331 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 630 | 0 |
'''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_o... | 350 |
"""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 ...... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class A :
def __init__( self , snake_case_ ) -> Tuple:
_a = value
_a = None
_a = None
class A :
def __init... | 131 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = int(number**0.5 )
return number == sq * sq
... | 630 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
_snake_case = [8, 5, 9, 7]
_snake_case = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_snake_case = [
[3, 2, 1, 4],
... | 580 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class lowerCAmelCase__ ... | 630 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class __lowercase :
_a = field(
default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} )
_a ... | 539 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ): # This function is recursive
_lowerCamelCase : Optional[Any] = len(lowercase__ )
# If the array contains only one element, we return it (it's t... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, 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_t... | 329 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = len(lowercase__ )
# We need to create solution object to save path.
_lowerCamelCase : Tuple = [[0 f... | 630 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( lowerCAmelCase__ ):
lowerCamelCase_ = [True] * limit
lowerCamelCase_ = False
lowerCamelCase_ = False
lowerCamelCase_ = True
for i in range(3 ,int(limit**0.5 + 1 ) ,2 ):
lower... | 29 |
"""simple docstring"""
import operator as op
def _snake_case ( lowercase__ ):
_lowerCamelCase : Dict = []
_lowerCamelCase : List[str] = lambda lowercase__ , lowercase__ : int(x / y ) # noqa: E731 integer ... | 630 | 0 |
"""simple docstring"""
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
a : Any = '''src/tr... | 633 |
"""simple docstring"""
def _snake_case ( lowercase__ = 1 , lowercase__ = 1000 ):
_lowerCamelCase : Optional[int] = 1
_lowerCamelCase : List[Any] = 0
for divide_by_number in range(lowercase__ , digit + 1 ):
... | 630 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : Union[str, Any] = {
'configuration_bigbird_pegasus': [
'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BigBirdPegasusConfig',
... | 246 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_... | 630 | 0 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
clas... | 121 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 630 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_con... | 664 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
pa... | 630 | 0 |
'''simple docstring'''
UpperCamelCase_ : List[str] = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G""": ... | 331 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""... | 630 | 0 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
a = False
a = True
a = False
if __name__ == "__main__":
a = arg... | 350 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-singl... | 630 | 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 ...test_configuration_commo... | 131 |
"""simple docstring"""
import re
def _snake_case ( lowercase__ ):
if len(re.findall('[ATCG]' , lowercase__ ) ) != len(lowercase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ... | 630 | 0 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.ge... | 580 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffuse... | 630 | 0 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( a_ : Optional[int] , a_ : str , a_ : Union[str, Any] ):
if exponent == 1:
return base
if exponent % 2 == 0:
__a = _modexpt(lowercase__ , exponent // 2 ... | 539 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torc... | 630 | 0 |
'''simple docstring'''
import operator as op
def lowerCAmelCase_ ( __A : Optional[Any] ):
'''simple docstring'''
snake_case: Dict = []
snake_case: List[str] = lambda __A , __A : int(x / y ) # noqa: E731 integer division oper... | 329 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 630 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
... | 29 |
"""simple docstring"""
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 ... | 630 | 0 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcess... | 633 |
"""simple docstring"""
from typing import Any
def _snake_case ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ , ):
_validation(
lowercase__ , lowercase__ , lowercase__ ,... | 630 | 0 |
import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
... | 246 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.l... | 630 | 0 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class snake_case__ :
'''simple docstring'''
__A = None
__A = False
__A = False
... | 121 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase__ :
'''simple docstring'''
pass | 630 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import BertConfig, 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_flax_available():
... | 664 |
"""simple docstring"""
import qiskit
def _snake_case ( lowercase__ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Dict = qiskit.Aer.get_backend('aer_simulator' )
... | 630 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils impo... | 331 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
a = list[list[float | int]]
def a_ ( __UpperCAmelCase , __UpperCAmelCase ) -> Union[str, Any]:
"""simple docstring"""
snak... | 350 |
"""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 ...... | 630 | 0 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational impo... | 131 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = int(number**0.5 )
return number == sq * sq
... | 630 | 0 |
"""simple docstring"""
def __snake_case ( SCREAMING_SNAKE_CASE: Dict ):
"""simple docstring"""
_lowerCAmelCase = [False] * len(lowercase__ )
_lowerCAmelCase = [-1] * len(lowercase__ )
def dfs(SCREAMING_SNAKE_CASE... | 580 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class lowerCAmelCase__ ... | 630 | 0 |
'''simple docstring'''
import numpy as np
UpperCAmelCase_ = [
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class __lowercase :
def __init__( ... | 539 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ): # This function is recursive
_lowerCamelCase : Optional[Any] = len(lowercase__ )
# If the array contains only one element, we return it (it's t... | 630 | 0 |
'''simple docstring'''
from typing import Dict, Optional
import numpy as np
import datasets
__UpperCAmelCase = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. For binary (two... | 329 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = len(lowercase__ )
# We need to create solution object to save path.
_lowerCamelCase : Tuple = [[0 f... | 630 | 0 |
"""simple docstring"""
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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 Tokenize... | 29 |
"""simple docstring"""
import operator as op
def _snake_case ( lowercase__ ):
_lowerCamelCase : Dict = []
_lowerCamelCase : List[str] = lambda lowercase__ , lowercase__ : int(x / y ) # noqa: E731 integer ... | 630 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[Any] , _lowercase : List[str] , _lowercase : Dict , _lowercase : List[str]=None ) ->int:
'''simple docstring'''
a : Union[st... | 633 |
"""simple docstring"""
def _snake_case ( lowercase__ = 1 , lowercase__ = 1000 ):
_lowerCamelCase : Optional[int] = 1
_lowerCamelCase : List[Any] = 0
for divide_by_number in range(lowercase__ , digit + 1 ):
... | 630 | 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
_lowerCAmelCase : Any = logging.get_logger(__name__)
_lowerCAmelCase : ... | 246 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_... | 630 | 0 |
from pathlib import Path
import torch
from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter
_lowerCamelCase : Dict = 'Create a default config file for Accelerate wit... | 121 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 630 | 0 |
'''simple docstring'''
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
__magic_name__ : Optional[Any] =logging.getLogger(__name__)
class UpperCamelCase_ :
"""simple docst... | 664 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
pa... | 630 | 0 |
'''simple docstring'''
def _lowerCAmelCase (_lowercase ):
"""simple docstring"""
assert (
isinstance(lowercase__ , lowercase__ ) and number_of_steps > 0
), F'number_of_steps needs to be positive integer, your input {number_of_steps}'
if num... | 331 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""... | 630 | 0 |
'''simple docstring'''
def a_ ( __UpperCAmelCase = 1_00 ) -> int:
"""simple docstring"""
snake_case: Optional[int] =n * (n + 1) * (2 * n + 1) / 6
snake_case: List[Any] =(n * (n + 1) / 2) ** 2
return int(square_of_sum - su... | 350 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-singl... | 630 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 131 |
"""simple docstring"""
import re
def _snake_case ( lowercase__ ):
if len(re.findall('[ATCG]' , lowercase__ ) ) != len(lowercase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ... | 630 | 0 |
"""simple docstring"""
import pytest
import datasets
# Import fixture modules as plugins
_snake_case = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def __snake_case ( SCREAMING_SNAKE_CASE: Optional[Any] , SCREAMING_SNAKE_CA... | 580 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffuse... | 630 | 0 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __lowercase ( __magic_name__ , __magic_name__ ):
... | 539 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torc... | 630 | 0 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class SCREAMING_SNAKE_CASE ( unittest.TestCase ):
'''simple docstring'''
def _UpperCamelCase ( self ):
'''simple docstring'''
snake_case: Dict =... | 329 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 630 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
A_ = logging.get_logger(__name__)
class __lowerCamelCase ( lowerCAmelCase ):
def __init__( self , *UpperCAmelCase , **UpperCAmelCase ... | 29 |
"""simple docstring"""
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 ... | 630 | 0 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a : Optional[Any] = logging.get_logger(__name__)
a : Union[str, Any] = {'''vocab_file''': ''... | 633 |
"""simple docstring"""
from typing import Any
def _snake_case ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ , ):
_validation(
lowercase__ , lowercase__ , lowercase__ ,... | 630 | 0 |
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
@maybe_allow_in... | 246 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.l... | 630 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokeniz... | 121 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase__ :
'''simple docstring'''
pass | 630 | 0 |
'''simple docstring'''
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
... | 664 |
"""simple docstring"""
import qiskit
def _snake_case ( lowercase__ = 2 ):
_lowerCamelCase : Optional[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : Dict = qiskit.Aer.get_backend('aer_simulator' )
... | 630 | 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... | 331 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 630 | 0 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as ... | 350 |
"""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 ...... | 630 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transforme... | 131 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = int(number**0.5 )
return number == sq * sq
... | 630 | 0 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def __snake_case ( SCREAMING_SNAKE_CASE: Optional[int] ):
"""simple docstring"""
_lowerCAmelCase = np.max(lowercase__ , axis=-1 , keepdims=lowercase__ ... | 580 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class lowerCAmelCase__ ... | 630 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase_ = {
"configuration_swiftformer": [
"SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SwiftForm... | 539 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ): # This function is recursive
_lowerCamelCase : Optional[Any] = len(lowercase__ )
# If the array contains only one element, we return it (it's t... | 630 | 0 |
'''simple docstring'''
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch... | 329 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( lowercase__ ):
_lowerCamelCase : int = len(lowercase__ )
# We need to create solution object to save path.
_lowerCamelCase : Tuple = [[0 f... | 630 | 0 |
"""simple docstring"""
A_ = [
"""VerificationMode""",
"""Version""",
"""disable_progress_bar""",
"""enable_progress_bar""",
"""is_progress_bar_enabled""",
"""experimental""",
]
from .info_utils import VerificationMode
from .logging import disable_progress_bar, enable_progress_b... | 29 |
"""simple docstring"""
import operator as op
def _snake_case ( lowercase__ ):
_lowerCamelCase : Dict = []
_lowerCamelCase : List[str] = lambda lowercase__ , lowercase__ : int(x / y ) # noqa: E731 integer ... | 630 | 0 |
"""simple docstring"""
from typing import Any
def _SCREAMING_SNAKE_CASE ( _lowercase : Optional[Any] , _lowercase : Tuple , _lowercase : List[str] , _lowercase : Any , _lowercase : Any , ) ->int:
... | 633 |
"""simple docstring"""
def _snake_case ( lowercase__ = 1 , lowercase__ = 1000 ):
_lowerCamelCase : Optional[int] = 1
_lowerCamelCase : List[Any] = 0
for divide_by_number in range(lowercase__ , digit + 1 ):
... | 630 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a_ ( UpperCamelCase_ : Any ) -> Union[str, Any]:
"""simple docstring"""
lowerCamelCase = int(number**0.5 )
return number == sq * sq
def a_ ... | 246 |
"""simple docstring"""
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_... | 630 | 0 |
from __future__ import annotations
class snake_case__ :
'''simple docstring'''
def __init__( self : Optional[int] , lowerCAmelCase_ : Optional[int] , lowerCAmelCase_ : int ) -> Union[str, Any]:
Upper... | 121 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 630 | 0 |
'''simple docstring'''
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class UpperCamelCase_ ( A )... | 664 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
lowercase__ = argparse.ArgumentParser("""Stable Diffusion script with intel optimization""", add_help=False)
pa... | 630 | 0 |
'''simple docstring'''
import itertools
import string
from collections.abc import Generator, Iterable
def _lowerCAmelCase (_lowercase , _lowercase ):
"""simple docstring"""
a__ = iter(lowercase__ )
while True:
a__ = ... | 331 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""... | 630 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
... | 350 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-singl... | 630 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_co... | 131 |
"""simple docstring"""
import re
def _snake_case ( lowercase__ ):
if len(re.findall('[ATCG]' , lowercase__ ) ) != len(lowercase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketrans('ATCG' ... | 630 | 0 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class _SCREAMING_SNAKE_CASE ( UpperCAmelCase ):
'''simple docstring'''
def __... | 580 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffuse... | 630 | 0 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodule... | 539 |
"""simple docstring"""
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torc... | 630 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( snake_case ):
'''simple docstring'''
__UpperCamelCase = (DDPMScheduler,)
def _UpperCamelCase ... | 329 |
"""simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizer... | 630 | 0 |
"""simple docstring"""
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectr... | 29 |
"""simple docstring"""
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 ... | 630 | 0 |
"""simple docstring"""
from collections import deque
class __UpperCamelCase :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ) -> Any:
a : Tuple = process_name # process name
a : i... | 633 |
"""simple docstring"""
from typing import Any
def _snake_case ( lowercase__ , lowercase__ , lowercase__ , lowercase__ , lowercase__ , ):
_validation(
lowercase__ , lowercase__ , lowercase__ ,... | 630 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_lowerCAmelCase : Union[str, Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
_lowerCAmelCase : Optional[int] = None
def a_ ( ) -... | 246 |
"""simple docstring"""
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class lowerCAmelCase__ ( tf.keras.l... | 630 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCamelCase : Any = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 121 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCAmelCase__ :
'''simple docstring'''
pass | 630 | 0 |
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