code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase_ ( lowercase_ ):
"""simple docstring"""
a_ :List[Any] =["""image_processor""", """tokenizer"""]
a_ ... | 582 |
_snake_case = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def _A ( __magic_name__ ):
# Make sure the supplied data is a bytes-like object
if not isinstance(__magic_name__ , __magic_name__ ):
lowercase__ = f'''a bytes-like object is re... | 655 | 0 |
import os
import jsonlines
import numpy as np
from tqdm import tqdm
UpperCAmelCase_ = 2_048
UpperCAmelCase_ = 4_096
UpperCAmelCase_ = 42
UpperCAmelCase_ = os.environ.pop("""PROCESS_TRAIN""", """false""")
UpperCAmelCase_ = {"""null""": 0, """short"""... | 458 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCAmelCase ( ... | 655 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from trans... | 275 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_tor... | 655 | 0 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bn... | 459 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.... | 655 | 0 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( __snake_case : List[str] , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase , _lowerCamelCase : List[str] = position
_lowerCamelCase : ... | 88 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertConf... | 655 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 57 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
f... | 655 | 0 |
"""simple docstring"""
def _snake_case ( lowerCamelCase__ : Union[str, Any] , lowerCamelCase__ : List[Any] ) -> Tuple:
return 1 if input_a == input_a else 0
def _snake_case ( ) -> str:
assert xnor_gate(0 , 0 )... | 153 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
_snake_case = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
_snake_case = _LazyModule(__name__, globals()["""__file__"""], _i... | 655 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowercase_ : int = logging.get_logger(__name__)
lowercase_ : Any = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual... | 572 |
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_acce... | 655 | 0 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytesse... | 194 |
import inspect
import unittest
class lowerCAmelCase ( unittest.TestCase ):
def UpperCAmelCase ( self :int ):
'''simple docstring'''
try:
import diffusers # noqa: F401
except ImportError:
assert False
def UpperCAmelCase ( ... | 655 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
class snake_case_ ( lowercase_ ):
def __init__( self , *a_ , **a_ ):... | 237 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 655 | 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
_UpperCamelCase : Optional[int] = logging.get_logger(__name__... | 284 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_u... | 655 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import l... | 582 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = """▁"""
_snake_case ... | 655 | 0 |
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTokenizer,
RobertaToke... | 458 |
def _A ( __magic_name__ ):
lowercase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _A ( __magic_name__ = 100 ):
lowercase__ = 1
lowercase__ = 2
for i in range(2 , max_n + 1 ):
lowercase__ ... | 655 | 0 |
'''simple docstring'''
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __snake_case ( lowercase_ ,lowercase_):
"""simple docstring"""
@register_to_conf... | 275 |
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
_snake_case = logging... | 655 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_... | 459 |
import math
import random
def _A ( __magic_name__ , __magic_name__ = False ):
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
_snake_case = 0.02
def _A ( __magic_name__ , __magic_name__ ):
lowercase__ = ... | 655 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_i... | 88 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"""
... | 655 | 0 |
# Copyright 2023 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... | 57 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmelCase ( enum.Enum ):
__low... | 655 | 0 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_... | 153 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
_snake_case = collections.namedtuple("""_Datasets""", ["""train""",... | 655 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : List[Any] = logging.get_logger(__name__)
lowercase_ : List[str] = {
'''microsoft/git-base'... | 572 |
from __future__ import annotations
class lowerCAmelCase :
def __init__( self :Union[str, Any] , _lowercase :List[Any]=None ):
'''simple docstring'''
lowercase__ = data
lowercase__ = None
def __repr__( self :Dict ... | 655 | 0 |
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is_tf_available() and ... | 194 |
import random
from .binary_exp_mod import bin_exp_mod
def _A ( __magic_name__ , __magic_name__=1000 ):
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
lowercase__ = n - 1
lowercase__ = 0
while d % 2 == 0:
d /= 2
... | 655 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE_ = TypeVar("""T""")
SCREAMING_SNAKE_CASE_ = TypeVar("""U""")
class snake_case_ ( Generic[T, U] ):
def _... | 237 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from diffusers.utils.t... | 655 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingSt... | 284 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
... | 655 | 0 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE_ = parse(importlib.metadata.version('torch'))
def __lowercase ( __SCREAMING_SNAKE_CASE , __SCR... | 582 |
_snake_case = """ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"""
def _A ( __magic_name__ ):
# Make sure the supplied data is a bytes-like object
if not isinstance(__magic_name__ , __magic_name__ ):
lowercase__ = f'''a bytes-like object is re... | 655 | 0 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
UpperCAmelCase_ = {
"""E""": 12.70,
"""T""": 9.06,
"""A""": 8.17,
"""O""": 7.51,
"""I""": 6.97,
"""N""": 6.75,
"""S""": 6.33,
"""H""": 6.09,
"""R""": 5.99,
"""D"... | 458 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCAmelCase ( ... | 655 | 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/... | 275 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_tor... | 655 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowercase_ )
class lowerCamelCase_ ( lowercase_ ):
"""simp... | 459 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"""microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.... | 655 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, re... | 88 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
BertConf... | 655 | 0 |
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__=False ) -> List[str]:
if isinstance(UpperCAmelCase__ , UpperCAmelCase__ ) and isinstance(UpperCAmelCase__ , UpperCAmelCase__ ):
UpperCamelCase_: Any ... | 57 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision.transforms import functional as F
from transformers import DetrImageProcessor, TableTransformerConfig, TableTransformerForObjectDetection
f... | 655 | 0 |
"""simple docstring"""
def _snake_case ( lowerCamelCase__ : Any ) -> str:
if any(not isinstance(lowerCamelCase__ , lowerCamelCase__ ) or x < 0 for x in sequence ):
raise TypeError("Sequence must be list of non-negative integers" )
... | 153 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
_snake_case = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
_snake_case = _LazyModule(__name__, globals()["""__file__"""], _i... | 655 | 0 |
"""simple docstring"""
from PIL import Image
def _lowerCAmelCase ( lowerCamelCase__ : Any ) -> Dict:
_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE : List[Any] = image.size
_SCREAMING_SNAKE_CASE : Optional[int] = 0
_SCREAMING_SNAKE_CASE : Di... | 572 |
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_acce... | 655 | 0 |
from collections import defaultdict
from math import ceil, sqrt
def __a ( __UpperCAmelCase = 100_0000 , __UpperCAmelCase = 10 ):
a__ = defaultdict(__UpperCAmelCase )
for outer_width in range(3 , (t_limit // 4) + 2 ):
if outer_width * outer_width > t_lim... | 194 |
import inspect
import unittest
class lowerCAmelCase ( unittest.TestCase ):
def UpperCAmelCase ( self :int ):
'''simple docstring'''
try:
import diffusers # noqa: F401
except ImportError:
assert False
def UpperCAmelCase ( ... | 655 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax... | 237 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 655 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformer... | 284 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_u... | 655 | 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 ...t... | 582 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = """▁"""
_snake_case ... | 655 | 0 |
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, prepare_imag... | 458 |
def _A ( __magic_name__ ):
lowercase__ = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _A ( __magic_name__ = 100 ):
lowercase__ = 1
lowercase__ = 2
for i in range(2 , max_n + 1 ):
lowercase__ ... | 655 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configu... | 275 |
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
_snake_case = logging... | 655 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelin... | 459 |
import math
import random
def _A ( __magic_name__ , __magic_name__ = False ):
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
_snake_case = 0.02
def _A ( __magic_name__ , __magic_name__ ):
lowercase__ = ... | 655 | 0 |
"""simple docstring"""
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcesso... | 88 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json"""
... | 655 | 0 |
A_ : List[str] = [
[0, 16, 13, 0, 0, 0],
[0, 0, 10, 12, 0, 0],
[0, 4, 0, 0, 14, 0],
[0, 0, 9, 0, 0, 20],
[0, 0, 0, 7, 0, 4],
[0, 0, 0, 0, 0, 0],
]
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ... | 57 |
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class lowerCAmelCase ( enum.Enum ):
__low... | 655 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 153 |
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
_snake_case = collections.namedtuple("""_Datasets""", ["""train""",... | 655 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def lowercase ( UpperCamelCase : str = "AAPL" ):
"""simple docstring"""
A__ : Union[str, Any] =F'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
A__ : Dict =BeautifulSoup(re... | 656 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : Any = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CONF... | 656 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 656 | """simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
... | 656 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : int = logging.get_logger(__name__)
__A : int = {
"facebook/wav2vec2-base-960h": "https://huggingface.co/facebook/wav2vec2-base-960h/... | 656 | """simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 656 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configurat... | 656 | """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
... | 656 | 1 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
__A : Dict = argparse.ArgumentParser("Stable Diffusion script with intel optimization", add_help=False)
parser.add_argument("-... | 656 | """simple docstring"""
import os
def lowercase ( ):
"""simple docstring"""
A__ : List[Any] =os.path.dirname(os.path.realpath(UpperCamelCase ) )
A__ : str =os.path.join(UpperCamelCase , "triangle.txt" )
with open(UpperCamelCase ) as f:
... | 656 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : Any = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CONF... | 656 | """simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__A : int ... | 656 | 1 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
__A : str = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snover, Matthew and\n ... | 656 | """simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__A : Any =... | 656 | 1 |
"""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/licenses/LICENSE-2.0
#... | 656 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Any = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __lowerCAmelCa... | 656 | 1 |
"""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")):
raise OptionalDependencyNotAv... | 656 | """simple docstring"""
from __future__ import annotations
def lowercase ( UpperCamelCase : list[float] ):
"""simple docstring"""
if len(UpperCamelCase ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if any(i <= 0 for i i... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
if length <= 0 or not isinstance(UpperCamelCase , UpperCamelCase ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(UpperC... | 656 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : Optional[Any] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not ... | 656 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProces... | 656 | """simple docstring"""
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
if num <= 0:
raise ValueError("Input must be a positive integer" )
A__ : Union[str, Any] =[True] * (num + 1)
A__ : Union[str, Any] =2
while p *... | 656 | 1 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowercase ( ):
... | 656 | """simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowerCAmelCase ( unittest.TestCase):
'''simple docstring'''
def ... | 656 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : Optional[Any] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not ... | 656 | """simple docstring"""
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 .tokeni... | 656 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 656 | """simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__A : Optional[int] = l... | 656 | 1 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats... | 656 | """simple docstring"""
def lowercase ( UpperCamelCase : int , UpperCamelCase : list[int] , UpperCamelCase : int ):
"""simple docstring"""
def count_of_possible_combinations(UpperCamelCase : int ) -> int:
if target < 0:
... | 656 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__A : List[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( _UpperCamelCase):
'''simple docs... | 656 | """simple docstring"""
import math
import tensorflow as tf
from packaging import version
def lowercase ( UpperCamelCase : Optional[Any] ):
"""simple docstring"""
A__ : List[Any] =tf.convert_to_tensor(UpperCamelCase )
A__ : List[Any] =0.5 * (1.0 + tf.ma... | 656 | 1 |
"""simple docstring"""
from collections.abc import Sequence
from queue import Queue
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self : Union[str, Any] , UpperCamelCase__ : str , UpperCamelCase__ : List[Any] , UpperCamelCase__ : Dict ... | 656 | """simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from... | 656 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Optional[int] = logging.get_logger(__name__)
__A : int = {
"caidas/swin2sr-classicalsr-x2-64": (
"https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/reso... | 656 | """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_flax_ava... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : str ):
"""simple docstring"""
return " ".join(
"".join(word[::-1] ) if len(UpperCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(re... | 656 | """simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : str , UpperCamelCase : str ):
"""simple docstring"""
A__ : Tuple =len(UpperCamelCase )
A__ : Optional[int] =[]
for i in range(len(UpperCamelCase ) - pat_len + 1 ):
A... | 656 | """simple docstring"""
__A : Union[str, Any] = {str(digit): digit**5 for digit in range(10)}
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(UpperCamelCase ) )
def lowercase ( ):
... | 656 | 1 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import... | 656 | """simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention,... | 656 | 1 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_... | 656 | """simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_para... | 656 | 1 |
"""simple docstring"""
class __lowerCAmelCase :
'''simple docstring'''
def __init__( self : Optional[int] ):
A__ : Optional[Any] =""
A__ : Optional[Any] =""
A__ : Dict =[]
def _UpperCAmelCase ( self ... | 656 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : Any = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CONF... | 656 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
__A : Any = ... | 656 | """simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : list , UpperCamelCase : list , UpperCamelCase : int ):
"""simple docstring"""
if len(UpperCamelCase ) != len(UpperCamelCase ):
raise ValueError("The length of profit and weight must b... | 656 | """simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 656 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __lowerCAmelCase ( _UpperCamelCase):
'''simple docstring'''
@staticmethod
@abstractmethod
def _UpperCAmelCase ( UpperCamelCase__ : ArgumentParser ):
... | 656 | """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
... | 656 | 1 |
"""simple docstring"""
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calc... | 656 | """simple docstring"""
import os
def lowercase ( ):
"""simple docstring"""
A__ : List[Any] =os.path.dirname(os.path.realpath(UpperCamelCase ) )
A__ : str =os.path.join(UpperCamelCase , "triangle.txt" )
with open(UpperCamelCase ) as f:
... | 656 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
res... | 656 | """simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__A : int ... | 656 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def lowercase ( UpperCamelCase : Dict ):
"""simple docstring"""
A__ : str =args.pruning_method
A__ : ... | 656 | """simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__A : Any =... | 656 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowercase ( UpperCamelCase : str ):
"""simple docstring"""
return [ord(UpperCamelCase ) - 96 for elem in plain]
def lowercase ( UpperCamelCase : list[int] ):
"""simple docstring"""
... | 656 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Any = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __lowerCAmelCa... | 656 | 1 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCAm... | 656 | """simple docstring"""
from __future__ import annotations
def lowercase ( UpperCamelCase : list[float] ):
"""simple docstring"""
if len(UpperCamelCase ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if any(i <= 0 for i i... | 656 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 656 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : Optional[Any] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not ... | 656 | 1 |
"""simple docstring"""
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMR... | 656 | """simple docstring"""
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
if num <= 0:
raise ValueError("Input must be a positive integer" )
A__ : Union[str, Any] =[True] * (num + 1)
A__ : Union[str, Any] =2
while p *... | 656 | 1 |
"""simple docstring"""
from collections import defaultdict
from math import gcd
def lowercase ( UpperCamelCase : int = 1500000 ):
"""simple docstring"""
A__ : defaultdict =defaultdict(UpperCamelCase )
A__ : Any =2
while 2 * euclid_m * (euclid_m + ... | 656 | """simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowerCAmelCase ( unittest.TestCase):
'''simple docstring'''
def ... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : int , UpperCamelCase : int ):
"""simple docstring"""
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
A__ : int =str(bin(UpperCamelCase ) )[2:] # ... | 656 | """simple docstring"""
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 .tokeni... | 656 | 1 |
"""simple docstring"""
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from ... | 656 | """simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__A : Optional[int] = l... | 656 | 1 |
"""simple docstring"""
import argparse
import os
import re
__A : str = "src/transformers"
# Pattern that looks at the indentation in a line.
__A : Dict = re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
__A : Tuple = re.compile(R... | 656 | """simple docstring"""
def lowercase ( UpperCamelCase : int , UpperCamelCase : list[int] , UpperCamelCase : int ):
"""simple docstring"""
def count_of_possible_combinations(UpperCamelCase : int ) -> int:
if target < 0:
... | 656 | 1 |
"""simple docstring"""
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def lowercase ( UpperCamelCase : Optional[int] , UpperCamelCase : List[Any]=() ... | 656 | """simple docstring"""
import math
import tensorflow as tf
from packaging import version
def lowercase ( UpperCamelCase : Optional[Any] ):
"""simple docstring"""
A__ : List[Any] =tf.convert_to_tensor(UpperCamelCase )
A__ : List[Any] =0.5 * (1.0 + tf.ma... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : int , UpperCamelCase : int ):
"""simple docstring"""
while a != 0:
A__ , A__ : List[Any] =b % a, a
return b
def lowercase ( UpperCamelCase : int , Uppe... | 656 | """simple docstring"""
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : list[list[int]] , UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : set ):
"""simple docstring"""
A__ , A__ : Union[str, Any] =len(UpperCamelCase ), le... | 656 | """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_flax_ava... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : list ):
"""simple docstring"""
A__ : Union[str, Any] =0
while len(UpperCamelCase ) > 1:
A__ : Optional[int] =0
# Consider two files with minimum cost to be merged
f... | 656 | """simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.... | 656 | 1 |
"""simple docstring"""
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
__A : Optional[Any] = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2... | 656 | """simple docstring"""
__A : Union[str, Any] = {str(digit): digit**5 for digit in range(10)}
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(UpperCamelCase ) )
def lowercase ( ):
... | 656 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_... | 656 | """simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention,... | 656 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_det... | 656 | """simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_para... | 656 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : str = logging.get_logger(__name__)
__A : str = {
"microsoft/cvt-13": "https://huggingface.co/microsoft/cvt-13/resolve/main/config.json",
# See all Cvt models at h... | 656 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__A : Any = {
"configuration_efficientformer": [
"EFFICIENTFORMER_PRETRAINED_CONF... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : str ):
"""simple docstring"""
A__ : Any =0
for ch in input_str:
A__ : int =ord(UpperCamelCase )
A__ : str =pow(2 , UpperCamelCase )
# If we alrea... | 656 | """simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
... | 656 | 1 |
"""simple docstring"""
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttention,... | 656 | """simple docstring"""
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 656 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Optional[int] = logging.get_logger(__name__)
__A : Tuple = {
"RWKV/rwkv-4-169m-pile": "https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json",
"RW... | 656 | """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
... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : str ):
"""simple docstring"""
assert column_title.isupper()
A__ : List[str] =0
A__ : Tuple =len(UpperCamelCase ) - 1
A__ : List[str] =0
while index >= 0:
A__ :... | 656 | """simple docstring"""
import os
def lowercase ( ):
"""simple docstring"""
A__ : List[Any] =os.path.dirname(os.path.realpath(UpperCamelCase ) )
A__ : str =os.path.join(UpperCamelCase , "triangle.txt" )
with open(UpperCamelCase ) as f:
... | 656 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A : Dict = logging.get_logger(__name__)
__A : List[str] = {
"facebook/xlm-r... | 656 | """simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
__A : int ... | 656 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__A : str = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
... | 656 | """simple docstring"""
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__A : Any =... | 656 | 1 |
"""simple docstring"""
from __future__ import annotations
__A : Any = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowercase ( UpperCamelCase : list[list[int]] , UpperCamelCase : list[int] , UpperCamelCase : ... | 656 | """simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Any = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __lowerCAmelCa... | 656 | 1 |
"""simple docstring"""
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowercase ( ):
"""simple docstring"""
A__ : Union[str, Any] ={
"repo_name": ["test_repo1", "test_repo2"... | 656 | """simple docstring"""
from __future__ import annotations
def lowercase ( UpperCamelCase : list[float] ):
"""simple docstring"""
if len(UpperCamelCase ) < 2:
raise ValueError("Monogons and Digons are not polygons in the Euclidean space" )
if any(i <= 0 for i i... | 656 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : Union[str, Any] = {
"configuration_clap": [
"CLAP_PRETRAINED_MODEL_ARCHIVE_LIST",
"ClapAudioConfig",
"ClapConfig",
... | 656 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : Optional[Any] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig"],
}
try:
if not ... | 656 | 1 |
"""simple docstring"""
__A : str = range(2, 20 + 1)
__A : Dict = [10**k for k in range(ks[-1] + 1)]
__A : dict[int, dict[int, list[list[int]]]] = {}
def lowercase ( UpperCamelCase : Optional[Any] , UpperCamelCase : int , Uppe... | 656 | """simple docstring"""
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
if num <= 0:
raise ValueError("Input must be a positive integer" )
A__ : Union[str, Any] =[True] * (num + 1)
A__ : Union[str, Any] =2
while p *... | 656 | 1 |
"""simple docstring"""
__A : Union[str, Any] = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
__A : Optional[int] ... | 656 | """simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class __lowerCAmelCase ( unittest.TestCase):
'''simple docstring'''
def ... | 656 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A : str = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"JukeboxPriorConfig",
... | 656 | """simple docstring"""
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 .tokeni... | 656 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_im... | 656 | """simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
__A : Optional[int] = l... | 656 | 1 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
__A : Optional[int] = logging.get_logger("transformers.models.speecht5")
def lowercase ( UpperCamelCase : ... | 656 | """simple docstring"""
def lowercase ( UpperCamelCase : int , UpperCamelCase : list[int] , UpperCamelCase : int ):
"""simple docstring"""
def count_of_possible_combinations(UpperCamelCase : int ) -> int:
if target < 0:
... | 656 | 1 |
"""simple docstring"""
def lowercase ( UpperCamelCase : str , UpperCamelCase : int ):
"""simple docstring"""
A__ : list[list[str]] =[[] for _ in range(UpperCamelCase )]
A__ : Union[str, Any] =key - 1
if key <= 0:
raise Val... | 656 | """simple docstring"""
import math
import tensorflow as tf
from packaging import version
def lowercase ( UpperCamelCase : Optional[Any] ):
"""simple docstring"""
A__ : List[Any] =tf.convert_to_tensor(UpperCamelCase )
A__ : List[Any] =0.5 * (1.0 + tf.ma... | 656 | 1 |
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