





'''simple docstring'''







from sklearn.neural_network import MLPClassifier

snake_case_       :    int          =					[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
snake_case_       :    Tuple          =					[0, 1, 0, 0]


snake_case_       :    Any          =					MLPClassifier(
    solver="lbfgs", alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


snake_case_       :    str          =					[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
snake_case_       :    List[Any]          =					clf.predict(test)





def     lowerCamelCase_ (					SCREAMING_SNAKE_CASE__ :     Tuple				)	->		Optional[int]:
						return list(_lowerCAmelCase				)


if __name__ == "__main__":
					import doctest

					doctest.testmod()












'''simple docstring'''







# 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 required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


snake_case_       :    List[Any]          =					{
    "configuration_tvlt": ["TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP", "TvltConfig"],
    "feature_extraction_tvlt": ["TvltFeatureExtractor"],
    "processing_tvlt": ["TvltProcessor"],
}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_       :    Optional[int]          =					[
					    "TVLT_PRETRAINED_MODEL_ARCHIVE_LIST",
					    "TvltModel",
					    "TvltForPreTraining",
					    "TvltForAudioVisualClassification",
					    "TvltPreTrainedModel",
					]

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					snake_case_       :    List[Any]          =					["TvltImageProcessor"]


if TYPE_CHECKING:
					from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
					from .processing_tvlt import TvltProcessor
					from .feature_extraction_tvlt import TvltFeatureExtractor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tvlt import (
										    TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TvltForAudioVisualClassification,
										    TvltForPreTraining,
										    TvltModel,
										    TvltPreTrainedModel,
										)

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .image_processing_tvlt import TvltImageProcessor


else:
					import sys

					snake_case_       :    Any          =					_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





