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增加keras-cv模型及训练代码  
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# Copyright 2022 The KerasCV Authors
#
# 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
#
#     https://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.

import tensorflow as tf
from absl.testing import parameterized

from keras_cv.models import convnext

from .models_test import ModelsTest

MODEL_LIST = [
    (
        convnext.ConvNeXtTiny,
        768,
        {"drop_path_rate": 0.1, "layer_scale_init_value": 1e-6},
    ),
    (
        convnext.ConvNeXtSmall,
        768,
        {
            "drop_path_rate": 0.1,
            "layer_scale_init_value": 1e-6,
        },
    ),
    (
        convnext.ConvNeXtBase,
        1024,
        {"drop_path_rate": 0.1, "layer_scale_init_value": 1e-6},
    ),
    (
        convnext.ConvNeXtLarge,
        1536,
        {"drop_path_rate": 0.1, "layer_scale_init_value": 1e-6},
    ),
    (
        convnext.ConvNeXtXLarge,
        2048,
        {"drop_path_rate": 0.1, "layer_scale_init_value": 1e-6},
    ),
]


class ConvNeXtTest(ModelsTest, tf.test.TestCase, parameterized.TestCase):
    @parameterized.parameters(*MODEL_LIST)
    def test_application_base(self, app, _, args):
        super()._test_application_base(app, _, args)

    @parameterized.parameters(*MODEL_LIST)
    def test_application_with_rescaling(self, app, last_dim, args):
        super()._test_application_with_rescaling(app, last_dim, args)

    @parameterized.parameters(*MODEL_LIST)
    def test_application_pooling(self, app, last_dim, args):
        super()._test_application_pooling(app, last_dim, args)

    @parameterized.parameters(*MODEL_LIST)
    def test_application_variable_input_channels(self, app, last_dim, args):
        super()._test_application_variable_input_channels(app, last_dim, args)

    @parameterized.parameters(*MODEL_LIST)
    def test_model_can_be_used_as_backbone(self, app, last_dim, args):
        super()._test_model_can_be_used_as_backbone(app, last_dim, args)


if __name__ == "__main__":
    tf.test.main()