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# Copyright 2023 The TensorFlow Authors. 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.
"""Test utilities for image classification tasks."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf, tf_keras
def trivial_model(num_classes):
"""Trivial model for ImageNet dataset."""
input_shape = (224, 224, 3)
img_input = tf_keras.layers.Input(shape=input_shape)
x = tf_keras.layers.Lambda(
lambda x: tf_keras.backend.reshape(x, [-1, 224 * 224 * 3]),
name='reshape')(img_input)
x = tf_keras.layers.Dense(1, name='fc1')(x)
x = tf_keras.layers.Dense(num_classes, name='fc1000')(x)
x = tf_keras.layers.Activation('softmax', dtype='float32')(x)
return tf_keras.models.Model(img_input, x, name='trivial')
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