Function pippin_28_28

tools/tensorflow-quantization/tests/network_pool.py:263–277

()

def pippin_28_28():
    input_img = tf.keras.layers.Input(shape=(28, 28))
    x = tf.keras.layers.Reshape(target_shape=(28, 28, 1))(input_img)
    x = tf.keras.layers.Conv2D(filters=12, kernel_size=(3, 3))(x)
    x = relu_bn(x)
    x = tf.keras.layers.Conv2D(filters=24, kernel_size=(3, 3))(x)
    x = relu_bn(x)
    x = identity_block_bn(x)
    x = identity_block_short_conv_bn(x)
    x = tf.keras.layers.MaxPooling2D(pool_size=(2, 2))(x)
    x = tf.keras.layers.Flatten()(x)
    x = tf.keras.layers.Dense(100)(x)
    x = tf.keras.layers.ReLU()(x)
    x = tf.keras.layers.Dense(10)(x)
    return tf.keras.Model(input_img, x, name="Pippin")