import sys, os

sys.path.append(os.path.dirname(os.getcwd()))

from tensorflow import keras
import numpy as np
from pyradox import modules


def test():
    inputs = keras.Input(shape=(28, 28, 1))
    x = modules.InceptionBlock(
        [
            [(32, (1, 1), (1, 1), "same"), (32, (3, 3), (1, 1), "same")],
            [(32, (1, 1), (1, 1), "same"), (32, (3, 1), (1, 1), "same")],
            [(32, (1, 1), (1, 1), "same"), (32, (1, 3), (1, 1), "same")],
        ],
        keras.layers.AveragePooling2D(padding="same", strides=(1, 1)),
        use_bias=True,
        dropout=0.2,
    )(inputs)
    x = keras.layers.GlobalAvgPool2D()(x)
    outputs = keras.layers.Dense(10, activation="softmax")(x)

    model = keras.models.Model(inputs=inputs, outputs=outputs)

import sys, os

sys.path.append(os.path.dirname(os.getcwd()))

from tensorflow import keras
import numpy as np
from pyradox import modules


def test():
    inputs = keras.Input(shape=(28, 28, 1))
    x = modules.InceptionBlock(
        [
            [(32, (1, 1), (1, 1), "same"), (32, (3, 3), (1, 1), "same")],
            [(32, (1, 1), (1, 1), "same"), (32, (3, 1), (1, 1), "same")],
            [(32, (1, 1), (1, 1), "same"), (32, (1, 3), (1, 1), "same")],
        ],
        keras.layers.AveragePooling2D(padding="same", strides=(1, 1)),
        use_bias=True,
        dropout=0.2,
    )(inputs)
    x = keras.layers.GlobalAvgPool2D()(x)
    outputs = keras.layers.Dense(10, activation="softmax")(x)

    model = keras.models.Model(inputs=inputs, outputs=outputs)
