def test_resnet():
n = 4
x = Input(shape=(1, 8, 8))
y = sequential([
conv2d_block(n),
resnet(n)
])(x)
model = Model(x, y)
assert model.get_output_shape_for((None, 1, 8, 8)) == (None, n, 8, 8)
def test_conv2d_block():
x = Input(shape=(1, 8, 8))
y = sequential(
conv2d_block(4)
)(x)
model = Model(x, y)
assert model.get_output_shape_for((None, 1, 8, 8)) == (None, 4, 8, 8)
x = Input(shape=(1, 8, 8))
y = sequential(
conv2d_block(4, pooling='avg')
)(x)
model = Model(x, y)
assert model.get_output_shape_for((None, 1, 8, 8)) == (None, 4, 4, 4)
x = Input(shape=(1, 8, 8))
y = sequential(
conv2d_block(4, up=True)
)(x)
model = Model(x, y)
assert model.get_output_shape_for((None, 1, 8, 8)) == (None, 4, 16, 16)
