def test_concatenate():
model = nn.HybridConcatenate(axis=1)
model.add(nn.Dense(128, activation='tanh', in_units=10))
model.add(nn.Dense(64, activation='tanh', in_units=10))
model.add(nn.Dense(32, in_units=10))
model2 = nn.Concatenate(axis=1)
model2.add(nn.Dense(128, activation='tanh', in_units=10))
model2.add(nn.Dense(64, activation='tanh', in_units=10))
model2.add(nn.Dense(32, in_units=10))
# ndarray
model.initialize(mx.init.Xavier(magnitude=2.24))
model2.initialize(mx.init.Xavier(magnitude=2.24))
x = model(mx.np.zeros((32, 10)))
x2 = model2(mx.np.zeros((32, 10)))
assert x.shape == (32, 224)
assert x2.shape == (32, 224)
x.wait_to_read()
x2.wait_to_read()
def __init__(self, input_num, dim, **kwargs):
super(SingleConcat, self).__init__(**kwargs)
self.concat = nn.HybridConcatenate(axis=dim)
for i in range(input_num):
self.concat.add(nn.Identity())