def construct(self, x1, x2, x3):
x1 = mnp.transpose(x1, [0, 2, 1])
x2 = x2.transpose(0, 2, 1)
x = mnp.concatenate((x1, x2, x3), -1)
x = mnp.ravel(x)
return x
def mnp_concatenate(input_tensor):
a = mnp.concatenate(input_tensor, None)
b = mnp.concatenate(input_tensor, 0)
c = mnp.concatenate(input_tensor, 1)
d = mnp.concatenate(input_tensor, 2)
return a, b, c, d
def mnp_concatenate_type_promotion(mnp_array1, mnp_array2, mnp_array3, mnp_array4):
m_concatenate = mnp.concatenate([mnp_array1,
mnp_array2,
mnp_array3,
mnp_array4], -1)
return m_concatenate
def concat(data, axis=0):
return mnp.concatenate(data, axis=axis)
