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)