def mnp_reshape(input_tensor):
a = mnp.reshape(input_tensor, (3, 8))
b = mnp.reshape(input_tensor, [3, -1])
c = mnp.reshape(input_tensor, (-1, 12))
d = mnp.reshape(input_tensor, (-1, ))
e = mnp.reshape(input_tensor, 24)
f = mnp.reshape(input_tensor, [2, 4, -1])
return a, b, c, d, e, f
def mnp_reshape(input_tensor):
a = mnp.reshape(input_tensor, (3, 8))
b = mnp.reshape(input_tensor, [3, -1])
c = mnp.reshape(input_tensor, (-1, 12))
d = mnp.reshape(input_tensor, (-1,))
e = mnp.reshape(input_tensor, 24)
f = mnp.reshape(input_tensor, [2, 4, -1])
g = input_tensor.reshape(3, 8)
h = input_tensor.reshape(3, -1)
i = input_tensor.reshape([-1, 3])
j = input_tensor.reshape(-1)
return a, b, c, d, e, f, g, h, i, j
def construct(self, x):
x = mnp.expand_dims(x, 2)
x = mnp.reshape(x, (1, 2, 3, 4, 1, 1))
x = mnp.squeeze(x)
return x