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- import numpy as np
- from mindspore import context, nn, Tensor, Parameter
- from mindspore.common import dtype as mstype
- from mindspore.ops import operations as P
-
-
- context.set_context(mode=context.GRAPH_MODE, save_graphs=False)
-
- class Net(nn.Cell):
- def __init__(self, data):
- super(Net, self).__init__()
- self.start = Tensor(0, dtype=mstype.int32)
- self.end = Tensor(2, dtype=mstype.int32)
- self.max_output = Parameter(data, "output_x")
- self.upd = P.ScatterNdUpdate()
- self.zero = Tensor(np.ones([1], dtype=np.int32))
-
- def construct(self, inputs):
- idx = self.start
- end = self.end
- while idx < end:
- xi = inputs[idx, :, :]
- self.upd(self.max_output, idx + self.zero, xi)
- idx = idx + 1
- return self.max_output + 0
-
-
- def test_x():
- x = Tensor(np.arange(10 * 2 * 3).reshape(10, 2, 3).astype(np.float32))
- net = Net(x)
- net(x)
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