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mindspore/docs/api/api_python/nn/mindspore.nn.Vjp.rst

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mindspore.nn.Vjp
=================
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.. py:class:: mindspore.nn.Vjp(fn)
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<20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>ſɱȻ<C9B1>(vector-Jacobian product, VJP)<29><>VJP<4A><50>Ӧ `<60><><EFBFBD><EFBFBD>ģʽ<C4A3>Զ<EFBFBD>΢<EFBFBD><CEA2> <https://mindspore.cn/docs/programming_guide/zh-CN/master/design/gradient.html#id4>`_<EFBFBD><EFBFBD>
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**<2A><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>**
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- **fn** (Cell) - <20><><EFBFBD><EFBFBD>Cell<6C><6C><EFBFBD><EFBFBD><EFBFBD>磬<EFBFBD><E7A3AC><EFBFBD>ڽ<EFBFBD><DABD><EFBFBD>Tensor<6F><72><EFBFBD>벢<EFBFBD><EBB2A2><EFBFBD><EFBFBD>Tensor<6F><72><EFBFBD><EFBFBD>TensorԪ<72>顣
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**<2A><><EFBFBD>룺**
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- **inputs** (Tensor) - <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Σ<EFBFBD><CEA3><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Tensor<6F><72>
- **v** (Tensor or Tuple of Tensor) - <20><><EFBFBD>ſɱȾ<C9B1><C8BE><EFBFBD><EFBFBD><EFBFBD><EFBFBD>˵<EFBFBD><CBB5><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>Shape<70><65><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>һ<EFBFBD>¡<EFBFBD>
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**<2A><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>**
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2<><32>Tensor<6F><72>TensorԪ<72>鹹<EFBFBD>ɵ<EFBFBD>Ԫ<EFBFBD>顣
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- **net_output** (Tensor or Tuple of Tensor) - <20><><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD><EFBFBD>
- **vjp** (Tensor or Tuple of Tensor) - <20><><EFBFBD><EFBFBD><EFBFBD>ſɱȻ<C9B1><C8BB>Ľ<EFBFBD><C4BD><EFBFBD><EFBFBD><EFBFBD>
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**֧<><D6A7>ƽ̨<C6BD><CCA8>**
``Ascend`` ``GPU`` ``CPU``
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**<2A><><EFBFBD><EFBFBD><EFBFBD><EFBFBD>**
>>> from mindspore.nn import Vjp
>>> class Net(nn.Cell):
... def construct(self, x, y):
... return x**3 + y
>>> x = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
>>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
>>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
>>> output = Vjp(Net())(x, y, v)