forked from mindspore-Ecosystem/mindspore
!25769 Fix document for Jvp and Vjp
Merge pull request !25769 from LiangZhibo/code_docs_master
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@ -55,9 +55,13 @@ class Jvp(Cell):
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Outputs:
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A tuple with 2 Tensors or Tuple of Tensors:
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- **net_output** (Tensors or Tuple of Tensors) - The output of `network(inputs)`.
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- **jvp** (Tensors or Tuple of Tensors) - The result of the jacobian vector product.
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Supported Platforms:
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``Ascend`` ``GPU`` ``CPU``
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Examples:
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>>> from mindspore.nn import Jvp
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>>> class Net(nn.Cell):
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@ -67,6 +71,10 @@ class Jvp(Cell):
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>>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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>>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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>>> output = Jvp(Net())(x, y, (v, v))
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>>> print(output[0])
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[[2, 10], [20, 68]]
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>>> print(output[1])
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[[4, 13], [28, 49]]
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"""
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def __init__(self, fn):
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super(Jvp, self).__init__()
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@ -119,9 +127,13 @@ class Vjp(Cell):
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Outputs:
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A tuple with 2 Tensors or Tuple of Tensors:
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- **net_output** (Tensors or Tuple of Tensors) - The output of `network(inputs)`.
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- **vjp** (Tensors or Tuple of Tensors) - The result of the dot product.
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Supported Platforms:
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``Ascend`` ``GPU`` ``CPU``
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Examples:
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>>> from mindspore.nn import Vjp
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>>> class Net(nn.Cell):
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@ -131,6 +143,10 @@ class Vjp(Cell):
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>>> y = Tensor(np.array([[1, 2], [3, 4]]).astype(np.float32))
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>>> v = Tensor(np.array([[1, 1], [1, 1]]).astype(np.float32))
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>>> output = Vjp(Net())(x, y, v)
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>>> print(output[0])
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[[2, 10], [20, 68]]
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>>> print(output[1])
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([[3, 12], [27, 48]], [[1, 1], [1, 1]])
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"""
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def __init__(self, fn):
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