Merge pull request !423 from lvmingfu/code_docs_0926pull/418/MERGE
@@ -36,8 +36,8 @@ class SuppressMasker(Callback): | |||||
Examples: | Examples: | ||||
>>> import mindspore.nn as nn | >>> import mindspore.nn as nn | ||||
>>> import mindspore.ops.operations as P | |||||
>>> from mindspore import context | |||||
>>> import mindspore as ms | |||||
>>> from mindspore import set_context, ops | |||||
>>> from mindspore.nn import Accuracy | >>> from mindspore.nn import Accuracy | ||||
>>> from mindarmour.privacy.sup_privacy import SuppressModel | >>> from mindarmour.privacy.sup_privacy import SuppressModel | ||||
>>> from mindarmour.privacy.sup_privacy import SuppressMasker | >>> from mindarmour.privacy.sup_privacy import SuppressMasker | ||||
@@ -46,14 +46,14 @@ class SuppressMasker(Callback): | |||||
>>> class Net(nn.Cell): | >>> class Net(nn.Cell): | ||||
... def __init__(self): | ... def __init__(self): | ||||
... super(Net, self).__init__() | ... super(Net, self).__init__() | ||||
... self._softmax = P.Softmax() | |||||
... self._softmax = ops.Softmax() | |||||
... self._Dense = nn.Dense(10,10) | ... self._Dense = nn.Dense(10,10) | ||||
... self._squeeze = P.Squeeze(1) | |||||
... self._squeeze = ops.Squeeze(1) | |||||
... def construct(self, inputs): | ... def construct(self, inputs): | ||||
... out = self._softmax(inputs) | ... out = self._softmax(inputs) | ||||
... out = self._Dense(out) | ... out = self._Dense(out) | ||||
... return self._squeeze(out) | ... return self._squeeze(out) | ||||
>>> context.set_context(mode=context.PYNATIVE_MODE, device_target="GPU") | |||||
>>> set_context(mode=ms.PYNATIVE_MODE, device_target="GPU") | |||||
>>> network = Net() | >>> network = Net() | ||||
>>> masklayers = [] | >>> masklayers = [] | ||||
>>> masklayers.append(MaskLayerDes("_Dense.weight", 0, False, True, 10)) | >>> masklayers.append(MaskLayerDes("_Dense.weight", 0, False, True, 10)) | ||||
@@ -66,8 +66,8 @@ class SuppressPrivacyFactory: | |||||
Examples: | Examples: | ||||
>>> import mindspore.nn as nn | >>> import mindspore.nn as nn | ||||
>>> import mindspore.ops.operations as P | |||||
>>> from mindspore import context | |||||
>>> import mindspore as ms | |||||
>>> from mindspore import set_context, ops | |||||
>>> from mindspore.nn import Accuracy | >>> from mindspore.nn import Accuracy | ||||
>>> from mindarmour.privacy.sup_privacy import SuppressPrivacyFactory | >>> from mindarmour.privacy.sup_privacy import SuppressPrivacyFactory | ||||
>>> from mindarmour.privacy.sup_privacy import MaskLayerDes | >>> from mindarmour.privacy.sup_privacy import MaskLayerDes | ||||
@@ -75,14 +75,14 @@ class SuppressPrivacyFactory: | |||||
>>> class Net(nn.Cell): | >>> class Net(nn.Cell): | ||||
... def __init__(self): | ... def __init__(self): | ||||
... super(Net, self).__init__() | ... super(Net, self).__init__() | ||||
... self._softmax = P.Softmax() | |||||
... self._softmax = ops.Softmax() | |||||
... self._Dense = nn.Dense(10,10) | ... self._Dense = nn.Dense(10,10) | ||||
... self._squeeze = P.Squeeze(1) | |||||
... self._squeeze = ops.Squeeze(1) | |||||
... def construct(self, inputs): | ... def construct(self, inputs): | ||||
... out = self._softmax(inputs) | ... out = self._softmax(inputs) | ||||
... out = self._Dense(out) | ... out = self._Dense(out) | ||||
... return self._squeeze(out) | ... return self._squeeze(out) | ||||
>>> context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU") | |||||
>>> set_context(mode=ms.PYNATIVE_MODE, device_target="CPU") | |||||
>>> network = Net() | >>> network = Net() | ||||
>>> masklayers = [] | >>> masklayers = [] | ||||
>>> masklayers.append(MaskLayerDes("_Dense.weight", 0, False, True, 10)) | >>> masklayers.append(MaskLayerDes("_Dense.weight", 0, False, True, 10)) | ||||