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!3442 bug fix for quant.py in train/ and nn/ 

Merge pull request !3442 from chenzhongming/master
This commit is contained in:
mindspore-ci-bot 2020-07-25 09:11:16 +08:00 committed by Gitee
parent ea545dc52f b8686fc5bf
commit 0fac402a1a
1 changed files with 7 additions and 7 deletions
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14
mindspore/nn/layer/quant.py
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@ -83,7 +83,7 @@ class Conv2dBnAct(Cell):
Initializer and string are the same as 'weight_init'. Refer to the values of
Initializer for more details. Default: 'zeros'.
has_bn (bool): Specifies to used batchnorm or not. Default: False.
activation (string): Specifies activation type. The optional values are as following:
activation (Cell): Specifies activation type. The optional values are as following:
'softmax', 'logsoftmax', 'relu', 'relu6', 'tanh', 'gelu', 'sigmoid',
'prelu', 'leakyrelu', 'hswish', 'hsigmoid'. Default: None.
@ -170,7 +170,7 @@ class DenseBnAct(Cell):
bias_init (Union[Tensor, str, Initializer, numbers.Number]): The trainable bias_init parameter. The dtype is
same as input x. The values of str refer to the function `initializer`. Default: 'zeros'.
has_bias (bool): Specifies whether the layer uses a bias vector. Default: True.
activation (str): Regularizer function applied to the output of the layer, eg. 'relu'. Default: None.
activation (Cell): Regularizer function applied to the output of the layer, eg. 'relu'. Default: None.
has_bn (bool): Specifies to used batchnorm or not. Default: False.
activation (string): Specifies activation type. The optional values are as following:
'softmax', 'logsoftmax', 'relu', 'relu6', 'tanh', 'gelu', 'sigmoid',
@ -403,8 +403,8 @@ class Conv2dBatchNormQuant(Cell):
out_channels (int): The number of output channel :math:`C_{out}`.
kernel_size (Union[int, tuple]): Specifies the height and width of the 2D convolution window.
stride (int): Specifies stride for all spatial dimensions with the same value.
pad_mode: (str): Specifies padding mode. The optional values are "same", "valid", "pad". Default: "same".
padding: (int): Implicit paddings on both sides of the input. Default: 0.
pad_mode (str): Specifies padding mode. The optional values are "same", "valid", "pad". Default: "same".
padding (int): Implicit paddings on both sides of the input. Default: 0.
eps (float): Parameters for BatchNormal. Default: 1e-5.
momentum (float): Parameters for BatchNormal op. Default: 0.997.
weight_init (Union[Tensor, str, Initializer, numbers.Number]): Initializer for the
@ -590,8 +590,8 @@ class Conv2dQuant(Cell):
out_channels (int): The number of output channel :math:`C_{out}`.
kernel_size (Union[int, tuple]): Specifies the height and width of the 2D convolution window.
stride (int): Specifies stride for all spatial dimensions with the same value. Default: 1.
pad_mode: (str): Specifies padding mode. The optional values are "same", "valid", "pad". Default: "same".
padding: (int): Implicit paddings on both sides of the input. Default: 0.
pad_mode (str): Specifies padding mode. The optional values are "same", "valid", "pad". Default: "same".
padding (int): Implicit paddings on both sides of the input. Default: 0.
dilation (int): Specifying the dilation rate to use for dilated convolution. Default: 1.
group (int): Split filter into groups, `in_ channels` and `out_channels` should be
divisible by the number of groups. Default: 1.
@ -989,7 +989,7 @@ class HSigmoidQuant(_QuantActivation):
symmetric=symmetric,
narrow_range=narrow_range,
quant_delay=quant_delay)
if issubclass(activation, nn.HSwish):
if issubclass(activation, nn.HSigmoid):
self.act = activation()
else:
raise ValueError("Activation should be `nn.HSigmoid`")