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@@ -85,9 +85,14 @@ class Conv2dBnAct(Cell): |
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Initializer and string are the same as 'weight_init'. Refer to the values of |
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Initializer and string are the same as 'weight_init'. Refer to the values of |
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Initializer for more details. Default: 'zeros'. |
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Initializer for more details. Default: 'zeros'. |
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has_bn (bool): Specifies to used batchnorm or not. Default: False. |
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has_bn (bool): Specifies to used batchnorm or not. Default: False. |
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momentum (float): Momentum for moving average.Momentum value should be [0, 1].Default:0.9 |
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eps (float): Term added to the denominator to improve numerical stability. Should be greater than 0. Default: |
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1e-5. |
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activation (Cell): Specifies activation type. The optional values are as following: |
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activation (Cell): Specifies activation type. The optional values are as following: |
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'softmax', 'logsoftmax', 'relu', 'relu6', 'tanh', 'gelu', 'sigmoid', |
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'softmax', 'logsoftmax', 'relu', 'relu6', 'tanh', 'gelu', 'sigmoid', |
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'prelu', 'leakyrelu', 'hswish', 'hsigmoid'. Default: None. |
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'prelu', 'leakyrelu', 'hswish', 'hsigmoid'. Default: None. |
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alpha (float): Slope of the activation function at x < 0. Default: 0.2. |
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after_fake(bool): Determin whether there should be a fake quantization operation after Cond2dBnAct. |
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Inputs: |
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Inputs: |
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- **input** (Tensor) - Tensor of shape :math:`(N, C_{in}, H_{in}, W_{in})`. |
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- **input** (Tensor) - Tensor of shape :math:`(N, C_{in}, H_{in}, W_{in})`. |
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@@ -171,6 +176,7 @@ class DenseBnAct(Cell): |
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activation (string): Specifies activation type. The optional values are as following: |
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activation (string): Specifies activation type. The optional values are as following: |
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'Softmax', 'LogSoftmax', 'ReLU', 'ReLU6', 'Tanh', 'GELU', 'Sigmoid', |
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'Softmax', 'LogSoftmax', 'ReLU', 'ReLU6', 'Tanh', 'GELU', 'Sigmoid', |
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'PReLU', 'LeakyReLU', 'h-Swish', and 'h-Sigmoid'. Default: None. |
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'PReLU', 'LeakyReLU', 'h-Swish', and 'h-Sigmoid'. Default: None. |
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after_fake(bool): Determin whether there should be a fake quantization operation after DenseBnAct. |
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Inputs: |
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Inputs: |
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- **input** (Tensor) - Tensor of shape :math:`(N, in\_channels)`. |
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- **input** (Tensor) - Tensor of shape :math:`(N, in\_channels)`. |
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