From fc7e7c904457bec2f121b48ee5c205416f50dc47 Mon Sep 17 00:00:00 2001 From: bingyaweng Date: Thu, 17 Sep 2020 16:25:42 +0800 Subject: [PATCH] modify comments of API in mdp --- mindspore/nn/probability/bijector/power_transform.py | 3 +-- mindspore/nn/probability/dpn/vae/cvae.py | 5 +++-- mindspore/nn/probability/dpn/vae/vae.py | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/mindspore/nn/probability/bijector/power_transform.py b/mindspore/nn/probability/bijector/power_transform.py index c14c493d7b..3242ce6e9b 100644 --- a/mindspore/nn/probability/bijector/power_transform.py +++ b/mindspore/nn/probability/bijector/power_transform.py @@ -41,8 +41,7 @@ class PowerTransform(Bijector): name (str): The name of the bijector. Default: 'PowerTransform'. param (dict): The parameters used to initialize the bijector. These parameters are only used when other Bijectors inherit from powertransform to pass in parameters. In this case the derived Bijector may overwrite - the argument `param`. - Default: None. + the argument `param`. Default: None. Examples: >>> # To initialize a PowerTransform bijector of power 0.5. diff --git a/mindspore/nn/probability/dpn/vae/cvae.py b/mindspore/nn/probability/dpn/vae/cvae.py index e2b220d6fd..4996a1b7ef 100644 --- a/mindspore/nn/probability/dpn/vae/cvae.py +++ b/mindspore/nn/probability/dpn/vae/cvae.py @@ -42,8 +42,9 @@ class ConditionalVAE(Cell): num_classes(int): The number of classes. Inputs: - - **input_x** (Tensor) - The input tensor is the same shape as the input of encoder, with the shape - being :math:`(N, C, H, W)`. + - **input_x** (Tensor) - The shape of input tensor is :math:`(N, C, H, W)`, which is the same as the input of + encoder. + - **input_y** (Tensor) - The tensor of the target data, the shape is :math:`(N,)`. Outputs: diff --git a/mindspore/nn/probability/dpn/vae/vae.py b/mindspore/nn/probability/dpn/vae/vae.py index 5f5c87cf35..2993233f09 100644 --- a/mindspore/nn/probability/dpn/vae/vae.py +++ b/mindspore/nn/probability/dpn/vae/vae.py @@ -39,8 +39,8 @@ class VAE(Cell): latent_size(int): The size of the latent space. Inputs: - - **input** (Tensor) - The input tensor is the same shape as the input of encoder, the shape - is :math:`(N, C, H, W)`. + - **input** (Tensor) - The shape of input tensor is :math:`(N, C, H, W)`, which is the same as the input of + encoder. Outputs: - **output** (Tuple) - (recon_x(Tensor), x(Tensor), mu(Tensor), std(Tensor)).