From 91c9366589b1082e5d9d8fdc70fe46666efb69a1 Mon Sep 17 00:00:00 2001 From: Kwotsin Date: Sun, 7 May 2017 01:50:35 +0800 Subject: [PATCH] Including batch_norm as the normalizer function by default, as mentioned in function description (#9652) * fixed separable_conv2d description error and included batch_norm by default as mentioned in description * Update layers.py * Update layers.py --- tensorflow/contrib/layers/python/layers/layers.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/tensorflow/contrib/layers/python/layers/layers.py b/tensorflow/contrib/layers/python/layers/layers.py index 32ca0c38d91..3681829f657 100644 --- a/tensorflow/contrib/layers/python/layers/layers.py +++ b/tensorflow/contrib/layers/python/layers/layers.py @@ -1087,7 +1087,7 @@ def convolution2d_transpose( """Adds a convolution2d_transpose with an optional batch normalization layer. The function creates a variable called `weights`, representing the - kernel, that is convolved with the input. If `batch_norm_params` is `None`, a + kernel, that is convolved with the input. If `normalizer_fn` is `None`, a second variable called 'biases' is added to the result of the operation. Args: @@ -1847,9 +1847,9 @@ def separable_convolution2d( This op first performs a depthwise convolution that acts separately on channels, creating a variable called `depthwise_weights`. If `num_outputs` is not None, it adds a pointwise convolution that mixes channels, creating a - variable called `pointwise_weights`. Then, if `batch_norm_params` is None, - it adds bias to the result, creating a variable called 'biases', otherwise - it adds a batch normalization layer. It finally applies an activation function + variable called `pointwise_weights`. Then, if `normalizer_fn` is None, + it adds bias to the result, creating a variable called 'biases', otherwise, + the `normalizer_fn` is applied. It finally applies an activation function to produce the end result. Args: