From 3f6146d194b55c9f34d9bde6e63262c4ebcd70ae Mon Sep 17 00:00:00 2001 From: Ashish Gupta Date: Tue, 22 Jan 2019 18:25:36 +0530 Subject: [PATCH 1/4] no need of if else --- learning.py | 6 ++---- 1 file changed, 2 insertions(+), 4 deletions(-) diff --git a/learning.py b/learning.py index e0d4cd26d..be0dd375c 100644 --- a/learning.py +++ b/learning.py @@ -839,10 +839,8 @@ def network(input_units, hidden_layer_sizes, output_units, activation=sigmoid): excluding input and output layers """ # Check for PerceptronLearner - if hidden_layer_sizes: - layers_sizes = [input_units] + hidden_layer_sizes + [output_units] - else: - layers_sizes = [input_units] + [output_units] + + layers_sizes = [input_units] + hidden_layer_sizes + [output_units] net = [[NNUnit(activation) for n in range(size)] for size in layers_sizes] From 62fbfdd3f367d01cc8ddbb2e92388c50595a40d1 Mon Sep 17 00:00:00 2001 From: Ashish Gupta Date: Tue, 22 Jan 2019 18:28:12 +0530 Subject: [PATCH 2/4] no need of if - else . As if hidden_layer_sizes is zero then it will not affect layer_sizes From f6425d1d4da74c157b8ffa1a89ce7a56cedce6a0 Mon Sep 17 00:00:00 2001 From: Ashish Gupta Date: Wed, 30 Jan 2019 22:53:10 +0530 Subject: [PATCH 3/4] removed comment --- learning.py | 1 - 1 file changed, 1 deletion(-) diff --git a/learning.py b/learning.py index be0dd375c..e086d44f3 100644 --- a/learning.py +++ b/learning.py @@ -838,7 +838,6 @@ def network(input_units, hidden_layer_sizes, output_units, activation=sigmoid): hidden_layers_sizes : List number of neuron units in each hidden layer excluding input and output layers """ - # Check for PerceptronLearner layers_sizes = [input_units] + hidden_layer_sizes + [output_units] From 7eedd1298aafb2bcd964a90b129df4df536fe0a5 Mon Sep 17 00:00:00 2001 From: Ashish Gupta Date: Thu, 31 Jan 2019 23:57:44 +0530 Subject: [PATCH 4/4] Update learning.py --- learning.py | 1 - 1 file changed, 1 deletion(-) diff --git a/learning.py b/learning.py index e086d44f3..898b6d2e0 100644 --- a/learning.py +++ b/learning.py @@ -838,7 +838,6 @@ def network(input_units, hidden_layer_sizes, output_units, activation=sigmoid): hidden_layers_sizes : List number of neuron units in each hidden layer excluding input and output layers """ - layers_sizes = [input_units] + hidden_layer_sizes + [output_units] net = [[NNUnit(activation) for n in range(size)]