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authorLester Solbakken <lesters@oath.com>2019-06-19 15:56:24 +0200
committerLester Solbakken <lesters@oath.com>2019-06-19 15:56:24 +0200
commit6ad990b0309d673a279f9a1308f6029d028c11b7 (patch)
tree77beff42b429d73521e1cc4942c86eb71cc9fbdd /model-integration
parentfb094bd5f31a5b9dee97a95473be8eae9ada9544 (diff)
Remove outdated comment
Diffstat (limited to 'model-integration')
-rw-r--r--model-integration/src/test/models/tensorflow/softmax/softmax.py4
1 files changed, 1 insertions, 3 deletions
diff --git a/model-integration/src/test/models/tensorflow/softmax/softmax.py b/model-integration/src/test/models/tensorflow/softmax/softmax.py
index c636af58043..aab9956f914 100644
--- a/model-integration/src/test/models/tensorflow/softmax/softmax.py
+++ b/model-integration/src/test/models/tensorflow/softmax/softmax.py
@@ -9,11 +9,9 @@ n_inputs = 5
n_outputs = 3
input = tf.placeholder(tf.float32, shape=(None, n_inputs), name="input")
-
-W = tf.Variable(tf.random.uniform([n_inputs, n_outputs]), name="weights") # or just add uniform random
+W = tf.Variable(tf.random.uniform([n_inputs, n_outputs]), name="weights")
b = tf.Variable(tf.random.uniform([n_outputs]), name="bias")
Z = tf.matmul(input, W) + b
-
hidden_layer = tf.nn.relu(Z)
output_layer = tf.nn.softmax(hidden_layer, name="output")