removing hidden weights - not used

examples/3_NeuralNetworks/bidirectional_rnn.py

@@ -40,11 +40,9 @@ y = tf.placeholder("float", [None, n_classes])
 # Define weights
 weights = {
     # Hidden layer weights => 2*n_hidden because of foward + backward cells
-    'hidden': tf.Variable(tf.random_normal([n_input, 2*n_hidden])),
     'out': tf.Variable(tf.random_normal([2*n_hidden, n_classes]))
 }
 biases = {
-    'hidden': tf.Variable(tf.random_normal([2*n_hidden])),
     'out': tf.Variable(tf.random_normal([n_classes]))
 }
 

notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb

@@ -80,11 +80,9 @@
     "# Define weights\n",
     "weights = {\n",
     "    # Hidden layer weights => 2*n_hidden because of foward + backward cells\n",
-    "    'hidden': tf.Variable(tf.random_normal([n_input, 2*n_hidden])),\n",
     "    'out': tf.Variable(tf.random_normal([2*n_hidden, n_classes]))\n",
     "}\n",
     "biases = {\n",
-    "    'hidden': tf.Variable(tf.random_normal([2*n_hidden])),\n",
     "    'out': tf.Variable(tf.random_normal([n_classes]))\n",
     "}"
    ]
@@ -284,4 +282,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}