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Update dynamic_rnn.py
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examples/3_NeuralNetworks/dynamic_rnn.py

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@@ -146,7 +146,7 @@ def dynamicRNN(x, seqlen, weights, biases):
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# Indexing
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outputs = tf.gather(tf.reshape(outputs, [-1, n_hidden]), index)
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# Linear activation, using rnn inner loop last output
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# Linear activation, using outputs computed above
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return tf.matmul(outputs, weights['out']) + biases['out']
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pred = dynamicRNN(x, seqlen, weights, biases)

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