I just started to learn tensorlayer, an excellent high-level wrapper over tensorflow framework for deep learning. Does anyone know how to do parameter gridsearch to tune DNN? Is there anyway that I can use GridSearchCV from sklearn to tune network parameters from tensorlayer? Thanks a lot.
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This is a fine question. Probably not very useful, but I have found a [distributed example of GridSearchCV with Spark](https://databricks.com/blog/2016/02/08/auto-scaling-scikit-learn-with-apache-spark.html). I didn't know about TensorLayer: Would you recommend it over Keras? – lucid_dreamer Jun 09 '17 at 22:44
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you can do something like this.
for .... (different hyper-parameter):
with tf.Graph().as_default() as graph: # clear all variables of TF
tl.layers.clear_layers_name() # clear all layer name of TL
sess = tf.InteractiveSession()
# define and train a new model here

zsdh
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