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You can execute Python via the Execute Python extension. So you can use Tensor via that extension.
TensorFlow recently released an initial API for Java so you could develop your own extension for RapidMiner.
Thanks Thomas. I have seen the small Python scripts integrating into a RapidMiner process. However, is it possible to convert a whole Python project into RapidMiner "blocks", in order to take advantage of RapidMiner flexibility and powerful visualization tools?
Yes. We have quite a few customers that use Python and R inside RapidMiner Studio and Server. If you check out the Cappius webinar, they did just that. They took R scripts and some other scripts and put them all into RapidMiner to operationalize it.
### An example of building a TensorFlow model from R using rPython ###
# For this script you need to
# 1. Have python 2.7 installed.
# 2. Install the rPython package in R.
# 3. Install Google's TensorFlow library as per these instructions:
### Here is how to setup and run a trivial TensorFlow model ###
# Load TensorFlow (I couldn't get this to work without setting sys.argv... )
sys.argv = ['']
import tensorflow as tf
# Define a "hello world" TensorFlow model adding two numbers
a = tf.constant(10)
b = tf.constant(32)
sum = a + b
#Instantiate a TensorFlow session, and get the result into R.
# (we need the .tolist() to convert from the result into something
# that can be serialized by JSON and imported into R)
sess = tf.Session()
result = sess.run(sum)
result = python.get("result.tolist()")
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