How to convert PyObject into a Julia array import PyCall tf = PyCall.pyimport("tensorflow") o = tf[:random_normal]((3,3)) PyObject <tf.Tensor: id=27, shape=(3, 3), dtype=float32, numpy= array([[0.02705349, 0.3173014 , 0.48765275], [0.03795605, 0.7796892 , 0.01696282], [0.9305789 , 0.3…

Convert it to a numpy array python - Convert a tensor to numpy array in Tensorflow? - Stack Overflow PyCall then automatically converts it to a Julia’s Array (provided that element type can be converted).

it does not seem to work: import PyCall tf = PyCall.pyimport("tensorflow") o = tf[:random_normal]((3,3))[:eval] PyObject <tf.Tensor: id=27, shape=(3, 3), dtype=float32, numpy= array([[0.02705349, 0.3173014 , 0.48765275], [0.03795605, 0.7796892 , 0.01696282], [0.9305789 , 0.3821437 , 0…

Don’t you need to execute the eval function as well?

actually this is what works: o = tf[:random_normal]((3,3))[:numpy]() 3×3 Array{Float32,2}: -1.35462 -0.0406312 -0.993727 -0.8862 1.15086 -1.85081 0.461948 -1.41717 -0.993305 Thank you very much!

I found the answer from the issue on the TensorFlow-Examples. https://github.com/aymericdamien/TensorFlow-Examples/issues/40#issuecomment-405892316 so using PyCall in that way. using PyCall tf = pyimport("tensorflow") o = tf[:random_normal]((3,3)) @pyimport tensorflow.python.keras.backend as K se…

Converting PyObject to a Julia array

General Usage Performance

kristoffer.carlsson December 8, 2018, 12:56am 2

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Converting PyObject to a Julia array

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