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Neither LSTM or RNN do not work (different errors) #640
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@erichiller Need to wait for those model to be fixed. Recently we're focused on building CNN model in Keras functional API. |
Ok, thanks! |
@erichiller If possible, you need to get familiar with porting Unit Tests from native from google to Tensorflow.NET as discussed here. Then if will have the "helicopter" view where are the missing parts and where the community can contribute in complementary way. |
@erichiller I think you can get started with just a simple unit test (from docs) like: inputs = np.random.random([32, 10, 8]).astype(np.float32)
simple_rnn = tf.keras.layers.SimpleRNN(4)
output = simple_rnn(inputs) # The output has shape `[32, 4]`. Absolutely we can help even you PR the buggy code. |
Closing due to RNN and LSTM has been developed, please reopen if you still have question, thanks! |
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I was running through the examples , particularly DigitRecognitionLSTM and DigitRecognitionRNN as well as the Keras version and am unable to get any of these to work.
The CNN example for image processing does work.
I can open multiple issues if you'd like, as they are quite different.
The below 3 issues are straight copies of the aforementioned examples.
DigitRecognitionRNN
This seems to be erroring about there being no "Trainable Variables"
DigitRecognitionLSTM
This appears to be an issue with reshaping and the
batch_size
being invalid.Keras LSTM
This seems to be occurring because
vendor\TensorFlow.NET\src\TensorFlowNET.Core\Keras\Layers\LSTM.cs
does not implement the required method (Call
inTensorFlow.NET\src\TensorFlowNET.Core\Keras\Engine\Layer.cs
, line 160) , I am guessing that this part of the library is not yet complete?Let me know if I'm doing something wrong on my end too, or if I can help in some way.
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