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This option doesn't work correctly on some situation.
On single use is OK.
x = layers.LSTM(128, return_sequences=True,use_cudnn=False)(x)
But on complex is not.
x = layers.Bidirectional(layers.LSTM(128, return_sequences=True,use_cudnn=False))(x)
The layers.Bidirectional() calls layers.LSTM 3 times at one operation.
use_cudnn=False <-- first call is good.
use_cudnn=Auto <-- second call is no good.
use_cudnn=Auto <-- third call is no good.
Thus, how do i resolve this problem?
I think.
An one way is to change LSTM init param in direct.
class LSTM(RNN):
....
def __init__(
....
#use_cudnn="auto",
use_cudnn=False,
The other way is,I want,
to add a use_cudnn option to Model.compile option like jit_compile option.
Hi Keras!
About https://keras.io/api/layers/recurrent_layers/lstm/
option
use_cudnn=False
This option doesn't work correctly on some situation.
On single use is OK.
x = layers.LSTM(128, return_sequences=True,use_cudnn=False)(x)
But on complex is not.
x = layers.Bidirectional(layers.LSTM(128, return_sequences=True,use_cudnn=False))(x)
The layers.Bidirectional() calls layers.LSTM 3 times at one operation.
use_cudnn=False <-- first call is good.
use_cudnn=Auto <-- second call is no good.
use_cudnn=Auto <-- third call is no good.
Thus, how do i resolve this problem?
I think.
An one way is to change LSTM init param in direct.
The other way is,I want,
to add a use_cudnn option to Model.compile option like jit_compile option.
My PC
Ubuntu 22.04
Python 3.10.12
virtual env
keras 3.7.0
tensorflow 2.16.2
cuDNN v8.9.6
I am looking forward for your answer.
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