Tensorcore support is on our list of future enhancements. However, in order to add tensorcore support we need to replace a good chunk of code. Part of the problem is that the version of Keras we use does not support Tensorcores, but we can't change to the newer version without removing AMD support. That's not really a great option, so we will have to build some sort of abstraction layer to avoid removing support for our AMD users.
The advantage of tensorcores is a good speed increase, but it will actually lose some accuracy/fidelity (though this can be mitigated somewhat).
Tensorcore support is on our list of future enhancements. However, in order to add tensorcore support we need to replace a good chunk of code. Part of the problem is that the version of Keras we use does not support Tensorcores, but we can't change to the newer version without removing AMD support. That's not really a great option, so we will have to build some sort of abstraction layer to avoid removing support for our AMD users.
The advantage of tensorcores is a good speed increase, but it will actually lose some accuracy/fidelity (though this can be mitigated somewhat).
Tensorcore support is on our list of future enhancements. However, in order to add tensorcore support we need to replace a good chunk of code. Part of the problem is that the version of Keras we use does not support Tensorcores, but we can't change to the newer version without removing AMD support. That's not really a great option, so we will have to build some sort of abstraction layer to avoid removing support for our AMD users.
The advantage of tensorcores is a good speed increase, but it will actually lose some accuracy/fidelity (though this can be mitigated somewhat).
Is there any build of keras that would automagically add support for tensor cores while maintaining the same version you are using? Something like...