Does this implementation support multivariate input? For example, I would like to test a multivariate time series dataset from the UCR database (FingerMovements). This data has a size of (316, 50, 28) which is (batch_size, sequence_length, features).
Does the pytorch implementation support this currently? And if not, what would be needed to add this? I'm thinking a conv2d layer replacing the conv1d is a good place to start, but the kernel size would likely need to match the number of features in one direction - i.e. using all the features and only sliding the conv kernel in the time direction. Let me know if you have any thoughts. Thanks
Does this implementation support multivariate input? For example, I would like to test a multivariate time series dataset from the UCR database (FingerMovements). This data has a size of (316, 50, 28) which is (batch_size, sequence_length, features).
Does the pytorch implementation support this currently? And if not, what would be needed to add this? I'm thinking a conv2d layer replacing the conv1d is a good place to start, but the kernel size would likely need to match the number of features in one direction - i.e. using all the features and only sliding the conv kernel in the time direction. Let me know if you have any thoughts. Thanks