I have multiple trials and the shape is [1950,48](time, feature). I read the comments of function 'fit' and organize my data into a tensor [442,1950,48]. The XTrain and YTrain are the same shape. And I define the reservoir network using:
model = RCN(
num_in=48,
leaky_rate=0.1,
in_connectivity=0.1,
num_hidden=900,
rec_connectivity=0.1,
num_out=48)
It shows the error:
Scanned function carry input and carry output must have equal types (e.g. shapes and dtypes of arrays), but they differ:
the input carry component i[1899226277072] has type float64[1,900] but the corresponding output carry component has type float64[442,900], so the shapes do not match
Revise the scanned function so that all output types (e.g. shapes and dtypes) match the corresponding input types.
But when I only use 1 data [1,1950,48] to train the model, it works. How can I train the network using multiple trials?
Hello!
I have multiple trials and the shape is [1950,48](time, feature). I read the comments of function 'fit' and organize my data into a tensor [442,1950,48]. The XTrain and YTrain are the same shape. And I define the reservoir network using:
And I use the offline trainer:
It shows the error: Scanned function carry input and carry output must have equal types (e.g. shapes and dtypes of arrays), but they differ:
Revise the scanned function so that all output types (e.g. shapes and dtypes) match the corresponding input types.
But when I only use 1 data [1,1950,48] to train the model, it works. How can I train the network using multiple trials?