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one question I want to ask is why the weighted sampling reader requires all reader have the exact same schema ? Can we modify it so that each reader have different schemas ?
The text was updated successfully, but these errors were encountered:
say i want to have a reader A contains schema (a,b,c) while another reader B schema contains (a,b,c,d). Can they both be sampled together ? The extra field in B will be used on extra loss function defined in the network.
It was design that way to support old TF reading style : the schema must have been known in advance to hook the reader into TF graph. This might not be necessary when not reading from TF. If you'd like to propose a PR, I would be happy to take a look.
one question I want to ask is why the weighted sampling reader requires all reader have the exact same schema ? Can we modify it so that each reader have different schemas ?
The text was updated successfully, but these errors were encountered: