marten | NET Transactional Document DB and Event Store on PostgreSQL | Microservice library

This function is an implementation of the following method:

The best random initialization scheme we found was one of our own design, "sparse initialization". In this scheme we hard limit the number of non-zero incoming connection weights to each unit (we used 15 in our experiments) and set the biases to 0 (or 0.5 for tanh units).

• Deep learning via Hessian-free optimization - Martens, J. (2010).

The reason it is not supported for higher order tensors is because it maintains the same proportion of zeros in each column, and it is not clear which [subset of] dimensions this condition should be maintained across for higher order tensors.

You can implement this initialization strategy with dropout or an equivalent function e.g:

Based on the xml doc it is just a convenience method:

Convenience method to create a new "lightweight" IDocumentSession with no IdentityMap or automatic dirty checking

In the current implementation it just calls OpenSession with DocumentTracking set to DocumentTracking.None.

Also from the troubleshooting docs:

From

IDocumentStore.OpenSession

Characteristics:

Defaults to session that tracks objects by their identity, DocumentTracking.IdentityOnly, with isolation level of Read Committed.

Use: Reading & writing data. Objects within a session are cached by their identity. Updates to objects are explicitly controlled through session operations (IDocumentSession.Update, IDocumentSession.Store). With the defaults, incurs lower overhead than DirtyTrackedSession.

And

From

IDocumentStore.LightweightSession

Characteristics:

No change tracking, DocumentTracking.None, with the default isolation level of Read Committed.

Use: Reading & writing data. No caching of objects is done within a session, e.g. repeated loads using the same document identity yield separate objects, each hydrated from the database. In case of updates to such objects, the last object to be stored will overwrite any pending changes from previously stored objects of the same identity. Can incur lower overhead than tracked sessions.

If you just want to get pairs of &str for the names of the departments and the employees, you can use an iterator chain like so:

That's a perfect job for a loop. You have to create helper functions that generate random names and prices and types.

For the name, we'll use:

As I said, no merging required in this problem. Also, I would recommend using data.table package to solve your problem, once it's simpler to perform modifications at specific rows based on conditions.

A solution using data.table would be:

You seem to want to match the same amount of chars on the left and right and then some chars in the middle, but this is not possible with PostgreSQL regex.

To find records that contain any of the characters in a pre-defined set, you may use SIMILAR TO with a %[qwerty]% pattern:

Confirmed this is fixed in 6.2.2.