tensors

I would like to convert a DataFrame to a JSON object the same way that Pandas does with to_dict().

toJSON() treats rows as elements in an array, and ignores the index labels. But to_dict() uses the index as keys.

Here is an example of what I have in mind:

function to_dict(df) {
    const rows = df.toJSON();
    const entries = df.index.map((e, i) => ({ [e]: rows[i] }));
  

Issue to track tutorial requests:

• Deep Learning with PyTorch: A 60 Minute Blitz - #69
• Sentence Classification - #79

We should just return x, when all the shapes passed into specify_shape are None as this won't do anything.

import aesara.tensor as at

x = at.matrix("x")
y = at.specify_shape(x, (None, None))
assert y is x

This has the potential to simplify internal code, and avoid some rewrites to remove useless specify_shapes

Related
#870

Feature functionality
As per #945, it is possible to pass a condition to _operations.__binary_op via the kwarg where. This feature is available in ht.divide. Extend feature to all operations calling _operations.__binary_op, if the numpy API calls for it.