Reshape should take each shape dimension as a separate input

Description

Reshape has only two inputs, x, and a vector of the output shape. This is cumbersome because many times we want to analyze the individual dimensions to rewrite Reshape as expand_dims or get rid of useless Reshape. Also the Reshape Op needs to be parametrized with the output length, because historically we didn't have static shapes, and couldn't always guess how many entries the shape vector had.

Most times Reshape is used to concatenate dimensions, so we end up with stuff like [x.shape[0], ..., x.shape[n] * x.shape[m], ..., x.shape[-1]], wrapped in a MakeVector. This makes Resahpe rewrites harder because they have to handle the case where things are joined in a MakeVector or may have been constant folded into a single tensor.

https://github.com/pymc-devs/pytensor/blob/bf73f8a06be2adf1d30e4f59e30c2dfa49c5204e/pytensor/tensor/rewriting/shape.py#L921-L926

SpecifyShape already works with a variable number of inputs and we haven't any trouble with it.

Start by reading the shape rewrite at pytensor/tensor/rewriting/shape.py around lines 921-926, then inspect the existing Reshape and SpecifyShape interfaces. Determine how Reshape can accept separate dimension inputs while preserving an explicit output length, and verify that shape rewrites no longer depend on MakeVector handling.