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Allow batched calculations of physics models (#40)

* First ideas on batching

* Another pass on batching GeneralContainer

In this notebook, I take a simpler approach to try to allow batching within the
GeneralContainer class.

* Trying out GeneralContainer batching with annotations

* More flair to annotated validation

Just making sure the shapes of the arrays are adequate.

* Ignoring .DS_Store

I don't know why this only showed up now, but it's time to go...

* Batching GeneralContainer

This commit adds the functionality necessary to batch GeneralContainer objects.
Now, all variables passed to the GeneralContainer (which were always either
floats or numpy arrays) are internally converted to a new object, a
BatchedVariable, which helps getting batch size and inner dimensions of each
variable. The appropriate conversion is dependent on if the variable is annotated
as a single-valued (SingleVal) variable, or as a multi-valued one (MultiVal).
These new Annotations were also added, and should help making transient states,
inputs, and outputs batched.

* Moving BatchedVariable to utils

Before, we had issues with circular imports. By defining it in utils, we no
longer need to import things from base in utils, and from utils in base.

* Making ECMTransientVector batchable

These modifications make sure the ECM parameters are all batchable

* Including None as a possible BatchedVariable

If a value of None is passed, then a BatchedVariable object is returned with None
as the batched_values, and batch_size and inner_dimensions both set to 0.

* Converting optional transient inputs to BatchedVariable

Since everything in the GeneralContainer is assumed to be a BatchedVariable
object, we needed to make sure the optional inputs, originally just set to None,
are now BatchedVariables of None.

* Fixing optional fields for ECMInput

Similar to what we did with transient, Optional fields now have to be appropria... (continued)

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