Feat: Neuron Operations

[ben9809]

This PR introduces the NeuronOperations metric, which calculates the computational workload associated with neuron activity in spiking neural networks (SNNs).

The metric provides two key outputs:

• Effective Neuron Ops: The total number of operations actually performed by neurons, normalized by the number of samples.
• Neuron Dense Ops: The total number of operations that would be computed if all neurons were updated at every time step, regardless of spiking activity.

Minor changes:

1. Unit tests have been added to validate the metric's functionality under various conditions, including scenarios with spiking and non-spiking inputs.

2. Lockfile was updated due to security reasons for some of the Python dependencies.

[codecov]

Codecov Report

❌ Patch coverage is 89.47368% with 4 lines in your changes missing coverage. Please review.
✅ Project coverage is 78.14%. Comparing base (4fa2cfb) to head (81f58d5).
⚠️ Report is 6 commits behind head on dev.

Files with missing lines	Patch %	Lines
neurobench/metrics/workload/neuron_operations.py	88.88%	1 Missing and 3 partials ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##              dev     #266      +/-   ##
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+ Coverage   77.63%   78.14%   +0.50%     
==========================================
  Files          43       44       +1     
  Lines         805      842      +37     
  Branches      119      123       +4     
==========================================
+ Hits          625      658      +33     
- Misses        133      134       +1     
- Partials       47       50       +3     

Flag	Coverage Δ
unittests	78.14% <89.47%> (+0.50%)	⬆️

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[jasonlyik]

Looks good, would like to see

1. How are the number of reset computes calculated for each neuron?
2. Documenting what is the diff between effective and dense Neuron Ops