Improve code readability for generic solver module

src/lava/lib/optimization/solvers/generic/builder.py

@@ -153,6 +153,8 @@ def constructor(
             name: ty.Optional[str] = None,
             log_config: ty.Optional[LogConfig] = None,
         ) -> None:
+            # TODO try method extraction to simplify some methods might be
+            #  useful for both proc and model constructors
             super(type(self), self).__init__(
                 backend=backend,
                 hyperparameters=hyperparameters,
@@ -229,6 +231,8 @@ def _create_model_constructor(self, target_cost: int):
         """
 
         def constructor(self, proc):
+            # TODO try method extraction to simplify some methods might be
+            #  useful for both proc and model constructors
             discrete_var_shape = None
             if hasattr(proc, "discrete_variables"):
                 discrete_var_shape = proc.discrete_variables.shape

src/lava/lib/optimization/solvers/generic/dataclasses.py

@@ -14,6 +14,8 @@
 from lava.proc.dense.process import Dense
 
 
+# TODO  convert all these into subproc models, move to
+#  hierarchical_processes.py file and delete dataclasses.py
 @dataclass
 class CostMinimizer:
     """Processes implementing an optimization problem's cost function."""

src/lava/lib/optimization/solvers/generic/nebm/process.py

@@ -57,6 +57,7 @@ def __init__(
         # Initial state determined in DiscreteVariables
         self.state = Var(shape=shape, init=init_state.astype(int))
 
+        # TODO:  is this property indented wrongly?
         @property
         def shape(self) -> ty.Tuple[int, ...]:
             return self.proc_params["shape"]
@@ -124,7 +125,7 @@ def __init__(
         )
 
         self.temperature = Var(shape=shape, init=int(max_temperature))
-
+        # TODO we can avoid line breaking by adding an intermediary variable
         self.refract_counter = Var(
             shape=shape,
             init=(refract or 0)
@@ -141,6 +142,8 @@ def __init__(
             else np.zeros(shape=shape, dtype=int),
         )
 
+
+        # TODO here too, is this property idented wrongly?
         @property
         def shape(self) -> ty.Tuple[int, ...]:
             return self.proc_params["shape"]

src/lava/lib/optimization/solvers/generic/qp/models.py

@@ -197,7 +197,9 @@ def __init__(self, proc):
             shape=shape_constraint_matrix_T,
             weights=constraint_matrix_T,
         )
-
+        # TODO: perform method extraction, this is doing more than one thing
+        #  by definition. Maybe the inner conditional is unnecessary if the
+        #  interface is common and the leaf proc deals with the input
         if sparse:
             if model == "SigDel":
                 print("[INFO]: Using Sigma Delta Solution Neurons")
@@ -305,6 +307,7 @@ def __init__(self, proc_params: dict) -> None:
         self.connectivity_spike = 0
 
     def run_spk(self):
+        # TODO all this conditionals should be done in an extracted method.
         self.decay_counter += 1
         a_in = self.a_in.recv()
         if self.decay_counter % 2 == 1:
@@ -373,6 +376,7 @@ def run_spk(self):
         self.growth_counter += 1
         a_in = self.a_in.recv()
 
+        # TODO all this conditionals should be done in an extracted method.
         if self.growth_counter % 2 == 1:
             if self.lr_growth_type == "schedule":
                 if self.growth_counter == self.beta_growth_schedule:
@@ -436,6 +440,7 @@ def run_spk(self):
         delta_state = s_in - self.x_internal
         self.x_internal = s_in
         self.decay_counter += 1
+        # TODO all this conditionals should be done in an extracted method.
         if self.theta_decay_type == "schedule":
             if self.decay_counter == self.theta_decay_schedule:
                 # TODO: guard against shift overflows in fixed-point

src/lava/lib/optimization/solvers/generic/solution_finder/models.py

@@ -55,6 +55,8 @@ def __init__(self, proc):
         problem = proc.proc_params.get("problem")
         backend = proc.proc_params.get("backend")
 
+        # TODO perform method extraction and simplify, the following is too
+        #  large and might include some code duplication.
         # Subprocesses
         self.variables = VariablesImplementation()
         if discrete_var_shape is not None: