From 5998daec2d1f6b5bec339d68138b283ff3419723 Mon Sep 17 00:00:00 2001
From: Paxon <e.paxon.frady@intel.com>
Date: Tue, 18 Jul 2023 15:53:29 -0700
Subject: [PATCH] adding some docstring, fixing unused imports

---
 src/lava/proc/graded/models.py        |  6 +++++-
 src/lava/proc/graded/process.py       | 10 ----------
 src/lava/proc/prodneuron/process.py   | 27 ++++++++++++++-------------
 tests/lava/proc/graded/test_graded.py |  5 +----
 4 files changed, 20 insertions(+), 28 deletions(-)

diff --git a/src/lava/proc/graded/models.py b/src/lava/proc/graded/models.py
index 28803142a..082b35016 100644
--- a/src/lava/proc/graded/models.py
+++ b/src/lava/proc/graded/models.py
@@ -3,7 +3,6 @@
 # See: https://spdx.org/licenses/
 
 import numpy as np
-import typing as ty
 
 from lava.magma.core.sync.protocols.loihi_protocol import LoihiProtocol
 from lava.magma.core.model.py.ports import PyInPort, PyOutPort
@@ -16,6 +15,8 @@
 
 
 class AbstractGradedVecModel(PyLoihiProcessModel):
+    """Implementation of GradedVec"""
+
     a_in = None
     s_out = None
 
@@ -83,6 +84,7 @@ def run_spk(self) -> None:
 @requires(CPU)
 @tag('float')
 class InvSqrtModelFloat(PyLoihiProcessModel):
+    """Implementation of InvSqrt in floating point"""
     a_in = LavaPyType(PyInPort.VEC_DENSE, float)
     s_out = LavaPyType(PyOutPort.VEC_DENSE, float)
 
@@ -133,6 +135,8 @@ def inv_sqrt(s_fp, n_iters=5, b_fraction=12):
 @requires(CPU)
 @tag('fixed_pt')
 class InvSqrtModelFP(PyLoihiProcessModel):
+    """Implementation of InvSqrt in fixed point"""
+
     a_in = LavaPyType(PyInPort.VEC_DENSE, np.int32, precision=24)
     s_out = LavaPyType(PyOutPort.VEC_DENSE, np.int32, precision=24)
     fp_base: np.ndarray = LavaPyType(np.ndarray, np.int32, precision=24)
diff --git a/src/lava/proc/graded/process.py b/src/lava/proc/graded/process.py
index a05caa11a..68b00c953 100644
--- a/src/lava/proc/graded/process.py
+++ b/src/lava/proc/graded/process.py
@@ -2,23 +2,13 @@
 # SPDX-License-Identifier: BSD-3-Clause
 # See: https://spdx.org/licenses/
 
-import os
 import numpy as np
 import typing as ty
-from typing import Any, Dict
-from enum import IntEnum, unique
 
 from lava.magma.core.process.process import AbstractProcess
 from lava.magma.core.process.variable import Var
 from lava.magma.core.process.ports.ports import InPort, OutPort
 
-from lava.magma.core.sync.protocols.loihi_protocol import LoihiProtocol
-from lava.magma.core.model.py.ports import PyInPort, PyOutPort
-from lava.magma.core.model.py.type import LavaPyType
-from lava.magma.core.resources import CPU
-from lava.magma.core.decorator import implements, requires, tag
-from lava.magma.core.model.py.model import PyLoihiProcessModel
-
 
 def loihi2round(vv):
     """
diff --git a/src/lava/proc/prodneuron/process.py b/src/lava/proc/prodneuron/process.py
index 08d5d88d1..dfa4dc35c 100644
--- a/src/lava/proc/prodneuron/process.py
+++ b/src/lava/proc/prodneuron/process.py
@@ -10,25 +10,26 @@
 
 
 class ProdNeuron(AbstractProcess):
+    """ProdNeuron
+
+    Multiplies two graded inputs.
+
+    Parameters
+    ----------
+
+    shape : tuple(int)
+        Number and topology of ProdNeuron neurons.
+    vth : int
+        Threshold
+    exp : int
+        Fixed-point base
+    """
     def __init__(
             self,
             shape: ty.Tuple[int, ...],
             vth=1,
             exp=0) -> None:
-        """ProdNeuron
-
-        Multiplies two graded inputs.
-
-        Parameters
-        ----------
 
-        shape : tuple(int)
-            Number and topology of ProdNeuron neurons.
-        vth : int
-            Threshold
-        exp : int
-            Fixed-point base
-        """
         super().__init__(shape=shape)
 
         self.a_in1 = InPort(shape=shape)
diff --git a/tests/lava/proc/graded/test_graded.py b/tests/lava/proc/graded/test_graded.py
index 469b7dcf6..d485c15fc 100644
--- a/tests/lava/proc/graded/test_graded.py
+++ b/tests/lava/proc/graded/test_graded.py
@@ -4,14 +4,13 @@
 
 import unittest
 import numpy as np
-from scipy.sparse import csr_matrix, find
+from scipy.sparse import csr_matrix
 
 from lava.proc.graded.process import GradedVec, NormVecDelay, InvSqrt
 from lava.proc.graded.models import inv_sqrt
 from lava.proc.dense.process import Dense
 from lava.proc.sparse.process import Sparse
 from lava.proc import io
-from lava.proc import embedded_io as eio
 
 from lava.magma.core.run_conditions import RunSteps
 from lava.magma.core.run_configs import Loihi2SimCfg
@@ -145,7 +144,6 @@ def test_invsqrt_calc(self):
 class TestNormVecDelayProc(unittest.TestCase):
 
     def test_norm_vec_delay_out1(self):
-        fp_base = 12  # base of the decimal point
         weight_exp = 7
         num_steps = 10
 
@@ -208,7 +206,6 @@ def test_norm_vec_delay_out1(self):
         self.assertTrue(np.all(expected_out[:, :-1] == out_data[:, 1:]))
 
     def test_norm_vec_delay_out2(self):
-        fp_base = 12  # base of the decimal point
         weight_exp = 7
         num_steps = 10