Merge pull request lava-nc#1 from SveaMeyer13/tutorials-on-loihi

Add Loihi 2 Tutorials

tutorials/lava/lib/dnf/dnf_regimes/script_dnf_regimes.py

@@ -1,62 +1,20 @@
-import unittest
 import numpy as np
-import typing as ty
-
 from lava.lib.dnf.inputs.rate_code_spike_gen.process import RateCodeSpikeGen
 from lava.proc.embedded_io.spike import PyToNxAdapter, NxToPyAdapter
 from lava.proc.io.sink import RingBuffer
 from lava.lib.dnf.connect.connect import connect
 from lava.lib.dnf.operations.operations import Convolution
 from lava.lib.dnf.inputs.gauss_pattern.process import GaussPattern
-
 from lava.magma.core.run_configs import Loihi1SimCfg
 from lava.proc.monitor.process import Monitor
 from lava.lib.dnf.kernels.kernels import MultiPeakKernel, Kernel
-
 from utils import plot_1d, animated_1d_plot
-
-from lava.magma.core.decorator import implements, requires
-from lava.magma.core.model.py.model import PyLoihiProcessModel
-from lava.magma.core.model.py.ports import PyInPort, PyOutPort
-from lava.magma.core.model.py.type import LavaPyType
-from lava.magma.core.process.ports.ports import InPort, OutPort
-from lava.magma.core.process.process import AbstractProcess
-from lava.magma.core.resources import CPU
-
 from lava.magma.core.run_conditions import RunSteps
 from lava.magma.core.run_configs import Loihi2HwCfg
-from lava.magma.core.sync.protocols.loihi_protocol import LoihiProtocol
 from lava.proc.lif.process import LIF
 from lava.proc.dense.process import Dense
 
 
-class Sum(AbstractProcess):
-    def __init__(self, shape: ty.Tuple[int, ...]) -> None:
-        super().__init__(shape=shape)
-
-        self.in_port_1 = InPort(shape=shape)
-        self.in_port_2 = InPort(shape=shape)
-        self.out_port = OutPort(shape=shape)
-
-
-@implements(proc=Sum, protocol=LoihiProtocol)
-@requires(CPU)
-class SumProcessModel(PyLoihiProcessModel):
-    in_port_1: PyInPort = LavaPyType(PyInPort.VEC_DENSE, bool)
-    in_port_2: PyInPort = LavaPyType(PyInPort.VEC_DENSE, bool)
-    out_port: PyOutPort = LavaPyType(PyOutPort.VEC_DENSE, bool)
-
-    # TODO (MR): Fix the bug (?) with multiple Dense Processes that have
-    #  different num_message_bit values.
-    def run_spk(self) -> None:
-        input_1 = self.in_port_1.recv()
-        input_2 = self.in_port_2.recv()
-        #output = input_1.astype(int) + input_2.astype(int)
-        output = input_1 + input_2
-
-        self.out_port.send(output)
-
-
 class Architecture:
     """This class structure is not required and is only used here to reduce
     code duplication for different examples."""
@@ -78,11 +36,13 @@ def __init__(self,
 
         self.spike_generator_1 = RateCodeSpikeGen(shape=shape)
         self.spike_generator_2 = RateCodeSpikeGen(shape=shape)
-        self.sum = Sum(shape=shape)
+
         if loihi2:
-            self.injector = PyToNxAdapter(shape=shape)
+            self.injector1 = PyToNxAdapter(shape=shape)
+            self.injector2 = PyToNxAdapter(shape=shape)
 
-        self.input_dense = Dense(weights=np.eye(shape[0]) * 25)
+        self.input_dense1 = Dense(weights=np.eye(shape[0]) * 25)
+        self.input_dense2 = Dense(weights=np.eye(shape[0]) * 25)
 
         self.dnf = LIF(shape=shape, du=409, dv=2047, vth=200)
         dense = connect(self.dnf.s_out, self.dnf.a_in, [Convolution(kernel)])
@@ -94,15 +54,17 @@ def __init__(self,
         self.gauss_pattern_1.a_out.connect(self.spike_generator_1.a_in)
         self.gauss_pattern_2.a_out.connect(self.spike_generator_2.a_in)
 
-        self.spike_generator_1.s_out.connect(self.sum.in_port_1)
-        self.spike_generator_2.s_out.connect(self.sum.in_port_2)
         if loihi2:
-            self.sum.out_port.connect(self.injector.inp)
-            self.injector.out.connect(self.input_dense.s_in)
+            self.spike_generator_1.s_out.connect(self.injector1.inp)
+            self.spike_generator_2.s_out.connect(self.injector2.inp)
+            self.injector1.out.connect(self.input_dense1.s_in)
+            self.injector2.out.connect(self.input_dense2.s_in)
         else:
-            self.sum.out_port.connect(self.input_dense.s_in)
+            self.spike_generator_1.s_out.connect(self.input_dense1.s_in)
+            self.spike_generator_2.s_out.connect(self.input_dense2.s_in)
 
-        self.input_dense.a_out.connect(self.dnf.a_in)
+        self.input_dense1.a_out.connect(self.dnf.a_in)
+        self.input_dense2.a_out.connect(self.dnf.a_in)
 
         if loihi2:
             self.dnf.s_out.connect(self.spike_reader.inp)
@@ -139,6 +101,7 @@ def run(self):
         self.gauss_pattern_1.run(condition=RunSteps(num_steps=200),
                                  run_cfg=self.run_cfg)
 
+
     def plot(self):
         # Get probed data from monitors
         data_dnf = self.py_receiver.data.get().transpose()