Fix Neureka

Deeploy/Targets/Neureka/Engine.py

@@ -31,11 +31,12 @@
         ConvLayer([NeurekaPWConv2DMapper, NeurekaDWConv2DMapper, NeurekaDenseConv2DMapper]),
 }
 
-_includeList = ["pulp_nnx_neureka.h", "pulp_nnx_util.h", "neureka_siracusa_bsp.h", "neureka.h", "neureka_task.h"]
+_includeList = ["pulp_nnx_neureka.h", "pulp_nnx_util.h", "neureka_siracusa_bsp.h", "neureka.h", "neureka_task.h", "neureka_gvsoc.h"]
 
 _neurekaInitCode = r"""
 neureka_siracusa_conf_t conf = {.max_stall = 8};
 neureka_nnx_init(neureka_siracusa_get_dev(), &conf);
+neureka_gvsoc_log_activate(neureka_siracusa_get_dev(), NEUREKA_GVSOC_LOG_LEVEL_ALL, NEUREKA_GVSOC_LOG_FORMAT_DECIMAL);
 """
 
 

Deeploy/Targets/Neureka/Parsers.py

@@ -50,14 +50,18 @@ def parseNodeCtxt(self,
         #         and enforcing that the channels_first is false
         data_in = newCtxt.lookup(self.operatorRepresentation['data_in'])
         data_out = newCtxt.lookup(self.operatorRepresentation['data_out'])
-        weight = newCtxt.lookup(self.operatorRepresentation['weight'])
+        # MARCHIOA: weight depends on the type of convolution so it requires to be parsed by the child parsers
+        #           - PW -> 3-dim
+        #           - DW -> 4-dim
+        #           - Dense -> 4-dim
+        # weight = newCtxt.lookup(self.operatorRepresentation['weight'])
 
         if not all([
                 channels_first == False,
                 len(data_in.shape) == 4,
-                # LMACAN: weight shape should be equal to 3 because we have to do the neureka's
-                #         special weight encoding
-                len(weight.shape) == 3,
+                # # LMACAN: weight shape should be equal to 3 because we have to do the neureka's
+                # #         special weight encoding
+                # len(weight.shape) == 3,
         ]):
             return newCtxt, False
 
@@ -95,6 +99,18 @@ def parseNode(self, node: gs.Node) -> bool:
 
         return True
 
+    def parseNodeCtxt(self, ctxt, node, channels_first = True):
+
+        newCtxt, ret = super().parseNodeCtxt(ctxt, node, channels_first)
+        if not ret:
+            return False
+
+        weight = newCtxt.lookup(self.operatorRepresentation['weight'])
+        if not (len(weight.shape) == 4):
+            return False
+
+        return newCtxt, True
+
 
 class NeurekaRQSDWConv2DParser(NeurekaDWConv2DParser, RQSParserInterface):
 
@@ -136,6 +152,18 @@ def parseNode(self, node: gs.Node) -> bool:
 
         return True
 
+    def parseNodeCtxt(self, ctxt, node, channels_first = True):
+
+        newCtxt, ret = super().parseNodeCtxt(ctxt, node, channels_first)
+        if not ret:
+            return False
+
+        weight = newCtxt.lookup(self.operatorRepresentation['weight'])
+        if not (len(weight.shape) == 3):
+            return False
+
+        return newCtxt, True
+
 
 class NeurekaRQSPWConv2DParser(NeurekaPWConv2DParser, RQSParserInterface):
 
@@ -176,6 +204,18 @@ def parseNode(self, node: gs.Node) -> bool:
 
         return True
 
+    def parseNodeCtxt(self, ctxt, node, channels_first = True):
+
+        newCtxt, ret = super().parseNodeCtxt(ctxt, node, channels_first)
+        if not ret:
+            return False
+
+        weight = newCtxt.lookup(self.operatorRepresentation['weight'])
+        if not (len(weight.shape) == 4):
+            return False
+
+        return newCtxt, True
+
 
 class NeurekaRQSDenseConv2DParser(NeurekaDenseConv2DParser, RQSParserInterface):
 

Deeploy/Targets/Neureka/Templates/ConvTemplate.py

@@ -256,12 +256,12 @@ def getCounters(
             operatorRepresentation: OperatorRepresentation) -> Tuple[int, int, int, int, int, int, int, int, int, int]:
         _ = operatorRepresentation  # operatorRepresentation not accessed for now because it's just for pointwise kernels
 
-        n_channel_out_subtiles = _getNumTiles(channel_out, 28)
+        n_channel_out_subtiles = _getNumTiles(channel_out, 32)
         n_channel_in_subtiles = _getNumTiles(channel_in, 28)
         n_height_out_subtiles = _getNumTiles(height_out, 6)
         n_width_out_subtiles = _getNumTiles(width_out, 6)
 
-        channel_out_border = _getBorderTileSize(channel_out, 28)
+        channel_out_border = _getBorderTileSize(channel_out, 32)
         channel_in_border = _getBorderTileSize(channel_in, 28)
         height_out_border = _getBorderTileSize(height_out, 6)
         width_out_border = _getBorderTileSize(width_out, 6)

Deeploy/Targets/Neureka/TileConstraints/NeurekaDenseConstraint.py

@@ -218,7 +218,10 @@ def serializeTilingSolution(
             replacementTypes['weight_addr_offset'] = PointerClass(uint32_t)
             for absoluteCube in absoluteOutputCubes:
                 COffset, CSize = absoluteCube.absoluteOffset[-1], absoluteCube.rectangle.dims[-1]
-                WeightCube = HyperRectangle((COffset, 0, 0), (CSize, weightShape[-2], weightShape[-1]))
+                # WeightCube = HyperRectangle((COffset, 0, 0), (CSize, weightShape[-2], weightShape[-1]))
+                WeightCube = HyperRectangle(
+                    (COffset, 0, 0, 0),
+                    (CSize, weightShape[-3], weightShape[-2], weightShape[-1]))
                 replacements['weight_addr_offset'].append(calculateFlatOffsetInBytes(WeightCube, weightBuffer))
         else:
             inputWeightBaseOffsets, outputWeightBaseOffsets = cls.extractBaseAddr(tilingSolution, targetMemLevel,

Deeploy/Targets/Neureka/TileConstraints/NeurekaDepthwiseConstraint.py

@@ -214,7 +214,10 @@ def serializeTilingSolution(
             replacementTypes['weight_addr_offset'] = PointerClass(uint32_t)
             for absoluteCube in absoluteOutputCubes:
                 COffset, CSize = absoluteCube.absoluteOffset[-1], absoluteCube.rectangle.dims[-1]
-                WeightCube = HyperRectangle((COffset, 0, 0), (CSize, weightShape[-2], weightShape[-1]))
+                # WeightCube = HyperRectangle((COffset, 0, 0), (CSize, weightShape[-2], weightShape[-1]))
+                WeightCube = HyperRectangle(
+                    (COffset, 0, 0, 0),
+                    (CSize, weightShape[-3], weightShape[-2], weightShape[-1]))
                 replacements['weight_addr_offset'].append(calculateFlatOffsetInBytes(WeightCube, weightBuffer))
         else:
             inputWeightBaseOffsets, outputWeightBaseOffsets = cls.extractBaseAddr(tilingSolution, targetMemLevel,

DeeployTest/testUtils/deeployRunner.py

@@ -238,6 +238,10 @@ def create_config_from_args(args: argparse.Namespace,
             gen_args_list.append(f"--searchStrategy={args.searchStrategy}")
         if hasattr(args, 'plotMemAlloc') and args.plotMemAlloc:
             gen_args_list.append("--plotMemAlloc")
+        if hasattr(args, 'enable_3x3') and args.enable_3x3:
+            gen_args_list.append("--enable-3x3")
+        if hasattr(args, 'neureka_wmem') and args.neureka_wmem:
+            gen_args_list.append("--neureka-wmem")
 
     if not tiling and getattr(args, 'profileUntiled', False):
         gen_args_list.append("--profileUntiled")