Improved comments and removed unnecessary components

Author: diaconuccalin

Deeploy/Targets/PULPOpen/TileConstraints/MatMulTileConstraint.py

@@ -75,19 +75,19 @@ def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: Netw
 
     @staticmethod
     def addPolicyConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: NetworkContext) -> TilerModel:
-
-        # Get input buffers and other required information
+        # ===== GET NECESSARY INFORMATION =====
         bufferA = ctxt.lookup(name = parseDict['A'])
         bufferB = ctxt.lookup(name = parseDict['B'])
 
         tensorsShapeLen = len(bufferA.shape)
 
-        # Get dimensions of interest from the 2 inputs
+        # ===== EXTRACT TENSOR DIMS AS VARS =====
         ASecondDimVar = tilerModel.getTensorDimVar(tensorName = bufferA.name,
                                                    dimIdx = (tensorsShapeLen - 1) - parseDict['transA'])
         BFirstDimVar = tilerModel.getTensorDimVar(tensorName = bufferB.name,
                                                   dimIdx = (tensorsShapeLen - 2) + parseDict['transB'])
 
+        # ===== ADD CONSTRAINTS =====
         # VIC: We don't want to deal with intermediate results between kernel calls
         tilerModel.addConstraint(ASecondDimVar == parseDict['N'])
         tilerModel.addConstraint(BFirstDimVar == parseDict['N'])
@@ -125,7 +125,7 @@ def serializeTilingSolution(
         # Prepare replacements lists
         replacements = {"M": [], "O": [], "batch": []}
 
-        # Every output is constructed by a pair of inputs. Reconstruct this pair.
+        # Every output tile is constructed by a pair of input tiles. Reconstruct this pair.
         for cube in outputCubes:
             # Get output dimensions
             MOffset, OOffset = cube.offset[-2:]
@@ -147,7 +147,7 @@ def serializeTilingSolution(
             replacements["O"].append(OSize)
             replacements["batch"].append(BatchSize)
 
-            # Compute A cube information
+            # ===== Compute A cube information =====
             #   Matrix offsets and shape
             AMatrixOffsets = (MOffset, NOffset)
             AMatrixShape = (MSize, NSize)
@@ -169,7 +169,7 @@ def serializeTilingSolution(
                 tuple(reversed(ABatchShape)) + tuple(AMatrixShape))
             inputACubes.append(ACube)
 
-            # Compute B cube information
+            # ===== Compute B cube information =====
             #   Matrix offsets and shape
             BMatrixOffsets = (NOffset, OOffset)
             BMatrixShape = (NSize, OSize)

Deeploy/Targets/PULPOpen/TileConstraints/ReduceMeanConstraint.py

@@ -21,7 +21,7 @@ class ReduceMeanTileConstraint(TileConstraint):
 
     @staticmethod
     def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: NetworkContext) -> TilerModel:
-        # Get necessary information
+        # ===== GET NECESSARY INFORMATION =====
         #   Get I/O buffer names
         inputBufferName = parseDict['data_in']
         outputBufferName = parseDict['data_out']
@@ -33,11 +33,12 @@ def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: Netw
         reduceAxes = parseDict['axes']
         keepDims = parseDict['keepdims']
 
-        # Add I/O dimensions to the model as variables
+        # ===== ADD I/O DIMENSIONS TO THE MODEL AS VARIABLES =====
         for bufferName in [inputBufferName, outputBufferName]:
             tilerModel.addTensorDimToModel(ctxt, bufferName)
 
-        # Add constratints for the I/O dimensions
+        # ===== ADD CONSTRAINTS =====
+        #   Add constraints for the I/O dimensions
         input_ax = 0
         for idx in range(len(outputShape)):
             # Get current dimension variables
@@ -60,10 +61,6 @@ def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: Netw
 
         return tilerModel
 
-    @staticmethod
-    def addPolicyConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: NetworkContext) -> TilerModel:
-        return tilerModel
-
     @staticmethod
     def constructSymbolicNodeRep(tilerModel: TilerModel, parseDict: Dict,
                                  ctxt: NetworkContext) -> Dict[str, Union[int, IntVar]]:

Deeploy/Targets/PULPOpen/TileConstraints/SliceConstraint.py

@@ -22,7 +22,7 @@ class SliceTileConstraint(TileConstraint):
     @staticmethod
     def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: NetworkContext) -> TilerModel:
 
-        # Get necessary information
+        # ===== GET NECESSARY INFORMATION =====
         #   Get I/O buffer names
         inputBufferName = parseDict['data_in']
         outputBufferName = parseDict['data_out']
@@ -34,11 +34,12 @@ def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: Netw
         sliceAxes = parseDict['axes']
         sliceSteps = parseDict['steps']
 
-        # Add I/O dimensions to the model as variables
+        # ===== ADD I/O DIMENSIONS TO THE MODEL AS VARIABLES =====
         for bufferName in [inputBufferName, outputBufferName]:
             tilerModel.addTensorDimToModel(ctxt, bufferName)
 
-        # Add constratints for the I/O dimensions
+        # ===== ADD CONSTRAINTS =====
+        #   Add constraints for the I/O dimensions
         for idx in range(len(inputShape)):
             # Get current dimension variables
             inputDimensionVar = tilerModel.getTensorDimVar(tensorName = inputBufferName, dimIdx = idx)
@@ -57,10 +58,6 @@ def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: Netw
 
         return tilerModel
 
-    @staticmethod
-    def addPolicyConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: NetworkContext) -> TilerModel:
-        return tilerModel
-
     @staticmethod
     def constructSymbolicNodeRep(tilerModel: TilerModel, parseDict: Dict,
                                  ctxt: NetworkContext) -> Dict[str, Union[int, IntVar]]: