Removed more restrictive ReduceMean policy constraint

Author: diaconuccalin

Deeploy/Targets/PULPOpen/TileConstraints/ReduceMeanConstraint.py

@@ -61,33 +61,6 @@ def addGeometricalConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: Netw
 
         return tilerModel
 
-    @staticmethod
-    def addPolicyConstraint(tilerModel: TilerModel, parseDict: Dict, ctxt: NetworkContext) -> TilerModel:
-        # ===== GET NECESSARY INFORMATION =====
-        #   Get I/O buffer names
-        inputBufferName = parseDict['data_in']
-
-        #   Get other necessary information
-        inputShape = parseDict['data_in_shape']
-        reduceAxes = parseDict['axes']
-        nonReducedDims = [ax for ax in range(len(inputShape)) if ax not in reduceAxes]
-
-        if len(nonReducedDims) > 0:
-            biggestNonReducedDim = max(nonReducedDims, key = lambda ax: inputShape[ax])
-        else:
-            biggestNonReducedDim = -1  # No non-reduced dimensions
-
-        # ===== ADD CONSTRAINTS =====
-        #  Kernel parallelized only on biggest non-reduced dimension,
-        #  so tile only on that dimension
-        for ax in range(len(inputShape)):
-            dimVar = tilerModel.getTensorDimVar(tensorName = inputBufferName, dimIdx = ax)
-            if ax != biggestNonReducedDim:
-                # This is not the biggest non-reduced dimension, force no tiling
-                tilerModel.addConstraint(dimVar == inputShape[ax])
-
-        return tilerModel
-
     @staticmethod
     def constructSymbolicNodeRep(tilerModel: TilerModel, parseDict: Dict,
                                  ctxt: NetworkContext) -> Dict[str, Union[int, IntVar]]: