[Mlir-commits] [mlir] 9a844c2 - Revert "[mlir] Make sure linearizeCollapsedDims doesn't drop input map dims"

[llvmlistbot at llvm.org]

Author: MaheshRavishankar
Date: 2021-11-30T22:43:46-08:00
New Revision: 9a844c2a9b5c09b4c35d573394a99ab860621581

URL: https://github.com/llvm/llvm-project/commit/9a844c2a9b5c09b4c35d573394a99ab860621581
DIFF: https://github.com/llvm/llvm-project/commit/9a844c2a9b5c09b4c35d573394a99ab860621581.diff

LOG: Revert "[mlir] Make sure linearizeCollapsedDims doesn't drop input map dims"

This reverts commit bc38673e4de50b995f4bc46d1a4b0ad95bef2356.

Added: 
    

Modified: 
    mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
    mlir/test/Dialect/Linalg/reshape_linearization_fusion.mlir

Removed: 
    


################################################################################
diff  --git a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
index 959dbb4d5b415..6faf6857c2aaa 100644
--- a/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
+++ b/mlir/lib/Dialect/Linalg/Transforms/ElementwiseOpFusion.cpp
@@ -385,15 +385,7 @@ static AffineMap linearizeCollapsedDims(AffineMap sourceMap,
         makeCanonicalStridedLayoutExpr(sizes, dimExprs, context);
     resultExprs.push_back(linearizedExpr);
   }
-  // The new affine map cannot drop unused dimension but some new symbols may
-  // have been added. Create a map with at least as many dimensions/symbols as
-  // the original affine map.
-  int64_t maxDim = -1;
-  int64_t maxSym = -1;
-  getMaxDimAndSymbol<SmallVector<AffineExpr>>({resultExprs}, maxDim, maxSym);
-  unsigned numDims = std::max(unsigned(maxDim + 1), sourceMap.getNumDims());
-  unsigned numSyms = std::max(unsigned(maxSym + 1), sourceMap.getNumSymbols());
-  return AffineMap::get(numDims, numSyms, resultExprs, context);
+  return AffineMap::inferFromExprList({resultExprs}).front();
 }
 
 // TensorExpandShapeOp is fusable with its consumer (i.e. reshape as a

diff  --git a/mlir/test/Dialect/Linalg/reshape_linearization_fusion.mlir b/mlir/test/Dialect/Linalg/reshape_linearization_fusion.mlir
index 512f7545a5eae..f563fe79474fd 100644
--- a/mlir/test/Dialect/Linalg/reshape_linearization_fusion.mlir
+++ b/mlir/test/Dialect/Linalg/reshape_linearization_fusion.mlir
@@ -199,31 +199,3 @@ func @generic_op_reshape_consumer_nofusion(%arg0 : tensor<?x?x?x5xf32>,
 //  CHECK-SAME:     ins(%[[ARG0]], %[[ARG1]]
 //       CHECK:   %[[RESULT:.+]] = linalg.tensor_collapse_shape %[[NOFUSE]]
 //       CHECK:   return %[[RESULT]]
-
-
-// -----
-
-func @generic_op_permultation_reshape_consumer_fusion_unused_dim(%arg0 : tensor<6x1xf32>) -> tensor<6xi32> {
-  %0 = linalg.init_tensor [6, 1] : tensor<6x1xi32>
-  %1 = linalg.generic {indexing_maps = [affine_map<(d0, d1) -> (d0, d1)>,
-                                        affine_map<(d0, d1) -> (d0, d1)>],
-   iterator_types = ["parallel", "parallel"]}
-   ins(%arg0 : tensor<6x1xf32>) outs(%0 : tensor<6x1xi32>) {
-    ^bb0(%arg3: f32, %arg4: i32):  // no predecessors
-      %5 = arith.fptosi %arg3 : f32 to i32
-      linalg.yield %5 : i32
-    } -> tensor<6x1xi32>
-    %6 = linalg.tensor_collapse_shape %1 [[0, 1]] : tensor<6x1xi32> into tensor<6xi32>
-  return %6 : tensor<6xi32>
-}
-//   CHECK-DAG: #[[MAP0:.+]] = affine_map<(d0, d1) -> (d0, d1)>
-//   CHECK-DAG: #[[MAP1:.+]] = affine_map<(d0, d1) -> (d0)>
-//       CHECK: func @generic_op_permultation_reshape_consumer_fusion_unused_dim
-//  CHECK-SAME:   %[[ARG0:.+]]: tensor<6x1xf32>
-//       CHECK:   %[[T0:.+]] = linalg.init_tensor [6, 1]
-//       CHECK:   %[[T1:.+]] = linalg.tensor_collapse_shape %[[T0]]
-//  CHECK-SAME:   [0, 1]
-//       CHECK:   linalg.generic
-//  CHECK-SAME:     indexing_maps = [#[[MAP0]], #[[MAP1]]]
-//  CHECK-SAME:     ins(%[[ARG0]] : tensor<6x1xf32>)
-//  CHECK-SAME:     outs(%[[T1]] : tensor<6xi32>)