Automerge: [mlir][Bufferization] Fix to_buffer(tensor.cast) folder (#150511)

Previously this folder would ignore the layout and memory space on the
to_buffer op and set it as default. This changes the pattern to retain
both fields from the existing memref type but incorporate the static
shape information from the tensor cast.
The `read_only` attribute was also dropped by the pattern and is
retained now as well.

Author: qedawkins

mlir/lib/Dialect/Bufferization/IR/BufferizationOps.cpp

@@ -805,10 +805,18 @@ struct ToBufferOfCast : public OpRewritePattern<ToBufferOp> {
         tensorCastOperand.getOperand().getType());
     if (!srcTensorType)
       return failure();
+    auto currentOutputMemRefType =
+        dyn_cast<MemRefType>(toBuffer.getResult().getType());
+    if (!currentOutputMemRefType)
+      return failure();
+
     auto memrefType = MemRefType::get(srcTensorType.getShape(),
-                                      srcTensorType.getElementType());
+                                      srcTensorType.getElementType(),
+                                      currentOutputMemRefType.getLayout(),
+                                      currentOutputMemRefType.getMemorySpace());
     Value memref = ToBufferOp::create(rewriter, toBuffer.getLoc(), memrefType,
-                                      tensorCastOperand.getOperand());
+                                      tensorCastOperand.getOperand(),
+                                      toBuffer.getReadOnly());
     rewriter.replaceOpWithNewOp<memref::CastOp>(toBuffer, toBuffer.getType(),
                                                 memref);
     return success();

mlir/test/Dialect/Bufferization/canonicalize.mlir

@@ -255,16 +255,32 @@ func.func @clone_and_preceding_dealloc(%arg0: memref<?xf32>) -> memref<32xf32> {
 func.func @tensor_cast_to_buffer(%arg0 : tensor<4x6x16x32xi8>) ->
   memref<?x?x16x32xi8> {
   %0 = tensor.cast %arg0 : tensor<4x6x16x32xi8> to tensor<?x?x16x32xi8>
-  %1 = bufferization.to_buffer %0 : tensor<?x?x16x32xi8> to memref<?x?x16x32xi8>
+  %1 = bufferization.to_buffer %0 read_only : tensor<?x?x16x32xi8> to memref<?x?x16x32xi8>
   return %1 : memref<?x?x16x32xi8>
 }
-// CHECK:   %[[M:.+]] = bufferization.to_buffer %[[ARG0]] : tensor<4x6x16x32xi8>
+// CHECK:   %[[M:.+]] = bufferization.to_buffer %[[ARG0]] read_only : tensor<4x6x16x32xi8>
 // CHECK:   %[[M1:.+]] = memref.cast %[[M]]
 // CHECK-SAME: memref<4x6x16x32xi8> to memref<?x?x16x32xi8>
 // CHECK:   return %[[M1]] : memref<?x?x16x32xi8>
 
 // -----
 
+// CHECK-LABEL: func @tensor_cast_to_buffer
+//  CHECK-SAME:   %[[ARG0:.+]]: tensor<4x6x16x32xi8>
+func.func @tensor_cast_to_buffer_layout_and_memspace(%arg0 : tensor<4x6x16x32xi8>) ->
+  memref<?x?x16x32xi8, strided<[?, ?, ?, 1], offset: ?>, 1> {
+  %0 = tensor.cast %arg0 : tensor<4x6x16x32xi8> to tensor<?x?x16x32xi8>
+  %1 = bufferization.to_buffer %0 : tensor<?x?x16x32xi8> to memref<?x?x16x32xi8, strided<[?, ?, ?, 1], offset: ?>, 1>
+  return %1 : memref<?x?x16x32xi8, strided<[?, ?, ?, 1], offset: ?>, 1>
+}
+// CHECK:   %[[M:.+]] = bufferization.to_buffer %[[ARG0]] : tensor<4x6x16x32xi8>
+// CHECK:   %[[M1:.+]] = memref.cast %[[M]]
+// CHECK-SAME: memref<4x6x16x32xi8, strided<[?, ?, ?, 1], offset: ?>, 1>
+// CHECK-SAME: to memref<?x?x16x32xi8, strided<[?, ?, ?, 1], offset: ?>, 1>
+// CHECK:   return %[[M1]] : memref<?x?x16x32xi8, strided<[?, ?, ?, 1], offset: ?>, 1>
+
+// -----
+
 // Folding of memref.load(to_buffer(%v, %idxs)) -> tensor.extract(%v, %idx)
 // CHECK-LABEL: func @load_from_buffer_cast(
 func.func @load_from_buffer_cast(%arg0: index, %arg1: index,