[mlir][linalg][bufferize] Print results of FuncOp read/write analysis

Print more information with test-analysis-only.

Differential Revision: https://reviews.llvm.org/D119118

Author: matthias-springer

mlir/lib/Dialect/Linalg/ComprehensiveBufferize/ModuleBufferization.cpp

@@ -239,6 +239,22 @@ static bool isValueWritten(Value value, const BufferizationState &state,
   return isWritten;
 }
 
+static void annotateFuncArgAccess(FuncOp funcOp, BlockArgument bbArg,
+                                  bool isRead, bool isWritten) {
+  OpBuilder b(funcOp.getContext());
+  Attribute accessType;
+  if (isRead && isWritten) {
+    accessType = b.getStringAttr("read-write");
+  } else if (isRead) {
+    accessType = b.getStringAttr("read");
+  } else if (isWritten) {
+    accessType = b.getStringAttr("write");
+  } else {
+    accessType = b.getStringAttr("none");
+  }
+  funcOp.setArgAttr(bbArg.getArgNumber(), "bufferization.access", accessType);
+}
+
 /// Determine which FuncOp bbArgs are read and which are written. If this
 /// PostAnalysisStepFn is run on a function with unknown ops, it will
 /// conservatively assume that such ops bufferize to a read + write.
@@ -263,9 +279,13 @@ funcOpBbArgReadWriteAnalysis(Operation *op, BufferizationState &state,
   for (BlockArgument bbArg : funcOp.getArguments()) {
     if (!bbArg.getType().isa<TensorType>())
       continue;
-    if (state.isValueRead(bbArg))
+    bool isRead = state.isValueRead(bbArg);
+    bool isWritten = isValueWritten(bbArg, state, aliasInfo);
+    if (state.getOptions().testAnalysisOnly)
+      annotateFuncArgAccess(funcOp, bbArg, isRead, isWritten);
+    if (isRead)
       moduleState.readBbArgs.insert(bbArg);
-    if (isValueWritten(bbArg, state, aliasInfo))
+    if (isWritten)
       moduleState.writtenBbArgs.insert(bbArg);
   }
 

mlir/test/Dialect/Linalg/comprehensive-module-bufferize-analysis.mlir

@@ -11,9 +11,11 @@
 
 // -----
 
-// CHECK-LABEL: func @extract_slice_fun
+// CHECK-LABEL: func @extract_slice_fun(
 func @extract_slice_fun(%A : tensor<?xf32> {linalg.inplaceable = false},
+//  CHECK-SAME:          bufferization.access = "read"
                         %B : tensor<?xf32> {linalg.inplaceable = true})
+//  CHECK-SAME:         bufferization.access = "read"
   -> (tensor<4xf32>, tensor<8xf32>)
 {
   // tensor.extract_slice is not used in a write, it is not compelled to
@@ -33,10 +35,13 @@ func @extract_slice_fun(%A : tensor<?xf32> {linalg.inplaceable = false},
 
 // -----
 
-// CHECK-LABEL: func @insert_slice_fun
+// CHECK-LABEL: func @insert_slice_fun(
 func @insert_slice_fun(%A : tensor<?xf32> {linalg.inplaceable = false},
+//  CHECK-SAME:        bufferization.access = "read"
                        %B : tensor<?xf32> {linalg.inplaceable = true},
+//  CHECK-SAME:        bufferization.access = "read-write"
                        %C : tensor<4xf32> {linalg.inplaceable = false})
+//  CHECK-SAME:        bufferization.access = "read"
   -> (tensor<?xf32>, tensor<?xf32>)
 {
   // must bufferize out of place.
@@ -56,9 +61,11 @@ func @insert_slice_fun(%A : tensor<?xf32> {linalg.inplaceable = false},
 
 // -----
 
-// CHECK-LABEL: func @conflict_on_B
+// CHECK-LABEL: func @conflict_on_B(
 func @conflict_on_B(%A : tensor<4x4xf32> {linalg.inplaceable = true},
+//  CHECK-SAME:     bufferization.access = "read"
                     %B : tensor<4x4xf32> {linalg.inplaceable = true})
+//  CHECK-SAME:     bufferization.access = "read-write"
   -> (tensor<4x4xf32>, tensor<4x4xf32>, tensor<4x4xf32>)
 {
   // matmul output operand interferes with input operand.
@@ -93,10 +100,12 @@ func @conflict_on_B(%A : tensor<4x4xf32> {linalg.inplaceable = true},
 
 // -----
 
-// CHECK-LABEL: func @extract_slice_extract_slice
+// CHECK-LABEL: func @extract_slice_extract_slice(
 func @extract_slice_extract_slice(
     %A : tensor<?xf32> {linalg.inplaceable = true},
+//  CHECK-SAME:         bufferization.access = "read"
     %B : tensor<?xf32> {linalg.inplaceable = false})
+//  CHECK-SAME:         bufferization.access = "read"
   -> (tensor<2xf32>, tensor<2xf32>)
 {
   // tensor.extract_slice is not used in a write, it is not compelled to
@@ -120,14 +129,20 @@ func @extract_slice_extract_slice(
 
 // -----
 
-// CHECK-LABEL: func @insert_slice_insert_slice
+// CHECK-LABEL: func @insert_slice_insert_slice(
 func @insert_slice_insert_slice(
     %A : tensor<?xf32> {linalg.inplaceable = true},
+//  CHECK-SAME:         bufferization.access = "read-write"
     %A2 : tensor<4xf32> {linalg.inplaceable = true},
+//  CHECK-SAME:          bufferization.access = "read-write"
     %A3 : tensor<2xf32> {linalg.inplaceable = true},
+//  CHECK-SAME:          bufferization.access = "read"
     %B : tensor<?xf32> {linalg.inplaceable = false},
+//  CHECK-SAME:         bufferization.access = "read"
     %B2 : tensor<4xf32> {linalg.inplaceable = false},
+//  CHECK-SAME:          bufferization.access = "read"
     %B3 : tensor<2xf32> {linalg.inplaceable = false})
+//  CHECK-SAME:          bufferization.access = "read"
   -> (tensor<?xf32>, tensor<?xf32>)
 {
   // CHECK: {__inplace_operands_attr__ = ["true", "true"]}
@@ -888,12 +903,16 @@ builtin.func @matmul_on_tensors(
 // prioritizing  the tensor.insert_slice ops.
 //===----------------------------------------------------------------------===//
 
+// CHECK-LABEL: func @insert_slice_chain(
 func @insert_slice_chain(
     %v1: vector<32x90xf32>,
     %v2: vector<30x90xf32>,
     %arg0: tensor<62x126xf32> {linalg.buffer_layout = affine_map<(d0, d1) -> (d0, d1)>, linalg.inplaceable = false},
+// CHECK-SAME: bufferization.access = "none"
     %arg1: tensor<126x90xf32> {linalg.buffer_layout = affine_map<(d0, d1) -> (d0, d1)>, linalg.inplaceable = false},
+// CHECK-SAME: bufferization.access = "none"
     %arg2: tensor<62x90xf32> {linalg.buffer_layout = affine_map<(d0, d1) -> (d0, d1)>, linalg.inplaceable = true})
+// CHECK-SAME: bufferization.access = "write"
   -> tensor<62x90xf32> attributes {passthrough = [["target-cpu", "skylake-avx512"], ["prefer-vector-width", "512"]]}
 {
   %c0 = arith.constant 0 : index
@@ -968,10 +987,13 @@ func @ip(%t: tensor<10x20xf32> {linalg.inplaceable = true},
   iterator_types = ["parallel"]
 }
 
-// CHECK-LABEL: func @linalg_op_same_out_tensors
+// CHECK-LABEL: func @linalg_op_same_out_tensors(
 func @linalg_op_same_out_tensors(
     %t1: tensor<?xf32> {linalg.inplaceable = true},
-    %t2: tensor<?xf32> {linalg.inplaceable = true}) -> (tensor<?xf32>, tensor<?xf32>){
+// CHECK-SAME:          bufferization.access = "read-write"
+    %t2: tensor<?xf32> {linalg.inplaceable = true})
+// CHECK-SAME:          bufferization.access = "write"
+  -> (tensor<?xf32>, tensor<?xf32>){
 
   //      CHECK: linalg.generic
   // CHECK-SAME: {__inplace_operands_attr__ = ["true", "true", "true"]
@@ -999,10 +1021,12 @@ func @linalg_op_same_out_tensors(
   iterator_types = ["parallel"]
 }
 
-// CHECK-LABEL: func @linalg_op_same_out_tensors_2
+// CHECK-LABEL: func @linalg_op_same_out_tensors_2(
 func @linalg_op_same_out_tensors_2(
     %t1: tensor<?xf32> {linalg.inplaceable = true},
+// CHECK-SAME:          bufferization.access = "read-write"
     %t2: tensor<?xf32> {linalg.inplaceable = true})
+// CHECK-SAME:          bufferization.access = "write"
         -> (tensor<?xf32>, tensor<?xf32>, tensor<?xf32>){
 
   //      CHECK: linalg.generic