[Mlir-commits] [mlir] [mlir][tosa] Harden folds/canonicalizations for unranked and dynamic shapes (PR #188188)

[Sayan Saha]

================
@@ -900,12 +900,77 @@ func.func @fold_resize_bilinear(%arg0 : tensor<1x15x13x1xi8>) -> tensor<1x15x13x
   %scale = tosa.const_shape { values = dense<[2, 2, 1, 1]> : tensor<4xindex> } : () -> !tosa.shape<4>
   %offset = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
   %border = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
-  %resize = tosa.resize %arg0, %scale, %offset, %border {mode = NEAREST_NEIGHBOR} : (tensor<1x15x13x1xi8>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<1x15x13x1xi8>
+  %resize = tosa.resize %arg0, %scale, %offset, %border {mode = BILINEAR} : (tensor<1x15x13x1xi8>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<1x15x13x1xi8>
   return %resize : tensor<1x15x13x1xi8>
 }
 
 // -----
 
+// ResizeOp::fold: unit scale (1:1 Y and X), zero offset/border, in/out types equal.
+// CHECK-LABEL: @fold_resize_identity_scale
+func.func @fold_resize_identity_scale(%arg0 : tensor<1x15x13x1xf32>) -> tensor<1x15x13x1xf32> {
+  // CHECK-NOT: tosa.resize
+  %scale = tosa.const_shape { values = dense<[1, 1, 1, 1]> : tensor<4xindex> } : () -> !tosa.shape<4>
+  %offset = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
+  %border = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
+  %resize = tosa.resize %arg0, %scale, %offset, %border {mode = NEAREST_NEIGHBOR} : (tensor<1x15x13x1xf32>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<1x15x13x1xf32>
+  return %resize : tensor<1x15x13x1xf32>
+}
+
+// -----
+// CHECK-LABEL: @fold_resize_identity_scale_to_unranked
+func.func @fold_resize_identity_scale_to_unranked(%arg0 : tensor<1x15x13x1xf32>) -> tensor<*xf32> {
+  // CHECK: tosa.resize
+  %scale = tosa.const_shape { values = dense<[1, 1, 1, 1]> : tensor<4xindex> } : () -> !tosa.shape<4>
+  %offset = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
+  %border = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
+  %resize = tosa.resize %arg0, %scale, %offset, %border {mode = NEAREST_NEIGHBOR} : (tensor<1x15x13x1xf32>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<*xf32>
+  return %resize : tensor<*xf32>
+}
+
+// -----
+
+// Same parameters except scale_y_n != scale_y_d: fold must not apply.
+// CHECK-LABEL: @resize_nofold_asymmetric_y_scale
+func.func @resize_nofold_asymmetric_y_scale(%arg0 : tensor<1x15x13x1xf32>) -> tensor<1x29x13x1xf32> {
+  // CHECK: tosa.resize
+  %scale = tosa.const_shape { values = dense<[4, 2, 1, 1]> : tensor<4xindex> } : () -> !tosa.shape<4>
+  %offset = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
+  %border = tosa.const_shape { values = dense<0> : tensor<2xindex> } : () -> !tosa.shape<2>
+  %resize = tosa.resize %arg0, %scale, %offset, %border {mode = NEAREST_NEIGHBOR} : (tensor<1x15x13x1xf32>, !tosa.shape<4>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<1x29x13x1xf32>
+  return %resize : tensor<1x29x13x1xf32>
+}
+
+// -----
+
+// CHECK-LABEL: @dont_canonicalize_unranked_clamp
+func.func @dont_canonicalize_unranked_clamp(%arg0 : tensor<*xf32>) -> tensor<*xf32> {
+  // CHECK: tosa.clamp
+  %0 = tosa.clamp %arg0 {min_val = 0.0 : f32, max_val = 1.0 : f32} : (tensor<*xf32>) -> tensor<*xf32>
+  return %0 : tensor<*xf32>
+}
+
+// -----
+
+// CHECK-LABEL: @dont_canonicalize_unranked_clamp
+func.func @dont_canonicalize_unranked_clamp(%arg0 : tensor<*xf32>) -> tensor<1xf32> {
----------------
sahas3 wrote:

```suggestion
func.func @dont_canonicalize_unranked_to_ranked_clamp(%arg0 : tensor<*xf32>) -> tensor<1xf32> {
```
to avoid the same name as above test point 

https://github.com/llvm/llvm-project/pull/188188