Modify the syntax of the the ElementsAttrs to print the type as a colon type.

This is the standard syntax for types on operations, and is also already used by IntegerAttr and FloatAttr.

Example:
  dense<5> : tensor<i32>
  dense<[3]> : tensor<1xi32>
PiperOrigin-RevId: 255069157

2 files changed, 13 insertions, 13 deletions

diff --git a/mlir/test/Quantizer/matmul.mlir b/mlir/test/Quantizer/matmul.mlir
index c2071624475..645f368caba 100644
--- a/mlir/test/Quantizer/matmul.mlir
+++ b/mlir/test/Quantizer/matmul.mlir
@@ -3,30 +3,30 @@
 // ----
 // A matmul without fused clamp or bias.
 // CHECK-LABEL: @matmul
-// CHECK: %cst = constant dense<tensor<3x5xi8>
+// CHECK: %cst = constant dense{{.*}}tensor<3x5xi8>
 // CHECK-NEXT: %0 = "quant.qcast"(%arg0) : (tensor<300x3xf32>) -> tensor<300x3x!quant.uniform<i8:f32, 0.037564418067230126:35>>
 // CHECK-NEXT: %1 = "quant.scast"(%cst) : (tensor<3x5xi8>) -> tensor<3x5x!quant.uniform<i8:f32, 0.0062823070315864236:-1>>
 // CHECK-NEXT: %2 = "fxpmath.real_matmul"(%0, %1) : (tensor<300x3x!quant.uniform<i8:f32, 0.037564418067230126:35>>, tensor<3x5x!quant.uniform<i8:f32, 0.0062823070315864236:-1>>) -> tensor<300x5x!quant.uniform<i8:f32, 0.0629921259842528:-1>>
 // CHECK-NEXT: %3 = "quant.dcast"(%2) : (tensor<300x5x!quant.uniform<i8:f32, 0.0629921259842528:-1>>) -> tensor<300x5xf32>
 func @matmul(%arg0: tensor<300x3xf32>) -> tensor<300x5xf32> {
-  %0 = "quant.stats"(%arg0) {layerStats: dense<tensor<2xf32>, [-6.123e+00, 3.45e+00]>} : (tensor<300x3xf32>) -> tensor<300x3xf32>
-  %cst = constant  {name: "constant.35"} dense<tensor<3x5xf32>, [[-1.060230e-01, 1.215050e-01, 8.002390e-01, -7.688850e-01, 0.0966112986], [6.890140e-01, -4.070560e-01, -0.797852993, 3.789250e-03, -2.088810e-01], [-6.085290e-01, 2.766170e-02, 2.685570e-01, 5.774010e-01, -4.284370e-01]]>
+  %0 = "quant.stats"(%arg0) {layerStats: dense<[-6.123e+00, 3.45e+00]> : tensor<2xf32>} : (tensor<300x3xf32>) -> tensor<300x3xf32>
+  %cst = constant  {name: "constant.35"} dense<[[-1.060230e-01, 1.215050e-01, 8.002390e-01, -7.688850e-01, 0.0966112986], [6.890140e-01, -4.070560e-01, -0.797852993, 3.789250e-03, -2.088810e-01], [-6.085290e-01, 2.766170e-02, 2.685570e-01, 5.774010e-01, -4.284370e-01]]> : tensor<3x5xf32>
   %1 = "fxpmath.real_matmul"(%0, %cst) : (tensor<300x3xf32>, tensor<3x5xf32>) -> tensor<300x5xf32>
-  %2 = "quant.stats"(%1) {layerStats: dense<tensor<2xf32>, [-8.000000e+00, 8.000000e+00]>} : (tensor<300x5xf32>) -> tensor<300x5xf32>
+  %2 = "quant.stats"(%1) {layerStats: dense<[-8.000000e+00, 8.000000e+00]> : tensor<2xf32>} : (tensor<300x5xf32>) -> tensor<300x5xf32>
   return %2 : tensor<300x5xf32>
 }
 
 // ----
 // A matmul with fused clamp which serves as statistics for the result.
 // CHECK-LABEL: @matmul_clamp
-// CHECK: %cst = constant dense<tensor<3x5xi8>
+// CHECK: %cst = constant dense{{.*}}tensor<3x5xi8>
 // CHECK-NEXT: %0 = "quant.qcast"(%arg0) : (tensor<300x3xf32>) -> tensor<300x3x!quant.uniform<i8:f32, 0.037564418067230126:35>>
 // CHECK-NEXT: %1 = "quant.scast"(%cst) : (tensor<3x5xi8>) -> tensor<3x5x!quant.uniform<i8:f32, 0.0062823070315864236:-1>>
 // CHECK-NEXT: %2 = "fxpmath.real_matmul"(%0, %1) {clamp_max: 6.100000e+00 : f64, clamp_min: -1.225000e+01 : f64} : (tensor<300x3x!quant.uniform<i8:f32, 0.037564418067230126:35>>, tensor<3x5x!quant.uniform<i8:f32, 0.0062823070315864236:-1>>) -> tensor<300x5x!quant.uniform<i8:f32, 0.072058823529412216:42>>
 // CHECK-NEXT: %3 = "quant.dcast"(%2) : (tensor<300x5x!quant.uniform<i8:f32, 0.072058823529412216:42>>) -> tensor<300x5xf32>
 func @matmul_clamp(%arg0: tensor<300x3xf32>) -> tensor<300x5xf32> {
-  %0 = "quant.stats"(%arg0) {layerStats: dense<tensor<2xf32>, [-6.123e+00, 3.45e+00]>} : (tensor<300x3xf32>) -> tensor<300x3xf32>
-  %cst = constant  {name: "constant.35"} dense<tensor<3x5xf32>, [[-1.060230e-01, 1.215050e-01, 8.002390e-01, -7.688850e-01, 0.0966112986], [6.890140e-01, -4.070560e-01, -0.797852993, 3.789250e-03, -2.088810e-01], [-6.085290e-01, 2.766170e-02, 2.685570e-01, 5.774010e-01, -4.284370e-01]]>
+  %0 = "quant.stats"(%arg0) {layerStats: dense<[-6.123e+00, 3.45e+00]> : tensor<2xf32>} : (tensor<300x3xf32>) -> tensor<300x3xf32>
+  %cst = constant  {name: "constant.35"} dense<[[-1.060230e-01, 1.215050e-01, 8.002390e-01, -7.688850e-01, 0.0966112986], [6.890140e-01, -4.070560e-01, -0.797852993, 3.789250e-03, -2.088810e-01], [-6.085290e-01, 2.766170e-02, 2.685570e-01, 5.774010e-01, -4.284370e-01]]> : tensor<3x5xf32>
   %1 = "fxpmath.real_matmul"(%0, %cst) {clamp_max: 6.10, clamp_min: -12.25} : (tensor<300x3xf32>, tensor<3x5xf32>) -> tensor<300x5xf32>
   return %1 : tensor<300x5xf32>
 }
@@ -34,17 +34,17 @@ func @matmul_clamp(%arg0: tensor<300x3xf32>) -> tensor<300x5xf32> {
 // ----
 // A matmul with bias and clamp.
 // CHECK-LABEL: @matmul_add_clamp
-// CHECK: %cst = constant dense<tensor<3x5xi8>
-// CHECK-NEXT: %cst_0 = constant dense<tensor<5xi32>, [14, 28, 42, 56, 69]>
+// CHECK: %cst = constant dense{{.*}}tensor<3x5xi8>
+// CHECK-NEXT: %cst_0 = constant dense<[14, 28, 42, 56, 69]> : tensor<5xi32>
 // CHECK-NEXT: %0 = "quant.qcast"(%arg0) : (tensor<300x3xf32>) -> tensor<300x3x!quant.uniform<i8:f32, 0.037564418067230126:35>>
 // CHECK-NEXT: %1 = "quant.scast"(%cst) : (tensor<3x5xi8>) -> tensor<3x5x!quant.uniform<i8:f32, 0.0062823070315864236:-1>>
 // CHECK-NEXT: %2 = "quant.scast"(%cst_0) : (tensor<5xi32>) -> tensor<5x!quant.uniform<i32:f32, 0.072058823529412216>>
 // CHECK-NEXT: %3 = "fxpmath.real_matmul_bias"(%0, %1, %2) {clamp_max: 6.100000e+00 : f64, clamp_min: -1.225000e+01 : f64} : (tensor<300x3x!quant.uniform<i8:f32, 0.037564418067230126:35>>, tensor<3x5x!quant.uniform<i8:f32, 0.0062823070315864236:-1>>, tensor<5x!quant.uniform<i32:f32, 0.072058823529412216>>) -> tensor<300x5x!quant.uniform<i8:f32, 0.072058823529412216:42>>
 // CHECK-NEXT: %4 = "quant.dcast"(%3) : (tensor<300x5x!quant.uniform<i8:f32, 0.072058823529412216:42>>) -> tensor<300x5xf32>
 func @matmul_add_clamp(%arg0: tensor<300x3xf32>) -> tensor<300x5xf32> {
-  %0 = "quant.stats"(%arg0) {layerStats: dense<tensor<2xf32>, [-6.123e+00, 3.45e+00]>} : (tensor<300x3xf32>) -> tensor<300x3xf32>
-  %cst = constant  {name: "constant.35"} dense<tensor<3x5xf32>, [[-1.060230e-01, 1.215050e-01, 8.002390e-01, -7.688850e-01, 0.0966112986], [6.890140e-01, -4.070560e-01, -0.797852993, 3.789250e-03, -2.088810e-01], [-6.085290e-01, 2.766170e-02, 2.685570e-01, 5.774010e-01, -4.284370e-01]]>
-  %cst_0 = constant  {name: "constant.37"} dense<tensor<5xf32>, [1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00]>
+  %0 = "quant.stats"(%arg0) {layerStats: dense<[-6.123e+00, 3.45e+00]> : tensor<2xf32>} : (tensor<300x3xf32>) -> tensor<300x3xf32>
+  %cst = constant  {name: "constant.35"} dense<[[-1.060230e-01, 1.215050e-01, 8.002390e-01, -7.688850e-01, 0.0966112986], [6.890140e-01, -4.070560e-01, -0.797852993, 3.789250e-03, -2.088810e-01], [-6.085290e-01, 2.766170e-02, 2.685570e-01, 5.774010e-01, -4.284370e-01]]> : tensor<3x5xf32>
+  %cst_0 = constant  {name: "constant.37"} dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00]> : tensor<5xf32>
   %1 = "fxpmath.real_matmul_bias"(%0, %cst, %cst_0) {clamp_max: 6.10, clamp_min: -12.25} : (tensor<300x3xf32>, tensor<3x5xf32>, tensor<5xf32>) -> tensor<300x5xf32>
   return %1 : tensor<300x5xf32>
 }
diff --git a/mlir/test/Quantizer/remove-instrumentation.mlir b/mlir/test/Quantizer/remove-instrumentation.mlir
index 222ddf751bd..2adae893b67 100644
--- a/mlir/test/Quantizer/remove-instrumentation.mlir
+++ b/mlir/test/Quantizer/remove-instrumentation.mlir
@@ -4,7 +4,7 @@
 // CHECK-LABEL: remove_ops
 func @remove_ops(%arg0: tensor<8x4x3xf32>) -> tensor<8x4x3xf32> {
   %0 = "quant.stats"(%arg0) {
-    layerStats: dense<tensor<2xf32>, [-1.0, 1.0]>
+    layerStats: dense<[-1.0, 1.0]> : tensor<2xf32>
   } : (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>
   %1 = "quant.coupled_ref"(%0) { coupledKey: "foobar" } :
       (tensor<8x4x3xf32>) -> tensor<8x4x3xf32>