1 files changed, 30 insertions, 0 deletions
diff --git a/mlir/test/Examples/Toy/Ch6/shape_inference.mlir b/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
new file mode 100644
index 00000000000..199446c188c
--- /dev/null
+++ b/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
@@ -0,0 +1,30 @@
+// RUN: toyc-ch6 %s -emit=mlir -opt 2>&1 | FileCheck %s
+
+// Check the result of inlining+shape inference on an input module.
+
+func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
+  %0 = "toy.transpose"(%arg0) : (tensor<*xf64>) -> tensor<*xf64>
+  %1 = "toy.transpose"(%arg1) : (tensor<*xf64>) -> tensor<*xf64>
+  %2 = "toy.mul"(%0, %1) : (tensor<*xf64>, tensor<*xf64>) -> tensor<*xf64>
+  "toy.return"(%2) : (tensor<*xf64>) -> ()
+}
+func @main() {
+  %0 = "toy.constant"() {value = dense<[[1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+  %1 = "toy.reshape"(%0) : (tensor<2x3xf64>) -> tensor<2x3xf64>
+  %2 = "toy.constant"() {value = dense<[1.000000e+00, 2.000000e+00, 3.000000e+00, 4.000000e+00, 5.000000e+00, 6.000000e+00]> : tensor<6xf64>} : () -> tensor<6xf64>
+  %3 = "toy.reshape"(%2) : (tensor<6xf64>) -> tensor<2x3xf64>
+  %4 = "toy.generic_call"(%1, %3) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+  %5 = "toy.generic_call"(%3, %1) {callee = @multiply_transpose} : (tensor<2x3xf64>, tensor<2x3xf64>) -> tensor<*xf64>
+  "toy.print"(%5) : (tensor<*xf64>) -> ()
+  "toy.return"() : () -> ()
+}
+
+// CHECK-NOT: func @multiply_transpose
+// CHECK-NOT: tensor<*xf64>
+
+// CHECK-LABEL: func @main()
+// CHECK:         [[VAL_0:%.*]] = "toy.constant"() {value = dense<{{\[\[}}1.000000e+00, 2.000000e+00, 3.000000e+00], [4.000000e+00, 5.000000e+00, 6.000000e+00]]> : tensor<2x3xf64>} : () -> tensor<2x3xf64>
+// CHECK:         [[VAL_1:%.*]] = "toy.transpose"([[VAL_0]]) : (tensor<2x3xf64>) -> tensor<3x2xf64>
+// CHECK:         [[VAL_2:%.*]] = "toy.mul"([[VAL_1]], [[VAL_1]]) : (tensor<3x2xf64>, tensor<3x2xf64>) -> tensor<3x2xf64>
+// CHECK:         "toy.print"([[VAL_2]]) : (tensor<3x2xf64>) -> ()
+// CHECK:         "toy.return"() : () -> ()