diff --git a/mlir/examples/toy/Ch4/CMakeLists.txt b/mlir/examples/toy/Ch4/CMakeLists.txt
--- a/mlir/examples/toy/Ch4/CMakeLists.txt
+++ b/mlir/examples/toy/Ch4/CMakeLists.txt
@@ -13,7 +13,6 @@
   parser/AST.cpp
   mlir/MLIRGen.cpp
   mlir/Dialect.cpp
-  mlir/DeadFunctionEliminationPass.cpp
   mlir/ShapeInferencePass.cpp
   mlir/ToyCombine.cpp
   )
diff --git a/mlir/examples/toy/Ch4/include/toy/Passes.h b/mlir/examples/toy/Ch4/include/toy/Passes.h
--- a/mlir/examples/toy/Ch4/include/toy/Passes.h
+++ b/mlir/examples/toy/Ch4/include/toy/Passes.h
@@ -20,7 +20,6 @@
 
 namespace toy {
 std::unique_ptr<Pass> createShapeInferencePass();
-std::unique_ptr<Pass> createDeadFunctionEliminationPass();
 } // end namespace toy
 } // end namespace mlir
 
diff --git a/mlir/examples/toy/Ch4/mlir/MLIRGen.cpp b/mlir/examples/toy/Ch4/mlir/MLIRGen.cpp
--- a/mlir/examples/toy/Ch4/mlir/MLIRGen.cpp
+++ b/mlir/examples/toy/Ch4/mlir/MLIRGen.cpp
@@ -170,6 +170,10 @@
                                                getType(VarType{})));
     }
 
+    // If this function isn't main, then set the visibility to private.
+    if (funcAST.getProto()->getName() != "main")
+      function.setVisibility(mlir::FuncOp::Visibility::Private);
+
     return function;
   }
 
diff --git a/mlir/examples/toy/Ch4/toyc.cpp b/mlir/examples/toy/Ch4/toyc.cpp
--- a/mlir/examples/toy/Ch4/toyc.cpp
+++ b/mlir/examples/toy/Ch4/toyc.cpp
@@ -119,7 +119,7 @@
 
     // Inline all functions into main and then delete them.
     pm.addPass(mlir::createInlinerPass());
-    pm.addPass(mlir::toy::createDeadFunctionEliminationPass());
+    pm.addPass(mlir::createSymbolDCEPass());
 
     // Now that there is only one function, we can infer the shapes of each of
     // the operations.
diff --git a/mlir/examples/toy/Ch5/CMakeLists.txt b/mlir/examples/toy/Ch5/CMakeLists.txt
--- a/mlir/examples/toy/Ch5/CMakeLists.txt
+++ b/mlir/examples/toy/Ch5/CMakeLists.txt
@@ -13,7 +13,6 @@
   parser/AST.cpp
   mlir/MLIRGen.cpp
   mlir/Dialect.cpp
-  mlir/DeadFunctionEliminationPass.cpp
   mlir/LowerToAffineLoops.cpp
   mlir/ShapeInferencePass.cpp
   mlir/ToyCombine.cpp
diff --git a/mlir/examples/toy/Ch5/include/toy/Passes.h b/mlir/examples/toy/Ch5/include/toy/Passes.h
--- a/mlir/examples/toy/Ch5/include/toy/Passes.h
+++ b/mlir/examples/toy/Ch5/include/toy/Passes.h
@@ -19,7 +19,6 @@
 class Pass;
 
 namespace toy {
-std::unique_ptr<Pass> createDeadFunctionEliminationPass();
 std::unique_ptr<Pass> createShapeInferencePass();
 
 /// Create a pass for lowering to operations in the `Affine` and `Std` dialects,
diff --git a/mlir/examples/toy/Ch5/mlir/MLIRGen.cpp b/mlir/examples/toy/Ch5/mlir/MLIRGen.cpp
--- a/mlir/examples/toy/Ch5/mlir/MLIRGen.cpp
+++ b/mlir/examples/toy/Ch5/mlir/MLIRGen.cpp
@@ -170,6 +170,10 @@
                                                getType(VarType{})));
     }
 
+    // If this function isn't main, then set the visibility to private.
+    if (funcAST.getProto()->getName() != "main")
+      function.setVisibility(mlir::FuncOp::Visibility::Private);
+
     return function;
   }
 
diff --git a/mlir/examples/toy/Ch5/toyc.cpp b/mlir/examples/toy/Ch5/toyc.cpp
--- a/mlir/examples/toy/Ch5/toyc.cpp
+++ b/mlir/examples/toy/Ch5/toyc.cpp
@@ -124,7 +124,7 @@
   if (enableOpt || isLoweringToAffine) {
     // Inline all functions into main and then delete them.
     pm.addPass(mlir::createInlinerPass());
-    pm.addPass(mlir::toy::createDeadFunctionEliminationPass());
+    pm.addPass(mlir::createSymbolDCEPass());
 
     // Now that there is only one function, we can infer the shapes of each of
     // the operations.
diff --git a/mlir/examples/toy/Ch6/CMakeLists.txt b/mlir/examples/toy/Ch6/CMakeLists.txt
--- a/mlir/examples/toy/Ch6/CMakeLists.txt
+++ b/mlir/examples/toy/Ch6/CMakeLists.txt
@@ -14,7 +14,6 @@
   parser/AST.cpp
   mlir/MLIRGen.cpp
   mlir/Dialect.cpp
-  mlir/DeadFunctionEliminationPass.cpp
   mlir/LowerToAffineLoops.cpp
   mlir/LowerToLLVM.cpp
   mlir/ShapeInferencePass.cpp
diff --git a/mlir/examples/toy/Ch6/include/toy/Passes.h b/mlir/examples/toy/Ch6/include/toy/Passes.h
--- a/mlir/examples/toy/Ch6/include/toy/Passes.h
+++ b/mlir/examples/toy/Ch6/include/toy/Passes.h
@@ -19,7 +19,6 @@
 class Pass;
 
 namespace toy {
-std::unique_ptr<Pass> createDeadFunctionEliminationPass();
 std::unique_ptr<Pass> createShapeInferencePass();
 
 /// Create a pass for lowering to operations in the `Affine` and `Std` dialects,
diff --git a/mlir/examples/toy/Ch6/mlir/MLIRGen.cpp b/mlir/examples/toy/Ch6/mlir/MLIRGen.cpp
--- a/mlir/examples/toy/Ch6/mlir/MLIRGen.cpp
+++ b/mlir/examples/toy/Ch6/mlir/MLIRGen.cpp
@@ -170,6 +170,10 @@
                                                getType(VarType{})));
     }
 
+    // If this function isn't main, then set the visibility to private.
+    if (funcAST.getProto()->getName() != "main")
+      function.setVisibility(mlir::FuncOp::Visibility::Private);
+
     return function;
   }
 
diff --git a/mlir/examples/toy/Ch6/toyc.cpp b/mlir/examples/toy/Ch6/toyc.cpp
--- a/mlir/examples/toy/Ch6/toyc.cpp
+++ b/mlir/examples/toy/Ch6/toyc.cpp
@@ -138,7 +138,7 @@
   if (enableOpt || isLoweringToAffine) {
     // Inline all functions into main and then delete them.
     pm.addPass(mlir::createInlinerPass());
-    pm.addPass(mlir::toy::createDeadFunctionEliminationPass());
+    pm.addPass(mlir::createSymbolDCEPass());
 
     // Now that there is only one function, we can infer the shapes of each of
     // the operations.
diff --git a/mlir/examples/toy/Ch7/CMakeLists.txt b/mlir/examples/toy/Ch7/CMakeLists.txt
--- a/mlir/examples/toy/Ch7/CMakeLists.txt
+++ b/mlir/examples/toy/Ch7/CMakeLists.txt
@@ -14,7 +14,6 @@
   parser/AST.cpp
   mlir/MLIRGen.cpp
   mlir/Dialect.cpp
-  mlir/DeadFunctionEliminationPass.cpp
   mlir/LowerToAffineLoops.cpp
   mlir/LowerToLLVM.cpp
   mlir/ShapeInferencePass.cpp
diff --git a/mlir/examples/toy/Ch7/include/toy/Passes.h b/mlir/examples/toy/Ch7/include/toy/Passes.h
--- a/mlir/examples/toy/Ch7/include/toy/Passes.h
+++ b/mlir/examples/toy/Ch7/include/toy/Passes.h
@@ -19,7 +19,6 @@
 class Pass;
 
 namespace toy {
-std::unique_ptr<Pass> createDeadFunctionEliminationPass();
 std::unique_ptr<Pass> createShapeInferencePass();
 
 /// Create a pass for lowering to operations in the `Affine` and `Std` dialects,
diff --git a/mlir/examples/toy/Ch7/mlir/MLIRGen.cpp b/mlir/examples/toy/Ch7/mlir/MLIRGen.cpp
--- a/mlir/examples/toy/Ch7/mlir/MLIRGen.cpp
+++ b/mlir/examples/toy/Ch7/mlir/MLIRGen.cpp
@@ -223,6 +223,10 @@
                                                *returnOp.operand_type_begin()));
     }
 
+    // If this function isn't main, then set the visibility to private.
+    if (funcAST.getProto()->getName() != "main")
+      function.setVisibility(mlir::FuncOp::Visibility::Private);
+
     return function;
   }
 
diff --git a/mlir/examples/toy/Ch7/toyc.cpp b/mlir/examples/toy/Ch7/toyc.cpp
--- a/mlir/examples/toy/Ch7/toyc.cpp
+++ b/mlir/examples/toy/Ch7/toyc.cpp
@@ -138,7 +138,7 @@
   if (enableOpt || isLoweringToAffine) {
     // Inline all functions into main and then delete them.
     pm.addPass(mlir::createInlinerPass());
-    pm.addPass(mlir::toy::createDeadFunctionEliminationPass());
+    pm.addPass(mlir::createSymbolDCEPass());
 
     // Now that there is only one function, we can infer the shapes of each of
     // the operations.
diff --git a/mlir/test/Examples/Toy/Ch4/shape_inference.mlir b/mlir/test/Examples/Toy/Ch4/shape_inference.mlir
--- a/mlir/test/Examples/Toy/Ch4/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch4/shape_inference.mlir
@@ -2,7 +2,8 @@
 
 // Check the result of inlining+shape inference on an input module.
 
-func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
+func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64>
+    attributes { sym_visibility = "private" } {
   %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>
diff --git a/mlir/test/Examples/Toy/Ch5/shape_inference.mlir b/mlir/test/Examples/Toy/Ch5/shape_inference.mlir
--- a/mlir/test/Examples/Toy/Ch5/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch5/shape_inference.mlir
@@ -2,7 +2,8 @@
 
 // Check the result of inlining+shape inference on an input module.
 
-func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
+func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64>
+    attributes { sym_visibility = "private" } {
   %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>
diff --git a/mlir/test/Examples/Toy/Ch6/shape_inference.mlir b/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
--- a/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch6/shape_inference.mlir
@@ -2,7 +2,8 @@
 
 // Check the result of inlining+shape inference on an input module.
 
-func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
+func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64>
+    attributes { sym_visibility = "private" } {
   %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>
diff --git a/mlir/test/Examples/Toy/Ch7/shape_inference.mlir b/mlir/test/Examples/Toy/Ch7/shape_inference.mlir
--- a/mlir/test/Examples/Toy/Ch7/shape_inference.mlir
+++ b/mlir/test/Examples/Toy/Ch7/shape_inference.mlir
@@ -2,7 +2,8 @@
 
 // Check the result of inlining+shape inference on an input module.
 
-func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64> {
+func @multiply_transpose(%arg0: tensor<*xf64>, %arg1: tensor<*xf64>) -> tensor<*xf64>
+    attributes { sym_visibility = "private" } {
   %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>
diff --git a/mlir/test/Examples/Toy/Ch7/struct-codegen.toy b/mlir/test/Examples/Toy/Ch7/struct-codegen.toy
--- a/mlir/test/Examples/Toy/Ch7/struct-codegen.toy
+++ b/mlir/test/Examples/Toy/Ch7/struct-codegen.toy
@@ -1,4 +1,4 @@
-# RUN: toyc-ch7 %s -emit=mlir 2>&1
+# RUN: toyc-ch7 %s -emit=mlir 2>&1 | FileCheck %s
 # RUN: toyc-ch7 %s -emit=mlir -opt 2>&1 | FileCheck %s --check-prefix=OPT
 
 struct Struct {
@@ -23,6 +23,7 @@
 
 # CHECK-LABEL:   func @multiply_transpose(
 # CHECK-SAME:                             [[VAL_0:%.*]]: !toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64>
+# CHECK-SAME:        attributes {sym_visibility = "private"}
 # CHECK-NEXT:      [[VAL_1:%.*]] = "toy.struct_access"([[VAL_0]]) {index = 0 : i64} : (!toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64>
 # CHECK-NEXT:      [[VAL_2:%.*]] = "toy.transpose"([[VAL_1]]) : (tensor<*xf64>) -> tensor<*xf64>
 # CHECK-NEXT:      [[VAL_3:%.*]] = "toy.struct_access"([[VAL_0]]) {index = 1 : i64} : (!toy.struct<tensor<*xf64>, tensor<*xf64>>) -> tensor<*xf64>