diff --git a/src/tim/transform/layout_inference.cc b/src/tim/transform/layout_inference.cc
index c9de876..7fd00dd 100644
--- a/src/tim/transform/layout_inference.cc
+++ b/src/tim/transform/layout_inference.cc
@@ -181,6 +181,7 @@ void LayoutInferContext::UpdateGraphOutputMap(const std::shared_ptr<vx::Tensor>&
       REGIST_LAYOUT_INFERENCE(VSI_NN_REDUCE_PROD, ReduceProd);                 \
       REGIST_LAYOUT_INFERENCE(VSI_NN_REDUCE_ANY, ReduceAny);                   \
       REGIST_LAYOUT_INFERENCE(VSI_NN_REDUCE_SUM, ReduceSum);                   \
+      REGIST_LAYOUT_INFERENCE(VSI_NN_REDUCE_ALL, ReduceAll);                   \
     default:                                                                   \
       VSILOGW("Op %d: Default layout inference pass for reduce.", reduce_type);\
       assert(false);                                                           \
diff --git a/src/tim/transform/ops/reduce_layout_inference.h b/src/tim/transform/ops/reduce_layout_inference.h
index 2544f32..7a03463 100644
--- a/src/tim/transform/ops/reduce_layout_inference.h
+++ b/src/tim/transform/ops/reduce_layout_inference.h
@@ -89,6 +89,7 @@ using ReduceAnyLayoutInfer = ReduceLayoutInfer<tim::vx::ops::ReduceAny>;
 using ReduceProdLayoutInfer = ReduceLayoutInfer<tim::vx::ops::ReduceProd>;
 using ReduceMeanLayoutInfer = ReduceLayoutInfer<tim::vx::ops::ReduceMean>;
 using ReduceSumLayoutInfer = ReduceLayoutInfer<tim::vx::ops::ReduceSum>;
+using ReduceAllLayoutInfer = ReduceLayoutInfer<tim::vx::ops::ReduceAll>;
 }  // namespace transform
 }  // namespace tim
 
diff --git a/src/tim/vx/ops/reduce_sum_test.cc b/src/tim/vx/ops/reduce_test.cc
similarity index 60%
rename from src/tim/vx/ops/reduce_sum_test.cc
rename to src/tim/vx/ops/reduce_test.cc
index c524c5d..b294db5 100644
--- a/src/tim/vx/ops/reduce_sum_test.cc
+++ b/src/tim/vx/ops/reduce_test.cc
@@ -128,4 +128,105 @@ TEST(Reduce_sum, KeepDims) {
   std::vector<float> output(golden.size());
   EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
   EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
+}
+
+TEST(Reduce_all, KeepDims) {
+  auto ctx = tim::vx::Context::Create();
+
+  auto graph = ctx->CreateGraph();
+  tim::vx::ShapeType input_shape({2, 3, 2});
+  tim::vx::ShapeType output_shape({1, 3, 1});
+
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::BOOL8, input_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8, output_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+
+  std::vector<int32_t> axis = {2, 0};
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto output_tensor = graph->CreateTensor(output_spec);
+  auto reduce_all = graph->CreateOperation<tim::vx::ops::ReduceAll>(axis, true);
+  (*reduce_all).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+  bool in_data[] = {true, true, true,  true, true, true,
+                    true, true, false, true, true, true};
+  bool golden[] = {true, false, true};
+  bool* p_in = in_data;
+  input_tensor->CopyDataToTensor(p_in, 12 * sizeof(bool));
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+
+  bool output[3 * sizeof(bool)];
+  bool* p_output = output;
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(p_output));
+  for (int i = 0; i < 3; ++i) {
+    EXPECT_TRUE(golden[i] == output[i]);
+  }
+}
+
+TEST(Reduce_all, NotKeepDims) {
+  auto ctx = tim::vx::Context::Create();
+
+  auto graph = ctx->CreateGraph();
+  tim::vx::ShapeType input_shape({2, 3, 2});
+  tim::vx::ShapeType output_shape({2});
+
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::BOOL8, input_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::BOOL8, output_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+
+  std::vector<int32_t> axis = {1, 2, 2, 2};
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto output_tensor = graph->CreateTensor(output_spec);
+  auto reduce_all =
+      graph->CreateOperation<tim::vx::ops::ReduceAll>(axis, false);
+  (*reduce_all).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+  bool in_data[] = {true, true, true, true, true, false,
+                    true, true, true, true, true, true};
+  bool golden[] = {true, false};
+  bool* p_in = in_data;
+  input_tensor->CopyDataToTensor(p_in, 12 * sizeof(bool));
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+
+  bool output[2 * sizeof(bool)];
+  bool* p_output = output;
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(p_output));
+  for (int i = 0; i < 2; ++i) {
+    EXPECT_TRUE(golden[i] == output[i]);
+  }
+}
+
+TEST(Reduce_max, NotKeepDims) {
+  auto ctx = tim::vx::Context::Create();
+
+  auto graph = ctx->CreateGraph();
+  tim::vx::ShapeType input_shape({2, 3});
+  tim::vx::ShapeType output_shape({3});
+
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, input_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, output_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto output_tensor = graph->CreateTensor(output_spec);
+  std::vector<int32_t> axis = {0};
+  auto reduce_sum = graph->CreateOperation<tim::vx::ops::ReduceMax>(axis, false);
+  (*reduce_sum).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+  std::vector<float> in_data = {-1.0f, -2.0f, 3.0f, 4.0f, 5.0f, -6.0f};
+  std::vector<float> golden = {-1.0f, 4.0f, 5.0f};
+
+  EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+
+  std::vector<float> output(golden.size());
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+  EXPECT_EQ(golden, output);
 }
\ No newline at end of file