op unittest for repeat/arange/reverse/elementwise_add_grad/flip

cinn/frontend/net_builder.cc

@@ -816,11 +816,7 @@ Variable NetBuilder::Arange(const float start, const float stop, const float ste
 }
 
 Variable NetBuilder::Flip(const Variable& operand, const std::vector<int>& axes) {
-  Instruction instr("flip", {operand});
-  instr.SetAttr("axes", axes);
-  InferShape(instr);
-  AppendInstruction(instr);
-  return instr.GetOutput(0);
+  return CustomInstr("reverse", {operand}, {{"axis", utils::GetPositiveAxes(axes, operand->shape.size())}}).front();
 }
 
 Variable NetBuilder::Matmul(const Variable& x, const Variable& y, bool trans_x, bool trans_y, float alpha) {

cinn/frontend/net_builder.h

@@ -901,7 +901,10 @@ class NetBuilder {
                   const std::string& padding_algorithm = "EXPLICIT");
 
   /**
-   * This API flipes the Variable x along the given axis.
+   * @brief This API reverse the Variable x along the given axis.
+   * @param x An N-D variable.
+   * @param axis Specify the axis to operate on the input reverse.
+   * @return A reversed variable with the same data type as x.
    */
   Variable Flip(const Variable& operand, const std::vector<int>& axes);
 

cinn/frontend/net_builder_test.cc

@@ -984,76 +984,6 @@ TEST(net_build, program_execute_arange_int) {
   }
 }
 
-TEST(net_build, program_execute_flip) {
-  const int C = 2;
-  const int H = 2;
-  const int W = 2;
-  const std::vector<int> axes{0};
-
-  NetBuilder builder("net_builder");
-  Placeholder input = builder.CreateInput(Float(32), {C, H, W}, "Img");
-  Variable output   = builder.Flip(input, axes);
-  auto program      = builder.Build();
-
-#ifdef CINN_WITH_CUDA
-  Target target = common::DefaultNVGPUTarget();
-#else
-  Target target = common::DefaultHostTarget();
-#endif
-  std::unordered_set<std::string> fetch_ids;
-  auto graph = Optimize(&program, fetch_ids, target);
-
-  auto scope = BuildScope(target, graph);
-  hlir::framework::GraphCompiler gc(target, scope, graph);
-  auto runtime_program = gc.Build();
-
-  scope->Var<hlir::framework::Tensor>(std::string(input.id()));
-  scope->Var<hlir::framework::Tensor>(std::string(output->id));
-
-  auto input_tensor = scope->GetTensor(std::string(input.id()));
-  SetRandData<float>(input_tensor, target);
-  std::vector<float> input_data = GetTensorData<float>(input_tensor, target);
-
-  runtime_program->Execute();
-  auto output_tensor                   = scope->GetTensor(std::string(output->id));
-  const std::vector<int>& output_shape = output_tensor->shape().data();
-  EXPECT_EQ(output_tensor->type(), Float(32));
-  EXPECT_EQ(output_shape.size(), 3UL);
-  EXPECT_EQ(output_shape[0], C);
-  EXPECT_EQ(output_shape[1], H);
-  EXPECT_EQ(output_shape[2], W);
-
-  std::vector<float> output_data = GetTensorData<float>(output_tensor, target);
-  VLOG(6) << "Visualize flip input_data";
-  for (int c = 0; c < C; c++) {
-    for (int h = 0; h < H; h++) {
-      std::string line;
-      for (int w = 0; w < W; w++) {
-        int index = c * (H * W) + h * W + w;
-        line += (std::to_string(index) + ": " + std::to_string(input_data[index]) + ", ");
-      }
-      VLOG(6) << line;
-    }
-  }
-
-  VLOG(6) << "Visualize flip output_data";
-  for (int c = 0; c < C; c++) {
-    int flip_c = std::find(axes.begin(), axes.end(), 0) == axes.end() ? c : C - c - 1;
-    for (int h = 0; h < H; h++) {
-      std::string line;
-      int flip_h = std::find(axes.begin(), axes.end(), 1) == axes.end() ? h : H - h - 1;
-      for (int w = 0; w < W; w++) {
-        int flip_w     = std::find(axes.begin(), axes.end(), 2) == axes.end() ? w : W - w - 1;
-        int flip_index = flip_c * H * W + flip_h * W + flip_w;
-        int index      = c * (H * W) + h * W + w;
-        line += (std::to_string(index) + ": " + std::to_string(output_data[index]) + ", ");
-        EXPECT_EQ(input_data[index], output_data[flip_index]);
-      }
-      VLOG(6) << line;
-    }
-  }
-}
-
 TEST(net_build, program_argmax_case1) {
   const int N     = 4;
   const int IN_C  = 3;

cinn/hlir/op/contrib/CMakeLists.txt

@@ -2,7 +2,6 @@ core_gather_headers()
 
 gather_srcs(cinnapi_src SRCS
         gather_nd.cc
-        flip.cc
         sort.cc
         argmin.cc
         argmax.cc
@@ -24,7 +23,6 @@ cc_test(test_gather_nd SRCS gather_nd_test.cc DEPS cinncore)
 cc_test(test_sort SRCS sort_test.cc DEPS cinncore)
 cc_test(test_argmin SRCS argmin_test.cc DEPS cinncore)
 cc_test(test_argmax SRCS argmax_test.cc DEPS cinncore)
-cc_test(test_flip SRCS flip_test.cc DEPS cinncore)
 cc_test(test_repeat SRCS repeat_test.cc DEPS cinncore)
 cc_test(test_one_hot SRCS one_hot_test.cc DEPS cinncore)
 cc_test(test_lookup_table SRCS lookup_table_test.cc DEPS cinncore)

cinn/hlir/op/transform.cc

@@ -831,7 +831,6 @@ std::shared_ptr<OpStrategy> StrategyForReverse(const framework::NodeAttr &attrs,
   std::vector<int> axis;
   if (attrs.attr_store.find("axis") != attrs.attr_store.end()) {
     axis = absl::get<std::vector<int>>(attrs.attr_store.at("axis"));
-    CHECK(!axis.empty()) << "axis is empty! Please check setting.\n";
     for (auto &e : axis) {
       if (e >= static_cast<int>(output_shapes[0].size()) || e < -1 * static_cast<int>(output_shapes[0].size())) {
         LOG(FATAL) << "axis is not in [0, n_dim), Please check.";
@@ -840,8 +839,6 @@ std::shared_ptr<OpStrategy> StrategyForReverse(const framework::NodeAttr &attrs,
         e += output_shapes[0].size();
       }
     }
-  } else {
-    LOG(FATAL) << "axis is not be set! Please check.";
   }
 
   framework::CINNCompute reverse_compute([=](lang::Args args, lang::RetValue *ret) {
@@ -875,7 +872,6 @@ std::vector<framework::shape_t> InferShapeForReverse(const std::vector<framework
   std::vector<framework::shape_t> res{inputs_shape[0]};
   if (attrs.find("axis") != attrs.end()) {
     auto axis = absl::get<std::vector<int>>(attrs.at("axis"));
-    CHECK(!axis.empty()) << "axis is empty! Please check setting.\n";
     for (auto &e : axis) {
       if (e >= static_cast<int>(inputs_shape[0].size()) || e < -1 * static_cast<int>(inputs_shape[0].size())) {
         LOG(FATAL) << "axis is not in [-n_dim, n_dim), Please check.";
@@ -884,8 +880,6 @@ std::vector<framework::shape_t> InferShapeForReverse(const std::vector<framework
         e += inputs_shape[0].size();
       }
     }
-  } else {
-    LOG(FATAL) << "axis is not be set! Please check.";
   }
   return res;
 }
@@ -896,14 +890,11 @@ std::vector<std::vector<std::string>> InferLayoutForReverse(const std::vector<fr
                                                             const Target &target) {
   if (attrs.attr_store.find("axis") != attrs.attr_store.end()) {
     auto axis = absl::get<std::vector<int>>(attrs.attr_store.at("axis"));
-    CHECK(!axis.empty()) << "axis is empty! Please check setting.\n";
     for (auto &e : axis) {
       if (e >= static_cast<int>(input_shapes[0].size()) || e < -1 * static_cast<int>(input_shapes[0].size())) {
         LOG(FATAL) << "axis is not in [-n_dim, n_dim), Please check.";
       }
     }
-  } else {
-    LOG(FATAL) << "axis is not be set! Please check.";
   }
   CHECK_EQ(input_layouts.size(), 1U) << "The input's layout size is not 1! Please check again.";
   return {input_layouts, input_layouts};

cinn/hlir/op/use_ops.h

@@ -28,7 +28,6 @@ CINN_USE_REGISTER(argmin_ops)
 CINN_USE_REGISTER(argmax_ops)
 CINN_USE_REGISTER(reduce_ops)
 CINN_USE_REGISTER(custom_call_op)
-CINN_USE_REGISTER(flip_ops)
 CINN_USE_REGISTER(repeat_ops)
 CINN_USE_REGISTER(one_hot_ops)
 CINN_USE_REGISTER(lookup_table_ops)