chore: import upstream snapshot with attribution

test/cpp/fluid/controlflow/CMakeLists.txt

@@ -0,0 +1,7 @@
+paddle_test(conditional_block_op_test SRCS conditional_block_op_test.cc)
+
+if(WITH_ONNXRUNTIME AND WIN32)
+  # Copy onnxruntime for some c++ test in Windows, since the test will
+  # be build only in CI, so suppose the generator in Windows is Ninja.
+  copy_onnx(conditional_block_op_test)
+endif()

test/cpp/fluid/controlflow/conditional_block_op_test.cc

@@ -0,0 +1,73 @@
+/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License. */
+
+#include "paddle/fluid/operators/controlflow/conditional_block_op.h"
+
+#include "gtest/gtest.h"
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/scope.h"
+
+using DenseTensorArray = phi::TensorArray;
+using Scope = paddle::framework::Scope;
+using Variable = paddle::framework::Variable;
+using Place = phi::Place;
+
+TEST(ConditionalBlockGrad, NoNeedRunDenseTensorArray) {
+  Place place = phi::CPUPlace();
+  Scope scope;
+
+  Variable* cond_var = scope.Var("condition");
+  phi::DenseTensor* cond_tensor = cond_var->GetMutable<phi::DenseTensor>();
+  phi::DDim cond_dims = common::make_ddim({1});
+  bool* cond_data = cond_tensor->mutable_data<bool>(cond_dims, place);
+  cond_data[0] = false;
+
+  Variable* input_var = scope.Var("input_lod_tensor_array");
+  DenseTensorArray* input_tensors = input_var->GetMutable<phi::TensorArray>();
+  for (int i = 0; i < 5; ++i) {
+    phi::DDim in_dims = common::make_ddim({i + 1, i + 2});
+    phi::DenseTensor lod_tensor;
+    float* in_data = lod_tensor.mutable_data<float>(in_dims, place);
+    for (int j = 0; j < (i + 1) * (i + 2); ++j) {
+      in_data[j] = static_cast<float>(j);
+    }
+    input_tensors->push_back(lod_tensor);
+  }
+
+  Variable* input_grad_var = scope.Var("input_lod_tensor_array@GRAD");
+  DenseTensorArray* grad_tensors =
+      input_grad_var->GetMutable<phi::TensorArray>();
+  grad_tensors->resize(5);
+
+  paddle::framework::AttributeMap attrs;
+  attrs.insert({"is_scalar_condition", true});
+
+  auto conditional_grad_op = paddle::framework::OpRegistry::CreateOp(
+      "conditional_block_grad",
+      {{"Input", {"input_lod_tensor_array"}}, {"Cond", {"condition"}}},
+      {{"Input@GRAD", {"input_lod_tensor_array@GRAD"}}},
+      attrs);
+
+  conditional_grad_op->Run(scope, place);
+
+  const DenseTensorArray& out_tensors = input_grad_var->Get<phi::TensorArray>();
+  for (int i = 0; i < 5; ++i) {
+    phi::DDim out_dims = out_tensors[i].dims();
+    EXPECT_EQ(common::make_ddim({i + 1, i + 2}), out_dims);
+    const float* out_data = out_tensors[i].data<float>();
+    for (int j = 0; j < (i + 1) * (i + 2); ++j) {
+      EXPECT_EQ(0, out_data[j]);
+    }
+  }
+}