提交 ce7f361a 编写于 作者: N nhzlx

fix comments

上级 df9cbabc
...@@ -20,7 +20,7 @@ namespace paddle { ...@@ -20,7 +20,7 @@ namespace paddle {
namespace inference { namespace inference {
namespace tensorrt { namespace tensorrt {
TEST(Pool2dOpConverter, main) { void test_pool2d(bool global_pooling) {
framework::Scope scope; framework::Scope scope;
std::unordered_set<std::string> parameters; std::unordered_set<std::string> parameters;
TRTConvertValidation validator(5, parameters, scope, 1 << 15); TRTConvertValidation validator(5, parameters, scope, 1 << 15);
...@@ -28,6 +28,9 @@ TEST(Pool2dOpConverter, main) { ...@@ -28,6 +28,9 @@ TEST(Pool2dOpConverter, main) {
// The ITensor's Dims should not contain the batch size. // The ITensor's Dims should not contain the batch size.
// So, the ITensor's Dims of input and output should be C * H * W. // So, the ITensor's Dims of input and output should be C * H * W.
validator.DeclInputVar("pool2d-X", nvinfer1::Dims3(3, 4, 4)); validator.DeclInputVar("pool2d-X", nvinfer1::Dims3(3, 4, 4));
if (global_pooling)
validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 1, 1));
else
validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 2, 2)); validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 2, 2));
// Prepare Op description // Prepare Op description
...@@ -40,7 +43,6 @@ TEST(Pool2dOpConverter, main) { ...@@ -40,7 +43,6 @@ TEST(Pool2dOpConverter, main) {
std::vector<int> strides({2, 2}); std::vector<int> strides({2, 2});
std::vector<int> paddings({0, 0}); std::vector<int> paddings({0, 0});
std::string pooling_t = "max"; std::string pooling_t = "max";
bool global_pooling = false;
desc.SetAttr("pooling_type", pooling_t); desc.SetAttr("pooling_type", pooling_t);
desc.SetAttr("ksize", ksize); desc.SetAttr("ksize", ksize);
...@@ -55,40 +57,9 @@ TEST(Pool2dOpConverter, main) { ...@@ -55,40 +57,9 @@ TEST(Pool2dOpConverter, main) {
validator.Execute(3); validator.Execute(3);
} }
TEST(Pool2dOpConverter, test_global_pooling) { TEST(Pool2dOpConverter, normal) { test_pool2d(false); }
framework::Scope scope;
std::unordered_set<std::string> parameters;
TRTConvertValidation validator(5, parameters, scope, 1 << 15);
// The ITensor's Dims should not contain the batch size.
// So, the ITensor's Dims of input and output should be C * H * W.
validator.DeclInputVar("pool2d-X", nvinfer1::Dims3(3, 4, 4));
validator.DeclOutputVar("pool2d-Out", nvinfer1::Dims3(3, 1, 1));
// Prepare Op description
framework::OpDesc desc;
desc.SetType("pool2d");
desc.SetInput("X", {"pool2d-X"});
desc.SetOutput("Out", {"pool2d-Out"});
std::vector<int> ksize({2, 2});
std::vector<int> strides({2, 2});
std::vector<int> paddings({0, 0});
std::string pooling_t = "max";
bool global_pooling = true;
desc.SetAttr("pooling_type", pooling_t);
desc.SetAttr("ksize", ksize);
desc.SetAttr("strides", strides);
desc.SetAttr("paddings", paddings);
desc.SetAttr("global_pooling", global_pooling);
LOG(INFO) << "set OP";
validator.SetOp(*desc.Proto());
LOG(INFO) << "execute";
validator.Execute(3); TEST(Pool2dOpConverter, test_global_pooling) { test_pool2d(true); }
}
} // namespace tensorrt } // namespace tensorrt
} // namespace inference } // namespace inference
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册