transpose output set to buffer

mindspore/lite/src/runtime/kernel/opencl/cl/fp32/transpose.cl

@@ -3,7 +3,7 @@
 #define READ_IMAGE read_imagef
 #define WRITE_IMAGE write_imagef
 __constant sampler_t smp_zero = CLK_NORMALIZED_COORDS_FALSE | CLK_ADDRESS_CLAMP | CLK_FILTER_NEAREST;
-__kernel void transpose(__read_only image2d_t src_data, __write_only image2d_t dst_data, int2 HW, int2 C) {
+__kernel void transpose_IMG(__read_only image2d_t src_data, __write_only image2d_t dst_data, int2 HW, int2 C) {
   int X = get_global_id(0);
   int Y = get_global_id(1);
   if (X >= HW.y || Y >= C.y) {
@@ -43,3 +43,44 @@ __kernel void transpose(__read_only image2d_t src_data, __write_only image2d_t d
   WRITE_IMAGE(dst_data, (int2)(X, 4 * Y + 2), result[2]);
   WRITE_IMAGE(dst_data, (int2)(X, 4 * Y + 3), result[3]);
 }
+
+__kernel void transpose_BUF(__read_only image2d_t src_data, global FLT4 *dst_data, int2 HW, int2 C) {
+  int X = get_global_id(0);
+  int Y = get_global_id(1);
+  if (X >= HW.y || Y >= C.y) {
+    return;
+  }
+  FLT4 result[4];
+  result[0] = (FLT4)(0.0f);
+  result[1] = (FLT4)(0.0f);
+  result[2] = (FLT4)(0.0f);
+  result[3] = (FLT4)(0.0f);
+  FLT4 x0 = READ_IMAGE(src_data, smp_zero, (int2)(Y, 4 * X));
+  FLT4 x1 = READ_IMAGE(src_data, smp_zero, (int2)(Y, 4 * X + 1));
+  FLT4 x2 = READ_IMAGE(src_data, smp_zero, (int2)(Y, 4 * X + 2));
+  FLT4 x3 = READ_IMAGE(src_data, smp_zero, (int2)(Y, 4 * X + 3));
+  result[0].x = x0.x;
+  result[0].y = x1.x;
+  result[0].z = x2.x;
+  result[0].w = x3.x;
+
+  result[1].x = x0.y;
+  result[1].y = x1.y;
+  result[1].z = x2.y;
+  result[1].w = x3.y;
+
+  result[2].x = x0.z;
+  result[2].y = x1.z;
+  result[2].z = x2.z;
+  result[2].w = x3.z;
+
+  result[3].x = x0.w;
+  result[3].y = x1.w;
+  result[3].z = x2.w;
+  result[3].w = x3.w;
+
+  dst_data[4 * Y * HW.y + X] = result[0];
+  dst_data[(4 * Y + 1) * HW.y + X] = result[1];
+  dst_data[(4 * Y + 2) * HW.y + X] = result[2];
+  dst_data[(4 * Y + 3) * HW.y + X] = result[3];
+}

mindspore/lite/src/runtime/kernel/opencl/kernel/transpose.cc

@@ -36,7 +36,11 @@ namespace mindspore::kernel {
 int TransposeOpenCLKernel::Init() {
   std::string kernel_name = "transpose";
   auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
-
+  if (!is_image_out_) {
+    kernel_name += "_BUF";
+  } else {
+    kernel_name += "_IMG";
+  }
 #ifdef PROGRAM_WITH_IL
   ocl_runtime->CreateKernelFromIL(kernel_(), kernel_name);
 #else
@@ -60,8 +64,12 @@ int TransposeOpenCLKernel::Init() {
     MS_LOG(ERROR) << "input H * W % 4 != 0 not support!";
     return RET_ERROR;
   }
-  ori_format_ = out_tensors_[0]->GetFormat();
+  // Transpose::InferShape just set output->SetFormat(input->GetFormat()); -^-!
+  ori_format_ = schema::Format_NCHW;
   out_tensors_[0]->SetFormat(schema::Format_NCHW);
+  if (!is_image_out_) {
+    out_mem_type_ = OpenCLMemType::BUF;
+  }
   MS_LOG(DEBUG) << kernel_name << " Init Done!";
   return RET_OK;
 }

mindspore/lite/src/runtime/kernel/opencl/kernel/transpose.h

@@ -38,6 +38,7 @@ class TransposeOpenCLKernel : public OpenCLKernel {
 
  private:
   cl::Kernel kernel_;
+  bool is_image_out_ = false;
 };
 }  // namespace mindspore::kernel
 

mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.cc

@@ -34,13 +34,13 @@ int SubGraphOpenCLKernel::GenToFormatOp(const std::vector<lite::tensor::Tensor *
   out_parameters->clear();
   out_convert_ops->clear();
   for (size_t i = 0; i < in_tensors.size(); ++i) {
-    OpenCLKernel* cur_opencl_op = reinterpret_cast<OpenCLKernel*>(in_kernels[i]);
+    OpenCLKernel *cur_opencl_op = reinterpret_cast<OpenCLKernel *>(in_kernels[i]);
     schema::Format ori_format = cur_opencl_op->GetOriFormat();
-    if (mem_type == cur_opencl_op->GetMemType() && in_tensors[i]->GetFormat() == ori_format) {
+    if (mem_type == OpenCLMemType::BUF && mem_type == cur_opencl_op->GetMemType() &&
+        in_tensors[i]->GetFormat() == ori_format) {
       continue;
     }
-    auto dst_format =
-      (mem_type == OpenCLMemType::IMG) ? in_kernels[i]->out_tensors()[0]->GetFormat() : ori_format;
+    auto dst_format = (mem_type == OpenCLMemType::IMG) ? in_kernels[i]->out_tensors()[0]->GetFormat() : ori_format;
     auto src_format =
       (mem_type == OpenCLMemType::IMG) ? in_tensors[i]->GetFormat() : in_kernels[i]->out_tensors()[0]->GetFormat();
     lite::tensor::Tensor *new_tensor = new (std::nothrow) lite::tensor::Tensor();

mindspore/lite/test/ut/src/runtime/kernel/opencl/activation_tests.cc

@@ -125,6 +125,7 @@ int RunSubGraphOpenCLKernel(const std::vector<lite::tensor::Tensor *> &inputs,
     MS_LOG(ERROR) << "Run SubGraphOpenCLKernel error.";
     return RET_ERROR;
   }
+  delete sub_graph;
   return RET_OK;
 }
 
@@ -180,6 +181,7 @@ TEST_F(TestActivationOpenCL, LeakyReluFp32_dim4) {
 
   delete input_tensor;
   delete output_tensor;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
   return;
 }
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/avg_pooling_tests.cc

@@ -119,6 +119,11 @@ TEST_F(TestAvgPoolingOpenCL, AvgPoolFp32) {
     }
   printf("test all close OK!\n");
   lite::CompareOutputData(output_data, expect, 4);
+  delete tensor_in;
+  delete tensor_out;
+  delete pooling_kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/concat_tests.cc

@@ -175,6 +175,14 @@ TEST_F(TestConcatOpenCL, ConcatFp32_2input_dim4_axis3) {
   sub_graph->Run();
   auto *output_data_gpu = reinterpret_cast<float *>(output_tensor->Data());
   CompareOutputData1(output_data_gpu, output_data_cpu.data(), output_tensor->ElementsNum(), 0.00001);
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete concat_kernel;
+  delete sub_graph;
   lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/conv2d_transpose_tests.cc

@@ -108,5 +108,14 @@ TEST_F(TestConv2dTransposeOpenCL, Conv2dTransposeFp32) {
   CompareOutputData(output_data, correct_data, oh * ow * co, 0.00001);
 
   MS_LOG(INFO) << "Test Conv2dTransposeFp32 passed";
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete arith_kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/convolution_tests.cc

@@ -120,6 +120,14 @@ void TEST_MAIN(ConvParameter *param, schema::Format data_format, const std::stri
   MyCompareOutput(output_tensor, expect_file);
   //  lite::CompareOutput(reinterpret_cast<float *>(output_tensor->Data()), expect_file);
 
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete conv_kernel;
+  delete sub_graph;
   mindspore::lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 

mindspore/lite/test/ut/src/runtime/kernel/opencl/matmul_tests.cc

@@ -75,12 +75,15 @@ TEST_F(TestMatMulOpenCL, MatMulFp32) {
   // compare
   CompareOutputData(output_data, correct_data, co, 0.00001);
 
-  delete input_data;
-  delete weight_data;
-  delete tensor_x;
-  delete tensor_w;
-  delete tensor_out;
-  delete correct_data;
   MS_LOG(INFO) << "TestMatMulFp32 passed";
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete arith_kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/max_pooling_tests.cc

@@ -92,6 +92,15 @@ TEST_F(TestMaxPoolingOpenCL, MaxPool_1_32_512_96) {
   MS_LOG(INFO) << "compare result";
   std::cout << "compare result" << std::endl;
   CompareOutput(output_tensor, expect_file);
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete pooling_kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/softmax_tests.cc

@@ -77,6 +77,15 @@ void RunTestCase(std::vector<int> input_shape, std::vector<int> output_shape, st
   MS_LOG(INFO) << "compare result";
   std::cout << "compare result" << std::endl;
   CompareOutput(output_tensor, expect_file);
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 
 TEST_F(TestSoftmaxOpenCL, Softmax_1) {

mindspore/lite/test/ut/src/runtime/kernel/opencl/to_format_tests.cc

@@ -75,5 +75,14 @@ TEST_F(TestToFormatOpenCL, TransposeFp32) {
   // compare
   CompareOutputData(output_data, correct_data, h * w * c, 0.00001);
   MS_LOG(INFO) << "TestMatMulFp32 passed";
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete arith_kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 }  // namespace mindspore

mindspore/lite/test/ut/src/runtime/kernel/opencl/transpose_tests.cc

@@ -75,5 +75,14 @@ TEST_F(TestTransposeOpenCL, TransposeFp32) {
   // compare
   CompareOutputData(output_data, correct_data, h * w * c, 0.00001);
   MS_LOG(INFO) << "TestMatMulFp32 passed";
+  for (auto tensor : inputs) {
+    delete tensor;
+  }
+  for (auto tensor : outputs) {
+    delete tensor;
+  }
+  delete arith_kernel;
+  delete pGraph;
+  lite::opencl::OpenCLRuntime::DeleteInstance();
 }
 }  // namespace mindspore