!4341 add leaky_relu ops for Opencl

Merge pull request !4341 from liuzhongkai/leaky_relu

mindspore/lite/src/runtime/kernel/arm/nnacl/leaky_relu_parameter.h

+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+
+#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_LEAKYRELU_H_
+#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_LEAKYRELU_H_
+
+#include "nnacl/op_base.h"
+
+typedef struct LeakyReluParameter {
+  OpParameter op_parameter_;
+  float alpha;
+} LeakyReluParameter;
+
+#endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_NNACL_LEAKYRELU_H_

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

@@ -16,7 +16,6 @@ __kernel void LeakyRelu(__read_only image2d_t input, __write_only image2d_t outp
 
   int Y = get_global_id(0);  // height id
   int X = get_global_id(1);  // weight id
-
   for (int num = 0; num < UP_DIV(C, SLICES); ++num) {
     FLT4 in_c4 = READ_FLT4(input, smp_zero, (int2)(X * UP_DIV(C, SLICES) + num, Y));  // NHWC4: H WC
     FLT4 tmp;

mindspore/lite/src/runtime/kernel/opencl/kernel/conv2d_transpose.cc

@@ -175,6 +175,10 @@ kernel::LiteKernel *OpenCLConv2dTransposeKernelCreator(const std::vector<lite::t
                                                        const kernel::KernelKey &desc,
                                                        const lite::Primitive *primitive) {
   auto *kernel = new Conv2dTransposeOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr.";
+    return nullptr;
+  }
   auto ret = kernel->Init();
   if (0 != ret) {
     // MS_LOG(ERROR) << "Init kernel failed, name: " << opDef.name()->str()

mindspore/lite/src/runtime/kernel/opencl/kernel/depthwise_conv2d.cc

@@ -194,6 +194,10 @@ kernel::LiteKernel *OpenCLDepthwiseConv2dKernelCreator(const std::vector<lite::t
                                                        const kernel::KernelKey &desc,
                                                        const lite::Primitive *primitive) {
   auto *kernel = new DepthwiseConv2dOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr.";
+    return nullptr;
+  }
   auto ret = kernel->Init();
   if (0 != ret) {
     MS_LOG(ERROR) << "Init DepthwiseConv2dOpenCLKernel failed!";

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

@@ -18,97 +18,105 @@
 
 #include <string>
 #include <set>
+#include <vector>
 
 #include "src/kernel_registry.h"
 #include "include/errorcode.h"
 #include "src/runtime/kernel/opencl/kernel/leaky_relu.h"
 #include "src/runtime/opencl/opencl_runtime.h"
 #include "src/runtime/kernel/opencl/cl/fp32/leaky_relu.cl.inc"
+#include "src/runtime/kernel/arm/nnacl/leaky_relu_parameter.h"
 
 using mindspore::kernel::KERNEL_ARCH::kGPU;
 using mindspore::lite::KernelRegistrar;
+using mindspore::lite::RET_ERROR;
 using mindspore::lite::RET_OK;
 using mindspore::schema::PrimitiveType_LeakyReLU;
 
 namespace mindspore::kernel {
 
-  int LeakyReluOpenCLKernel::Init() {
-    if (inputs_[0]->shape().size() != 4) {
-      MS_LOG(ERROR) << "leaky_relu only support dim=4, but your dim=" << inputs_[0]->shape().size();
-    }
-    std::set<std::string> build_options;
-    std::string source = leaky_relu_source_fp32;
-    std::string program_name = "LeakyRelu";
-    std::string kernel_name = "LeakyRelu";
-    auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
-    ocl_runtime->LoadSource(program_name, source);
-    ocl_runtime->BuildKernel(kernel_, program_name, kernel_name, build_options);
-
-    MS_LOG(DEBUG) << kernel_name << " Init Done!";
-    return RET_OK;
+int LeakyReluOpenCLKernel::Init() {
+  if (in_tensors_[0]->shape().size() != 4) {
+    MS_LOG(ERROR) << "leaky_relu only support dim=4, but your dim=" << in_tensors_[0]->shape().size();
+    return RET_ERROR;
   }
-
-
-    int LeakyReluOpenCLKernel::GetImageSize(size_t idx, std::vector<size_t> *img_size) {
-      int H = inputs_[0]->shape()[1];
-      int W = inputs_[0]->shape()[2];
-      int C = inputs_[0]->shape()[3];
+  std::set<std::string> build_options;
+  std::string source = leaky_relu_source_fp32;
+  std::string program_name = "LeakyRelu";
+  std::string kernel_name = "LeakyRelu";
+  auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
+  ocl_runtime->LoadSource(program_name, source);
+  ocl_runtime->BuildKernel(kernel_, program_name, kernel_name, build_options);
+
+  MS_LOG(DEBUG) << kernel_name << " Init Done!";
+  return RET_OK;
+}
+
+int LeakyReluOpenCLKernel::Run() {
+  auto param = reinterpret_cast<LeakyReluParameter *>(op_parameter_);
+  MS_LOG(DEBUG) << " Running!";
+  int N = in_tensors_[0]->shape()[0];
+  int H = in_tensors_[0]->shape()[1];
+  int W = in_tensors_[0]->shape()[2];
+  int C = in_tensors_[0]->shape()[3];
+  cl_int4 input_shape = {N, H, W, C};
+
+  auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
+  int arg_idx = 0;
+  ocl_runtime->SetKernelArg(kernel_, arg_idx++, in_tensors_[0]->Data());
+  ocl_runtime->SetKernelArg(kernel_, arg_idx++, out_tensors_[0]->Data());
+  ocl_runtime->SetKernelArg(kernel_, arg_idx++, input_shape);
+  ocl_runtime->SetKernelArg(kernel_, arg_idx++, param->alpha);
+
+  std::vector<size_t> local = {1, 1};
+  std::vector<size_t> global = {static_cast<size_t>(H), static_cast<size_t>(W)};
+  ocl_runtime->RunKernel(kernel_, global, local, nullptr);
+  return RET_OK;
+}
+
+int LeakyReluOpenCLKernel::GetImageSize(size_t idx, std::vector<size_t> *img_size) {
+  int H = in_tensors_[0]->shape()[1];
+  int W = in_tensors_[0]->shape()[2];
+  int C = in_tensors_[0]->shape()[3];
 
 #ifdef ENABLE_FP16
-      size_t img_dtype = CL_HALF_FLOAT;
+  size_t img_dtype = CL_HALF_FLOAT;
 #else
-      size_t img_dtype = CL_FLOAT;
+  size_t img_dtype = CL_FLOAT;
 #endif
 
-      img_size->clear();
-      img_size->push_back(W * UP_DIV(C, C4NUM));
-      img_size->push_back(H);
-      img_size->push_back(img_dtype);
-      return RET_OK;
-    }
-
-  int LeakyReluOpenCLKernel::Run() {
-    auto param = reinterpret_cast<LeakyReluParameter *>(this->opParameter);
-    MS_LOG(DEBUG) << this->Name() << " Running!";
-    int N = inputs_[0]->shape()[0];
-    int H = inputs_[0]->shape()[1];
-    int W = inputs_[0]->shape()[2];
-    int C = inputs_[0]->shape()[3];
-    cl_int4 input_shape = {N, H, W, C};
-
-    auto ocl_runtime = lite::opencl::OpenCLRuntime::GetInstance();
-    int arg_idx = 0;
-    ocl_runtime->SetKernelArg(kernel_, arg_idx++, inputs_[0]->Data());
-    ocl_runtime->SetKernelArg(kernel_, arg_idx++, outputs_[0]->Data());
-    ocl_runtime->SetKernelArg(kernel_, arg_idx++, input_shape);
-    ocl_runtime->SetKernelArg(kernel_, arg_idx++, param->alpha);
-
-    std::vector<size_t> local = {1, 1};
-    std::vector<size_t> global = {static_cast<size_t>(H), static_cast<size_t>(W)};
-    ocl_runtime->RunKernel(kernel_, global, local, nullptr);
-    return 0;
+  img_size->clear();
+  img_size->push_back(W * UP_DIV(C, C4NUM));
+  img_size->push_back(H);
+  img_size->push_back(img_dtype);
+  return RET_OK;
+}
+
+kernel::LiteKernel *OpenCLLeakyReluKernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
+                                                 const std::vector<lite::tensor::Tensor *> &outputs,
+                                                 OpParameter *opParameter, const lite::Context *ctx,
+                                                 const kernel::KernelKey &desc, const lite::Primitive *primitive) {
+  if (inputs.size() == 0) {
+    MS_LOG(ERROR) << "Input data size must be greater than 0, but your size is " << inputs.size();
+    return nullptr;
   }
-
-  kernel::LiteKernel *OpenCLLeakyReluKernelCreator(const std::vector<lite::tensor::Tensor *> &inputs,
-                                                   const std::vector<lite::tensor::Tensor *> &outputs,
-                                                   OpParameter *opParameter, const lite::Context *ctx,
-                                                   const kernel::KernelKey &desc, const lite::Primitive *primitive) {
-    auto *kernel = new LeakyReluOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
-    if (inputs.size() == 0) {
-      MS_LOG(ERROR) << "Input data size must must be greater than 0, but your size is " << inputs.size();
-    }
-    if (inputs[0]->shape()[0] > 1) {
-      MS_LOG(ERROR) << "Init `leaky relu` kernel failed: Unsupported multi-batch.";
-    }
-    auto ret = kernel->Init();
-    if (0 != ret) {
-      MS_LOG(ERROR) << "Init `Leaky Relu` kernel failed!";
-      delete kernel;
-      return nullptr;
-    }
-    return kernel;
+  if (inputs[0]->shape()[0] > 1) {
+    MS_LOG(ERROR) << "Init `leaky relu` kernel failed: Unsupported multi-batch.";
+    return nullptr;
+  }
+  auto *kernel = new LeakyReluOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr.";
+    return nullptr;
   }
+  auto ret = kernel->Init();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init `Leaky Relu` kernel failed!";
+    delete kernel;
+    return nullptr;
+  }
+  return kernel;
+}
 
-  REG_KERNEL(kGPU, kNumberTypeFloat32, PrimitiveType_LeakyReLU, OpenCLLeakyReluKernelCreator)
+REG_KERNEL(kGPU, kNumberTypeFloat32, PrimitiveType_LeakyReLU, OpenCLLeakyReluKernelCreator)
 }  // namespace mindspore::kernel
-

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

@@ -14,18 +14,15 @@
  * limitations under the License.
  */
 
-#ifndef MINDSPORE_LITE_SRC_BACKEND_OPENCL_LEAKYRELU_H_
-#define MINDSPORE_LITE_SRC_BACKEND_OPENCL_LEAKYRELU_H_
+#ifndef MINDSPORE_LITE_SRC_RUNTIME_KERNEL_OPENCL_KERNEL_LEAKYRELU_H
+#define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_OPENCL_KERNEL_LEAKYRELU_H_
 
 #include <vector>
-
-#include "src/runtime/opencl/opencl_runtime.h"
+#include <string>
+#include "src/ir/tensor.h"
 #include "src/runtime/kernel/opencl/opencl_kernel.h"
-
-struct LeakyReluParameter {
-  OpParameter op_parameter_;
-  cl_float alpha;
-};
+#include "schema/model_generated.h"
+#include "src/runtime/opencl/opencl_runtime.h"
 
 namespace mindspore::kernel {
 
@@ -46,4 +43,4 @@ class LeakyReluOpenCLKernel : public OpenCLKernel {
 
 }  // namespace mindspore::kernel
 
-#endif  // MINDSPORE_LITE_SRC_BACKEND_OPENCL_LEAKYRELU_H_
+#endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_OPENCL_KERNEL_LEAKYRELU_H_

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

@@ -161,6 +161,10 @@ kernel::LiteKernel *OpenCLMatMulKernelCreator(const std::vector<lite::tensor::Te
     hasBias = (reinterpret_cast<MatMulParameter *>(opParameter))->has_bias_;
   }
   auto *kernel = new MatMulOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs, hasBias);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr.";
+    return nullptr;
+  }
   auto ret = kernel->Init();
   if (0 != ret) {
     // MS_LOG(ERROR) << "Init kernel failed, name: " << opDef.name()->str()

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

@@ -87,6 +87,10 @@ kernel::LiteKernel *OpenCLSoftMaxKernelCreator(const std::vector<lite::tensor::T
                                                OpParameter *opParameter, const lite::Context *ctx,
                                                const kernel::KernelKey &desc, const lite::Primitive *primitive) {
   auto *kernel = new SoftmaxOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr.";
+    return nullptr;
+  }
   if (inputs[0]->shape()[0] > 1) {
     MS_LOG(ERROR) << "Init `Softmax` kernel failed: Unsupported multi-batch.";
   }

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

@@ -110,6 +110,10 @@ kernel::LiteKernel *OpenCLTransposeKernelCreator(const std::vector<lite::tensor:
                                                  OpParameter *opParameter, const lite::Context *ctx,
                                                  const kernel::KernelKey &desc, const lite::Primitive *primitive) {
   auto *kernel = new TransposeOpenCLKernel(reinterpret_cast<OpParameter *>(opParameter), inputs, outputs);
+  if (kernel == nullptr) {
+    MS_LOG(ERROR) << "kernel " << opParameter->name_ << "is nullptr.";
+    return nullptr;
+  }
   auto ret = kernel->Init();
   if (0 != ret) {
     delete kernel;

mindspore/lite/test/CMakeLists.txt

@@ -142,7 +142,7 @@ if (SUPPORT_GPU)
             ${LITE_DIR}/src/runtime/kernel/opencl/kernel/matmul.cc
             ${LITE_DIR}/src/runtime/kernel/opencl/kernel/softmax.cc
             ${LITE_DIR}/src/runtime/kernel/opencl/kernel/concat.cc
-            # ${LITE_DIR}/src/runtime/kernel/opencl/kernel/leaky_relu.cc
+            ${LITE_DIR}/src/runtime/kernel/opencl/kernel/leaky_relu.cc
             ${LITE_DIR}/src/runtime/kernel/opencl/kernel/conv2d_transpose.cc
             ${LITE_DIR}/src/runtime/kernel/opencl/kernel/transpose.cc
             ${LITE_DIR}/src/runtime/kernel/opencl/kernel/reshape.cc
@@ -321,7 +321,7 @@ if (SUPPORT_GPU)
             ${TEST_DIR}/ut/src/runtime/kernel/opencl/conv2d_transpose_tests.cc
             ${TEST_DIR}/ut/src/runtime/kernel/opencl/transpose_tests.cc
             ${TEST_DIR}/ut/src/runtime/kernel/opencl/convolution_tests.cc
-            # ${TEST_DIR}/ut/src/runtime/kernel/opencl/leakyrelu_tests.cc
+            ${TEST_DIR}/ut/src/runtime/kernel/opencl/leakyrelu_tests.cc
             )
 endif()
 

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

@@ -21,12 +21,14 @@
 #include "mindspore/lite/src/runtime/opencl/opencl_runtime.h"
 #include "mindspore/lite/src/runtime/kernel/opencl/subgraph_opencl_kernel.h"
 #include "mindspore/lite/src/runtime/kernel/opencl/kernel/leaky_relu.h"
+#include "mindspore/lite/src/runtime/kernel/arm/nnacl/leaky_relu_parameter.h"
+
+using mindspore::kernel::LeakyReluOpenCLKernel;
+using mindspore::kernel::LiteKernel;
+using mindspore::kernel::SubGraphOpenCLKernel;
 
 namespace mindspore {
-class TestLeakyReluOpenCL : public mindspore::Common {
- public:
-  TestLeakyReluOpenCL() {}
-};
+class TestLeakyReluOpenCL : public mindspore::CommonTest {};
 
 void LoadDataLeakyRelu(void *dst, size_t dst_size, const std::string &file_path) {
   if (file_path.empty()) {
@@ -99,7 +101,6 @@ TEST_F(TestLeakyReluOpenCL, LeakyReluFp32_dim4) {
   LoadDataLeakyRelu(input_tensor->Data(), input_tensor->Size(), in_file);
   MS_LOG(INFO) << "==================input data================";
   printf_tensor(inputs[0]);
-
   sub_graph->Run();
 
   MS_LOG(INFO) << "==================output data================";