1 files changed, 80 insertions, 0 deletions
diff --git a/runtimes/nn/common/NNFWKernels.lst b/runtimes/nn/common/NNFWKernels.lst
new file mode 100644
index 000000000..2a60e0120
--- /dev/null
+++ b/runtimes/nn/common/NNFWKernels.lst
@@ -0,0 +1,80 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. 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.
+ */
+
+NNFW_KERNEL(convFloat32, bool, 
+            (const float* inputData, const Shape& inputShape,
+                 const float* filterData, const Shape& filterShape,
+                 const float* biasData, const Shape& biasShape,
+                 int32_t padding_left, int32_t padding_right,
+                 int32_t padding_top, int32_t padding_bottom,
+                 int32_t stride_width, int32_t stride_height,
+                 int32_t activation,
+                 float* outputData, const Shape& outputShape)
+           );
+
+NNFW_KERNEL(depthwiseConvFloat32, bool,
+             (const float* inputData, const Shape& inputShape,
+              const float* filterData, const Shape& filterShape,
+              const float* biasData, const Shape& biasShape,
+              int32_t padding_left, int32_t padding_right,
+              int32_t padding_top, int32_t padding_bottom,
+              int32_t stride_width, int32_t stride_height,
+              int32_t depth_multiplier, int32_t activation,
+              float* outputData, const Shape& outputShape)
+            );
+
+NNFW_KERNEL(averagePoolFloat32, bool,
+            (const float* inputData, const Shape& inputShape,
+             int32_t padding_left, int32_t padding_right,
+             int32_t padding_top, int32_t padding_bottom,
+             int32_t stride_width, int32_t stride_height,
+             int32_t filter_width, int32_t filter_height, int32_t activation,
+             float* outputData, const Shape& outputShape)
+           );
+
+NNFW_KERNEL(maxPoolFloat32, bool,
+            (const float* inputData, const Shape& inputShape,
+             int32_t padding_left, int32_t padding_right,
+             int32_t padding_top, int32_t padding_bottom,
+             int32_t stride_width, int32_t stride_height,
+             int32_t filter_width, int32_t filter_height, int32_t activation,
+             float* outputData, const Shape& outputShape)
+           );
+
+NNFW_KERNEL(softmaxFloat32, bool,
+            (const float* inputData, const Shape& inputShape,
+             const float beta,
+             float* outputData, const Shape& outputShape)
+           );
+
+NNFW_KERNEL(fullyConnectedFloat32, bool,
+            (const float* inputData, const Shape& inputShape,
+             const float* weights, const Shape& weightsShape,
+             const float* biasData, const Shape& biasShape,
+             int32_t activation,
+             float* outputData, const Shape& outputShape)
+           );
+
+NNFW_KERNEL(concatenationFloat32, bool,
+            (const std::vector<const float*>& inputDataPtrs,
+             const std::vector<Shape>& inputShapes, int32_t axis,
+             float* outputData, const Shape& outputShape)
+           );
+
+NNFW_KERNEL(reshapeGeneric, bool,
+            (const void* inputData, const Shape& inputShape,
+                    void* outputData, const Shape& outputShape)
+           );