1 files changed, 99 insertions, 0 deletions
diff --git a/compiler/mir-onnx-importer/Op/AveragePool.cpp b/compiler/mir-onnx-importer/Op/AveragePool.cpp
new file mode 100644
index 000000000..503feffc8
--- /dev/null
+++ b/compiler/mir-onnx-importer/Op/AveragePool.cpp
@@ -0,0 +1,99 @@
+/*
+ * Copyright (c) 2019 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.
+ */
+
+#include "AveragePool.h"
+
+#include "ONNXHelpers.h"
+#include "AttributeHelpers.h"
+#include "ConvPoolHelpers.h"
+
+#include "mir/ops/AvgPool2DOp.h"
+
+namespace mir_onnx
+{
+
+void convertAveragePoolV1(const onnx::NodeProto &onnx_node, ConverterContext *context)
+{
+  std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node);
+  mir::Graph *graph = context->getGraph();
+
+  assert(inputs.size() == 1);
+  auto input = inputs[0];
+
+  const auto &input_shape = input->getShape();
+  if (input_shape.rank() != 4)
+    throw std::runtime_error("AveragePool: only 2-D input is supported.");
+
+  constexpr int num_spatial_dims = 2;
+
+  const auto strides =
+      getAttributeValue(onnx_node, "strides", std::vector<std::int32_t>(num_spatial_dims, 1));
+  if (strides.size() != num_spatial_dims)
+    throw std::runtime_error("AveragePool: attribute 'strides' has incorrect size.");
+
+  const auto kernel_shape = getAttributeValue<std::vector<std::int32_t>>(onnx_node, "kernel_shape");
+  if (kernel_shape.size() != num_spatial_dims)
+    throw std::runtime_error("AveragePool: attribute 'kernel_shape' has incorrect size.");
+
+  std::vector<std::int32_t> padding_before(num_spatial_dims, 0);
+  std::vector<std::int32_t> padding_after(num_spatial_dims, 0);
+  if (const auto *pads_attr = findAttribute(onnx_node, "pads"))
+  {
+    const auto pads = getAttributeValue<std::vector<std::int32_t>>(*pads_attr);
+    if (pads.size() != num_spatial_dims * 2)
+      throw std::runtime_error("AveragePool: attribute 'pads' has incorrect size.");
+    padding_before.assign(pads.cbegin(), std::next(pads.cbegin(), num_spatial_dims));
+    padding_after.assign(std::next(pads.cbegin(), num_spatial_dims), pads.cend());
+  }
+  else
+  {
+    const auto auto_pad = getAttributeValue<std::string>(onnx_node, "auto_pad", "NOTSET");
+    const std::vector<std::int32_t> dilations(num_spatial_dims, 1);
+    inferAutoPadding(auto_pad, input_shape, dilations, strides, kernel_shape, padding_before,
+                     padding_after);
+  }
+
+  mir::AvgPool2DOpAttributes attributes;
+  attributes.window = kernel_shape;
+  attributes.strides = strides;
+  attributes.padding_before = padding_before;
+  attributes.padding_after = padding_after;
+  attributes.include_pad = false;
+  attributes.data_format = mir::DataFormat::NCHW;
+  auto result = createOp<mir::ops::AvgPool2DOp>(graph, input, attributes)->getOutput(0);
+
+  context->setNodeOutputs(onnx_node, {result});
+}
+
+void convertAveragePoolV7(const onnx::NodeProto &onnx_node, ConverterContext *context)
+{
+  const auto count_include_pad = getAttributeValue<int64_t>(onnx_node, "count_include_pad", 0);
+  if (count_include_pad != 0)
+    throw std::runtime_error("Not supported count_include_pad attribute!");
+
+  convertAveragePoolV1(onnx_node, context);
+}
+
+void convertAveragePoolV10(const onnx::NodeProto &onnx_node, ConverterContext *context)
+{
+  const auto ceil_mode = getAttributeValue<int64_t>(onnx_node, "ceil_mode", 0);
+  if (ceil_mode != 0)
+    throw std::runtime_error("Not supported ceil_mode attribute!");
+
+  convertAveragePoolV7(onnx_node, context);
+}
+
+} // namespace mir_onnx