1 files changed, 60 insertions, 0 deletions
diff --git a/compiler/mir/src/ops/DepthwiseConv2DOp.cpp b/compiler/mir/src/ops/DepthwiseConv2DOp.cpp
new file mode 100644
index 000000000..0154bcd09
--- /dev/null
+++ b/compiler/mir/src/ops/DepthwiseConv2DOp.cpp
@@ -0,0 +1,60 @@
+/*
+ * 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.
+ */
+
+#include "mir/ops/DepthwiseConv2DOp.h"
+
+namespace mir
+{
+namespace ops
+{
+
+void DepthwiseConv2DOp::inferOutputTypes()
+{
+  // Kernel shape: [Hk, Wk, Ci, M].
+  const auto &input_shape = getInputShape(0);
+  const auto &kernel_shape = getInputShape(1);
+  const int batch_dim_index = getDataBatchDimIndex(_attributes.data_format);
+  const int channel_dim_index = getDataChannelDimIndex(_attributes.data_format);
+
+  assert(input_shape.rank() == 4);
+  assert(kernel_shape.rank() == 4);
+  assert(input_shape.dim(channel_dim_index) == kernel_shape.dim(2));
+  assert(_attributes.strides.size() == 2);
+  assert(_attributes.padding_before.size() == 2);
+  assert(_attributes.padding_after.size() == 2);
+
+  Shape output_shape(4);
+
+  output_shape.dim(batch_dim_index) = input_shape.dim(batch_dim_index);
+  output_shape.dim(channel_dim_index) = input_shape.dim(channel_dim_index) * kernel_shape.dim(3);
+
+  for (int i = 0; i < 2; i++)
+  {
+    const int spatial_dim_index = getDataSpatialDimIndex(_attributes.data_format, i);
+    const std::int32_t padded_input = input_shape.dim(spatial_dim_index) +
+                                      _attributes.padding_before[i] + _attributes.padding_after[i];
+    // out_size = ceil((in_size - kernel_size + 1) / stride) =
+    //   (in_size - kernel_size + 1 + stride - 1) / stride =
+    //   (in_size - kernel_size) / stride + 1
+    output_shape.dim(spatial_dim_index) =
+        (padded_input - kernel_shape.dim(i)) / _attributes.strides[i] + 1;
+  }
+
+  setOutputType(0, {getInput(0)->getElementType(), output_shape});
+}
+
+} // namespace ops
+} // namespace mir