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-rw-r--r--compiler/mir/src/ops/DeConv2DOp.cpp96
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diff --git a/compiler/mir/src/ops/DeConv2DOp.cpp b/compiler/mir/src/ops/DeConv2DOp.cpp
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+/*
+ * 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/Deconv2DOp.h"
+
+namespace mir
+{
+namespace ops
+{
+
+// See the formulas at https://github.com/onnx/onnx/blob/master/docs/Operators.md#convtranspose.
+void DeConv2DOp::inferPaddings()
+{
+ assert(_attributes.padding_type != PaddingType::Explicit);
+
+ const auto &input_shape = getInputShape(0);
+ const auto &kernel_shape = getInputShape(1);
+ const auto &output_shape = getOutputShape(0);
+
+ constexpr int num_spatial_dims = 2;
+
+ for (int i = 0; i < num_spatial_dims; ++i)
+ {
+ const int spatial_dim_index = getDataSpatialDimIndex(_attributes.data_format, i);
+ const std::int32_t total_padding =
+ (input_shape.dim(spatial_dim_index) - 1) * _attributes.strides[i] + kernel_shape.dim(i) -
+ output_shape.dim(spatial_dim_index);
+
+ switch (_attributes.padding_type)
+ {
+ case PaddingType::Valid:
+ // TODO Figure out what to do.
+ assert(false);
+ break;
+ case PaddingType::SameLower:
+ _attributes.padding_after[i] = total_padding / 2;
+ _attributes.padding_before[i] = total_padding - _attributes.padding_after[i];
+ break;
+ case PaddingType::SameUpper:
+ _attributes.padding_before[i] = total_padding / 2;
+ _attributes.padding_after[i] = total_padding - _attributes.padding_before[i];
+ break;
+ default:
+ assert(false);
+ }
+ }
+}
+
+// See the formulas at https://github.com/onnx/onnx/blob/master/docs/Operators.md#convtranspose.
+void DeConv2DOp::inferOutputTypes()
+{
+ assert(_attributes.padding_type == PaddingType::Explicit);
+
+ // Kernel shape: [Hk, Wk, Co, Ci]
+ 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(kernel_shape.dim(3) == input_shape.dim(channel_dim_index));
+
+ Shape output_shape(4);
+
+ output_shape.dim(batch_dim_index) = input_shape.dim(batch_dim_index);
+ output_shape.dim(channel_dim_index) = kernel_shape.dim(2);
+
+ constexpr int num_spatial_dims = 2;
+
+ for (int i = 0; i < num_spatial_dims; i++)
+ {
+ const int spatial_dim_index = getDataSpatialDimIndex(_attributes.data_format, i);
+ output_shape.dim(spatial_dim_index) =
+ (input_shape.dim(spatial_dim_index) - 1) * _attributes.strides[i] + kernel_shape.dim(i) -
+ (_attributes.padding_before.at(i) + _attributes.padding_after.at(i));
+ }
+
+ setOutputType(0, {getInput(0)->getElementType(), output_shape});
+}
+
+} // namespace ops
+} // namespace mir