1 files changed, 97 insertions, 0 deletions
diff --git a/compiler/mir-onnx-importer/Op/Reshape.cpp b/compiler/mir-onnx-importer/Op/Reshape.cpp
new file mode 100644
index 000000000..5cd4985e2
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+++ b/compiler/mir-onnx-importer/Op/Reshape.cpp
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+/*
+ * 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 "Reshape.h"
+
+#include "ONNXHelpers.h"
+#include "AttributeHelpers.h"
+
+#include "mir/Tensor.h"
+#include "mir/ShapeRange.h"
+
+#include "mir/ops/ConstantOp.h"
+#include "mir/ops/ReshapeOp.h"
+
+namespace mir_onnx
+{
+
+void convertReshapeV1(const onnx::NodeProto &onnx_node, ConverterContext *context)
+{
+  std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node);
+  mir::Graph *graph = context->getGraph();
+  // consumed_inputs attribute not used
+  const auto *shape_attr = findAttribute(onnx_node, "shape");
+  if (shape_attr && shape_attr->ints_size() > 0)
+  {
+    mir::Shape in_shape = inputs[0]->getShape();
+    mir::Shape out_shape(shape_attr->ints_size());
+    for (int32_t index = 0; index < out_shape.rank(); index++)
+    {
+      const auto dim_value = shape_attr->ints(index);
+      if (dim_value == 0)
+        out_shape.dim(index) = in_shape.dim(index);
+      else
+        out_shape.dim(index) = dim_value;
+    }
+
+    auto result = createOp<mir::ops::ReshapeOp>(graph, inputs[0], out_shape)->getOutput(0);
+
+    context->setNodeOutputs(onnx_node, {result});
+  }
+  else // dimension value is unchanged
+  {
+    context->setNodeOutputs(onnx_node, {inputs[0]});
+  }
+}
+
+void convertReshapeV5(const onnx::NodeProto &onnx_node, ConverterContext *context)
+{
+  std::vector<mir::Operation::Output *> inputs = context->getNodeInputs(onnx_node);
+  mir::Graph *graph = context->getGraph();
+  // The original shape
+  const auto &in_shape = inputs[0]->getShape();
+
+  // Input tensor describing the new shape
+  auto *op = dynamic_cast<mir::ops::ConstantOp *>(inputs[1]->getNode());
+  assert(op && "We support only constant shape input");
+  auto shape_tensor = op->getValue();
+  mir::Shape shape_tensor_shape = (shape_tensor).getShape();
+  assert(shape_tensor_shape.rank() == 1);
+  // The rank of the new shape
+  auto cnt = shape_tensor_shape.numElements();
+  // The vector to build the new shape from
+  std::vector<int32_t> shape_vector(cnt);
+  mir::ShapeRange out_range(shape_tensor_shape);
+  mir::Tensor<int64_t> tensor_accessor(shape_tensor);
+
+  int i = 0;
+  for (auto idx : out_range)
+  {
+    if (tensor_accessor.at(idx) == 0)
+      shape_vector[i] = in_shape.dim(i);
+    else if (tensor_accessor.at(idx) == -1)
+      shape_vector[i] = mir::Shape::autoDim;
+    else
+      shape_vector[i] = tensor_accessor.at(idx);
+    i++;
+  }
+  auto out_shape = mir::Shape(shape_vector);
+  auto result = createOp<mir::ops::ReshapeOp>(graph, inputs[0], out_shape)->getOutput(0);
+
+  context->setNodeOutputs(onnx_node, {result});
+}
+
+} // namespace mir_onnx