[onert] Adding shape inference for Abs and its test case (Samsung#1380)

* [onert] Adding shape inference for Abs and its test case

This adds shape inference for Abs and its test case.

Signed-off-by: Hyun Sik Yoon <hyunsik.yoon.1024@gmail.com>

* fix compilation error after rebasing

runtime/onert/core/include/util/ShapeInference.h

@@ -102,6 +102,7 @@ class StaticInferer : public ir::OperationVisitor
 private:
   // TODO Define visitors for operations. List them in alphabetic order.
   // Remove TODO when any op starting from the alphabet is added
+  void visit(const ir::operation::Abs &op);
   void visit(const ir::operation::Add &op);
   void visit(const ir::operation::Concat &op);
   // TODO write op starting from D
@@ -118,6 +119,13 @@ class StaticInferer : public ir::OperationVisitor
   // TODO write op starting from U
   // TODO write op starting from Z
 
+private:
+  /**
+   * @brief Performs shape inference for unary op whose output shape is
+   *        always same with input shape
+   */
+  void handleSimpleUnaryOp(const ir::Operation &op, const ir::OperandIndex input_idx);
+
 private:
   ir::Operands &_operands;
 };
@@ -143,6 +151,7 @@ class DynamicInferer : public ir::OperationVisitor
 public:
   // TODO Define visitors for operations. List them in alphabetic order.
   // Remove TODO when any op starting from the alphabet is added
+  void visit(const ir::operation::Abs &op);
   void visit(const ir::operation::Add &op);
   // TODO write op starting from C
   // TODO write op starting from D
@@ -159,6 +168,13 @@ class DynamicInferer : public ir::OperationVisitor
   // TODO write op starting from U
   // TODO write op starting from Z
 
+private:
+  /**
+   * @brief Performs shape inference and memory allocation for unary op whose output shape is
+   *        always same with input shape
+   */
+  void handleSimpleUnaryOp(const ir::Operation &op, const ir::OperandIndex input_idx);
+
 private:
   /**
    * @brief To get operand-level info, e.g., ir::Operand::isConstant()

runtime/onert/core/src/util/shapeinf/Abs.cc

@@ -0,0 +1,35 @@
+/*
+ * Copyright (c) 2020 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 "util/ShapeInference.h"
+
+namespace onert
+{
+namespace shape_inference
+{
+
+void StaticInferer::visit(const ir::operation::Abs &op)
+{
+  handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::Abs::Input::INPUT));
+}
+
+void DynamicInferer::visit(const ir::operation::Abs &op)
+{
+  handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::Abs::INPUT));
+}
+
+} // namespace shape_inference
+} // namespace onert

runtime/onert/core/src/util/shapeinf/ShapeInference.cc

@@ -211,6 +211,26 @@ ir::Shape inferMaxPoolShape(const ir::Shape &in_shape, const ir::operation::MaxP
   - For visit() of each operator, find each op's C file
 */
 
+void StaticInferer::handleSimpleUnaryOp(const ir::Operation &op, const ir::OperandIndex input_idx)
+{
+  const auto &input = _operands.at(input_idx);
+
+  // get mutable output operand
+  const auto output_idx = op.getOutputs().at(0);
+  ir::Operand &output = _operands.at(output_idx);
+
+  // if input is dynamic, output also becomes dynamic
+  if (input.info().isDynamic())
+  {
+    output.info().setDynamic();
+    return;
+  }
+
+  // re-sizing output shape
+  ir::Shape new_shape = input.info().shape();
+  output.info().shape(new_shape);
+}
+
 void StaticInferer::dump()
 {
   auto get_shape_str = [](const ir::Shape &shape) {
@@ -269,5 +289,24 @@ void StaticInferer::visit(const ir::operation::Concat &op)
   - For visit() of each operator, find each op's C file
  */
 
+void DynamicInferer::handleSimpleUnaryOp(const ir::Operation &op, const ir::OperandIndex input_ind)
+{
+  // check if output is not dynamic
+  auto output_ind = op.getOutputs().at(0);
+  auto output = _tensor_registry->getITensor(output_ind);
+  if (!output->is_dynamic())
+    return;
+
+  // getting output shape
+  auto input = _tensor_registry->getITensor(input_ind);
+  auto output_shape = getShape(input.get());
+
+  // set output shape and output buffer
+  setShape(output.get(), output_shape);
+
+  _dynamic_tensor_manager->allocate(output_ind, output_shape);
+  assert(output->buffer() != nullptr);
+}
+
 } // namespace shape_inference
 } // namespace onert

runtime/onert/core/src/util/shapeinf/Tanh.cc

@@ -23,43 +23,12 @@ namespace shape_inference
 
 void StaticInferer::visit(const ir::operation::Tanh &op)
 {
-  const auto input_idx{op.getInputs().at(ir::operation::Tanh::Input::INPUT)};
-  const auto &input = _operands.at(input_idx);
-
-  // get mutable output operand
-  const auto output_idx = op.getOutputs().at(0);
-  ir::Operand &output = _operands.at(output_idx);
-
-  // if input is dynamic, output also becomes dynamic
-  if (input.info().isDynamic())
-  {
-    output.info().setDynamic();
-    return;
-  }
-
-  // re-sizing output shape
-  ir::Shape new_shape = input.info().shape();
-  output.info().shape(new_shape);
+  handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::Tanh::Input::INPUT));
 }
 
 void DynamicInferer::visit(const ir::operation::Tanh &op)
 {
-  // check if output is not dynamic
-  auto output_ind = op.getOutputs().at(0);
-  auto output = _tensor_registry->getITensor(output_ind);
-  if (!output->is_dynamic())
-    return;
-
-  // getting output shape
-  auto input_ind = op.getInputs().at(ir::operation::Tanh::Input::INPUT);
-  auto input = _tensor_registry->getITensor(input_ind);
-  auto output_shape = getShape(input.get());
-
-  // set output shape and output buffer
-  setShape(output.get(), output_shape);
-
-  _dynamic_tensor_manager->allocate(output_ind, output_shape);
-  assert(output->buffer() != nullptr);
+  handleSimpleUnaryOp(op, op.getInputs().at(ir::operation::Tanh::INPUT));
 }
 
 } // namespace shape_inference

tests/nnapi/nnapi_gtest.skip.aarch64-linux.acl_cl

@@ -1,4 +1,5 @@
 GeneratedTests.abs_
+GeneratedTests.abs_dynamic_nnfw
 GeneratedTests.add_dynamic
 GeneratedTests.cast_float16_to_float16
 GeneratedTests.cast_float16_to_float32

tests/nnapi/nnapi_gtest.skip.aarch64-linux.acl_neon

@@ -1,4 +1,5 @@
 GeneratedTests.abs_
+GeneratedTests.abs_dynamic_nnfw
 GeneratedTests.add_dynamic
 GeneratedTests.cast_float16_to_float16
 GeneratedTests.cast_float16_to_float32

tests/nnapi/nnapi_gtest.skip.armv7l-linux.acl_cl

@@ -1,4 +1,5 @@
 GeneratedTests.abs_
+GeneratedTests.abs_dynamic_nnfw
 GeneratedTests.add_dynamic
 GeneratedTests.cast_float16_to_float16
 GeneratedTests.cast_float16_to_float32

tests/nnapi/nnapi_gtest.skip.armv7l-linux.acl_neon

@@ -1,5 +1,5 @@
 GeneratedTests.abs_
-GeneratedTests.abs_dynamic
+GeneratedTests.abs_dynamic_nnfw
 GeneratedTests.add_dynamic
 GeneratedTests.cast_float16_to_float16
 GeneratedTests.cast_float16_to_float32

tests/nnapi/nnapi_gtest.skip.noarch.interp

@@ -3,6 +3,7 @@ GeneratedTests.abs_1D_float_nnfw
 GeneratedTests.abs_2D_float_nnfw
 GeneratedTests.abs_3D_float_nnfw
 GeneratedTests.abs_4D_float_nnfw
+GeneratedTests.abs_dynamic_nnfw
 GeneratedTests.add_broadcast_quant8
 GeneratedTests.add_dynamic
 GeneratedTests.add_quant8

tests/nnapi/specs/V1_2/abs_dynamic_nnfw.mod.py

@@ -0,0 +1,65 @@
+#
+# Copyright (C) 2018 The Android Open Source Project
+# Copyright (c) 2020 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.
+#
+
+# refer to tanh_v1_dynamic.mod.py about the structore
+
+# This adds reshape as the first op in a model and
+# returns output of reshape, which is dynamic tensor
+
+'''
+Testing Abs op when the input is dynamic.
+
+      input [1, 2, 3]  shape [3]  (value of shape will be [1, 2, 3])
+          |             |
+          +-------------+
+          |
+       Reshape (added by DynamicInputGenerator since it generates its output to be dynamic)
+          |
+          | dynamic tensor at compilation time but the shape will be [1, 2, 3] at execution time
+          |
+         Abs
+          |
+        output (dynamic tensor, [1, 2, 3] at execution time)
+'''
+
+import dynamic_tensor
+
+model = Model()
+
+model_input_shape = [1, 2, 3]
+
+dynamic_layer = dynamic_tensor.DynamicInputGenerator(model, model_input_shape)
+
+test_node_input = dynamic_layer.getTestNodeInput()
+
+# write ABS test. input is `test_input`
+
+# note output shape is used by expected output's shape
+model_output = Output("output", "TENSOR_FLOAT32", "{1, 2, 3}")
+
+model.Operation("ABS", test_node_input).To(model_output)
+
+model_input_data = [1, -2, 3, -4, 5, -6]
+model_output_data = [1, 2, 3, 4, 5, 6]
+
+Example({
+    # use these two as input
+    dynamic_layer.getModelInput(): model_input_data,
+    dynamic_layer.getShapeInput() : model_input_shape,
+
+    model_output: model_output_data,
+})