[mir] Remove Deserializer unittest (#6178)

This is a leftover after removing serialization support.

Signed-off-by: Sergei Barannikov <s.barannikov@samsung.com>

diff --git a/compiler/mir/unittests/Deserializer.cpp b/compiler/mir/unittests/Deserializer.cpp
deleted file mode 100644 (file)
index 5b23f90..0000000
--- a/compiler/mir/unittests/Deserializer.cpp
+++ /dev/null
@@ -1,303 +0,0 @@
-/*
- * 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 <gtest/gtest.h>
-
-#include "mir/Deserializer.h"
-#include "mir/ShapeRange.h"
-#include "mir/Tensor.h"
-
-using namespace mir;
-
-const double EPS = 0.0000001;
-
-static void checkShape(const Shape &shape, const proto::TensorShapeProto &proto_shape)
-{
-  ASSERT_EQ(shape.rank(), proto_shape.dims_size());
-  for (int i = 0; i < shape.rank(); i++)
-  {
-    ASSERT_EQ(shape.dim(i), proto_shape.dims(i));
-  }
-}
-
-template <typename T>
-static void checkTensorContent(const Tensor<T> &tensor, const proto::TensorProto &proto_tensor)
-{
-  ShapeRange range(tensor.getShape());
-  auto data = (T *)proto_tensor.tensor_content().c_str();
-  int i = 0;
-  for (auto &idx : range)
-  {
-    ASSERT_EQ(tensor.at(idx), data[i++]);
-  }
-}
-
-static void checkIntTensor(const Tensor<int> &tensor, const proto::TensorProto &proto_tensor)
-{
-  ASSERT_EQ(proto_tensor.dtype(), proto::DataType::DT_INT32);
-  checkTensorContent<int>(tensor, proto_tensor);
-}
-
-static void checkFloatTensor(const Tensor<float> &tensor, const proto::TensorProto &proto_tensor)
-{
-  ASSERT_EQ(proto_tensor.dtype(), proto::DataType::DT_FLOAT);
-  checkTensorContent<float>(tensor, proto_tensor);
-}
-
-static void checkDoubleTensor(const Tensor<double> &tensor, const proto::TensorProto &proto_tensor)
-{
-  ASSERT_EQ(proto_tensor.dtype(), proto::DataType::DT_DOUBLE);
-  checkTensorContent<double>(tensor, proto_tensor);
-}
-
-TEST(Deserializer, ShapeDeserializationTest)
-{
-  Deserializer<Shape> deserializer;
-
-  proto::TensorShapeProto proto_shape;
-  std::string serializedShape;
-  Shape shape;
-  proto_shape.SerializeToString(&serializedShape);
-  shape = deserializer.deserializeFromString(serializedShape);
-  checkShape(shape, proto_shape);
-
-  proto_shape.add_dims(5);
-  proto_shape.SerializeToString(&serializedShape);
-  shape = deserializer.deserializeFromString(serializedShape);
-  checkShape(shape, proto_shape);
-
-  proto_shape.add_dims(2);
-  proto_shape.add_dims(4);
-  proto_shape.SerializeToString(&serializedShape);
-  shape = deserializer.deserializeFromString(serializedShape);
-  checkShape(shape, proto_shape);
-
-  proto_shape.clear_dims();
-  proto_shape.add_dims(1);
-  proto_shape.add_dims(1);
-  proto_shape.add_dims(1);
-  proto_shape.add_dims(1);
-  proto_shape.SerializeToString(&serializedShape);
-  shape = deserializer.deserializeFromString(serializedShape);
-  checkShape(shape, proto_shape);
-}
-
-TEST(Deserializer, IntTensorDeserializationTest)
-{
-  Deserializer<TensorVariant> deserializer;
-  int tmp = 0;
-
-  std::vector<int> values;
-  proto::TensorProto proto_tensor;
-  proto_tensor.set_dtype(proto::DataType::DT_INT32);
-  proto::TensorShapeProto *proto_shapePtr = proto_tensor.mutable_shape();
-  std::string serializedTensor;
-
-  Shape shape_1{3};
-  for (auto &idx : ShapeRange(shape_1))
-  {
-    (void)idx;
-    values.push_back(tmp++);
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(int) * shape_1.numElements()));
-  for (int32_t i = 0; i < shape_1.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_1.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_1 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_1, proto_tensor.shape());
-  checkIntTensor(Tensor<int>(tensor_1), proto_tensor);
-
-  Shape shape_2{3, 4, 5};
-  values.clear();
-  proto_shapePtr->clear_dims();
-  for (auto &idx : ShapeRange(shape_2))
-  {
-    (void)idx;
-    values.push_back(tmp--);
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(int) * shape_2.numElements()));
-  for (int32_t i = 0; i < shape_2.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_2.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_2 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_2, proto_tensor.shape());
-  checkIntTensor(Tensor<int>(tensor_2), proto_tensor);
-
-  Shape shape_3{1, 1, 1, 1, 1};
-  values.clear();
-  proto_shapePtr->clear_dims();
-  for (auto &idx : ShapeRange(shape_3))
-  {
-    (void)idx;
-    values.push_back(tmp++);
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(int) * shape_3.numElements()));
-  for (int32_t i = 0; i < shape_3.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_3.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_3 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_3, proto_tensor.shape());
-  checkIntTensor(Tensor<int>(tensor_3), proto_tensor);
-}
-
-TEST(Deserializer, FloatTensorDeserializationTest)
-{
-  Deserializer<TensorVariant> deserializer;
-  float tmp = 1.0f;
-
-  std::vector<float> values;
-  proto::TensorProto proto_tensor;
-  proto_tensor.set_dtype(proto::DataType::DT_FLOAT);
-  proto::TensorShapeProto *proto_shapePtr = proto_tensor.mutable_shape();
-  std::string serializedTensor;
-
-  Shape shape_1{3};
-  for (auto &idx : ShapeRange(shape_1))
-  {
-    (void)idx;
-    values.push_back(tmp);
-    tmp += 7.3f;
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(float) * shape_1.numElements()));
-  for (int32_t i = 0; i < shape_1.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_1.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_1 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_1, proto_tensor.shape());
-  checkFloatTensor(Tensor<float>(tensor_1), proto_tensor);
-
-  Shape shape_2{3, 4, 5};
-  values.clear();
-  proto_shapePtr->clear_dims();
-  for (auto &idx : ShapeRange(shape_2))
-  {
-    (void)idx;
-    values.push_back(tmp);
-    tmp *= -1.32f;
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(float) * shape_2.numElements()));
-  for (int32_t i = 0; i < shape_2.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_2.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_2 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_2, proto_tensor.shape());
-  checkFloatTensor(Tensor<float>(tensor_2), proto_tensor);
-
-  Shape shape_3{1, 1, 1, 1, 1};
-  values.clear();
-  proto_shapePtr->clear_dims();
-  for (auto &idx : ShapeRange(shape_3))
-  {
-    (void)idx;
-    tmp /= 2;
-    values.push_back(tmp);
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(float) * shape_3.numElements()));
-  for (int32_t i = 0; i < shape_3.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_3.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_3 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_3, proto_tensor.shape());
-  checkFloatTensor(Tensor<float>(tensor_3), proto_tensor);
-}
-
-TEST(Deserializer, DoubleTensorDeserializationTest)
-{
-  Deserializer<TensorVariant> deserializer;
-  double tmp = 1.0f;
-
-  std::vector<double> values;
-  proto::TensorProto proto_tensor;
-  proto_tensor.set_dtype(proto::DataType::DT_DOUBLE);
-  proto::TensorShapeProto *proto_shapePtr = proto_tensor.mutable_shape();
-  std::string serializedTensor;
-
-  Shape shape_1{3};
-  for (auto &idx : ShapeRange(shape_1))
-  {
-    (void)idx;
-    values.push_back(tmp);
-    tmp += 7.3f;
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(double) * shape_1.numElements()));
-  for (int32_t i = 0; i < shape_1.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_1.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_1 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_1, proto_tensor.shape());
-  checkDoubleTensor(Tensor<double>(tensor_1), proto_tensor);
-
-  Shape shape_2{3, 4, 5};
-  values.clear();
-  proto_shapePtr->clear_dims();
-  for (auto &idx : ShapeRange(shape_2))
-  {
-    (void)idx;
-    values.push_back(tmp);
-    tmp *= -1.32f;
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(double) * shape_2.numElements()));
-  for (int32_t i = 0; i < shape_2.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_2.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_2 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_2, proto_tensor.shape());
-  checkDoubleTensor(Tensor<double>(tensor_2), proto_tensor);
-
-  Shape shape_3{1, 1, 1, 1, 1};
-  values.clear();
-  proto_shapePtr->clear_dims();
-  for (auto &idx : ShapeRange(shape_3))
-  {
-    (void)idx;
-    tmp /= 2;
-    values.push_back(tmp);
-  }
-  proto_tensor.set_tensor_content(
-      std::string((char *)values.data(), sizeof(double) * shape_3.numElements()));
-  for (int32_t i = 0; i < shape_3.rank(); i++)
-  {
-    proto_shapePtr->add_dims(shape_3.dim(i));
-  }
-  proto_tensor.SerializeToString(&serializedTensor);
-  TensorVariant tensor_3 = deserializer.deserializeFromString(serializedTensor);
-  checkShape(shape_3, proto_tensor.shape());
-  checkDoubleTensor(Tensor<double>(tensor_3), proto_tensor);
-}