1 files changed, 71 insertions, 0 deletions
diff --git a/compiler/mir-interpreter/src/ops/Quantization.cpp b/compiler/mir-interpreter/src/ops/Quantization.cpp
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index 000000000..283a7c751
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+++ b/compiler/mir-interpreter/src/ops/Quantization.cpp
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+/*
+ * 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 "Quantization.h"
+#include "mir/Tensor.h"
+#include "mir/ShapeRange.h"
+
+#include <cmath>
+#include <limits>
+
+namespace mir_interpreter
+{
+using namespace mir;
+
+void Dequantize(const TensorVariant &input, TensorVariant &output)
+{
+  const TensorType &input_type = input.getType();
+  assert(input_type.isQuantized());
+  assert(input_type.getElementType() == DataType::UINT8);
+
+  const float scale = input_type.getQuantization().getScale();
+  const int32_t zero_point = input_type.getQuantization().getZeroPoint();
+
+  Tensor<uint8_t> input_accessor(input);
+  Tensor<float> res_accessor(output);
+
+  for (const auto &index : ShapeRange(output.getShape()))
+  {
+    const int32_t value = input_accessor.at(index);
+    res_accessor.at(index) = scale * static_cast<float>(value - zero_point);
+  }
+}
+
+void Quantize(const TensorVariant &input, TensorVariant &output)
+{
+  const TensorType &output_type = output.getType();
+  assert(output_type.isQuantized());
+  assert(input.getElementType() == DataType::FLOAT32);
+
+  const float scale = output_type.getQuantization().getScale();
+  const int32_t zero_point = output_type.getQuantization().getZeroPoint();
+
+  const int32_t min_val = std::numeric_limits<uint8_t>::min();
+  const int32_t max_val = std::numeric_limits<uint8_t>::max();
+
+  Tensor<float> input_accessor(input);
+  Tensor<uint8_t> res_accessor(output);
+
+  for (const auto &index : ShapeRange(output.getShape()))
+  {
+    const float value = input_accessor.at(index);
+    int32_t unclamped = static_cast<int32_t>(std::round(value / scale)) + zero_point;
+    int32_t clamped = std::min(std::max(unclamped, min_val), max_val);
+    res_accessor.at(index) = static_cast<uint8_t>(clamped);
+  }
+}
+
+} // namespace mir_interpreter