Quantizer class to perform quantization

debian/nntrainer-dev.install

@@ -17,6 +17,7 @@
 /usr/include/nntrainer/blas_interface.h
 /usr/include/nntrainer/var_grad.h
 /usr/include/nntrainer/weight.h
+/usr/include/nntrainer/quantizer.h
 /usr/include/nntrainer/blas_avx.h
 # todo: update dataset headers
 /usr/include/nntrainer/databuffer.h

nntrainer/tensor/meson.build

@@ -12,6 +12,7 @@ tensor_sources = [
   'tensor_dim.cpp',
   'var_grad.cpp',
   'weight.cpp',
+  'quantizer.cpp',
   'basic_planner.cpp',
   'memory_pool.cpp',
   'swap_device.cpp',
@@ -31,6 +32,7 @@ tensor_headers = [
   'uint_tensor.h',
   'weight.h',
   'var_grad.h',    
+  'quantizer.h',    
   'tensor_wrap_specs.h',
   'blas_interface.h',
   'manager.h',

nntrainer/tensor/quantizer.cpp

@@ -0,0 +1,84 @@
+// SPDX-License-Identifier: Apache-2.0
+/**
+ * @file	quantizer.cpp
+ * @date	10 December 2024
+ * @brief	This defines quantizers for different types of quantization schemes
+ * @see		https://github.com/nnstreamer/nntrainer
+ * @author	Donghyeon Jeong <[email protected]>
+ * @bug		No known bugs except for NYI items
+ */
+
+#include <quantizer.h>
+
+namespace nntrainer {
+
+/**
+ * @brief PerTensorAffineQuantizer class
+ */
+std::unique_ptr<Quantizer> PerTensorAffineQuantizer::create() {
+  return std::make_unique<PerTensorAffineQuantizer>();
+}
+
+Tensor PerTensorAffineQuantizer::quantize(const Tensor &input,
+                                          Tdatatype qtype) {
+  /// @todo NYI
+  return input;
+}
+
+Tensor PerTensorAffineQuantizer::dequantize(const Tensor &input,
+                                            Tdatatype dtype) {
+  /// @todo NYI
+  return input;
+}
+
+QScheme PerTensorAffineQuantizer::qscheme() const {
+  return QScheme::PER_TENSOR_AFFINE;
+}
+
+/**
+ * @brief PerChannelAffineQuantizer class
+ */
+std::unique_ptr<Quantizer> PerChannelAffineQuantizer::create() {
+  return std::make_unique<PerChannelAffineQuantizer>();
+}
+
+Tensor PerChannelAffineQuantizer::quantize(const Tensor &input,
+                                           Tdatatype qtype) {
+  /// @todo NYI
+  return input;
+}
+
+Tensor PerChannelAffineQuantizer::dequantize(const Tensor &input,
+                                             Tdatatype dtype) {
+  /// @todo NYI
+  return input;
+}
+
+QScheme PerChannelAffineQuantizer::qscheme() const {
+  return QScheme::PER_CHANNEL_AFFINE;
+}
+
+/**
+ * @brief BinaryCodeBasedQuantizer class
+ */
+std::unique_ptr<Quantizer> BinaryCodeBasedQuantizer::create() {
+  return std::make_unique<BinaryCodeBasedQuantizer>();
+}
+
+Tensor BinaryCodeBasedQuantizer::quantize(const Tensor &input,
+                                          Tdatatype qtype) {
+  /// @todo NYI
+  return input;
+}
+
+Tensor BinaryCodeBasedQuantizer::dequantize(const Tensor &input,
+                                            Tdatatype dtype) {
+  /// @todo NYI
+  return input;
+}
+
+QScheme BinaryCodeBasedQuantizer::qscheme() const {
+  return QScheme::BINARY_CODE_BASED;
+}
+
+} // namespace nntrainer