[TensorV2] Multiplication operation skeleton

This pull request adds a basic implementation of tensor multiplication operations to our codebase. The new functionality allows users to perform multiplication of tensors by simply calling a function. **Self-evaluation:** 1. Build test: [X]Passed [ ]Failed [ ]Skipped 2. Run test: [X]Passed [ ]Failed [ ]Skipped Signed-off-by: Donghyeon Jeong <[email protected]>
nnstreamer · Jan 19, 2024 · ac68c68 · ac68c68
1 parent cd11a54
commit ac68c68
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diff --git a/nntrainer/tensor/float_tensor.h b/nntrainer/tensor/float_tensor.h
@@ -178,6 +178,30 @@ class FloatTensor : public TensorBase {
   TensorV2 &apply(std::function<float(float)> f,
                   TensorV2 &output) const override;
 
+  /**
+   * @copydoc TensorV2::multiply_i(float const &value)
+   * @todo    Need implementation and unit tests
+   */
+  int multiply_i(float const &value) override { return 0; }
+
+  /**
+   * @copydoc TensorV2::multiply(float const &value, TensorV2 &out)
+   * @todo    Need implementation and unit tests
+   */
+  TensorV2 &multiply(float const &value, TensorV2 &out) const override {
+    return out;
+  }
+
+  /**
+   * @copydoc TensorV2::multiply(TensorV2 const &m, TensorV2 &output, const
+   * float beta = 0.0)
+   * @todo    Need implementation and unit tests
+   */
+  TensorV2 &multiply(TensorV2 const &m, TensorV2 &output,
+                     const float beta = 0.0) const override {
+    return output;
+  }
+
   /**
    * @copydoc TensorV2::print(std::ostream &out)
    */

diff --git a/nntrainer/tensor/half_tensor.h b/nntrainer/tensor/half_tensor.h
@@ -177,6 +177,30 @@ class HalfTensor : public TensorBase {
   TensorV2 &apply(std::function<_FP16(_FP16)> f,
                   TensorV2 &output) const override;
 
+  /**
+   * @copydoc TensorV2::multiply_i(float const &value)
+   * @todo    Need implementation and unit tests
+   */
+  int multiply_i(float const &value) override { return 0; }
+
+  /**
+   * @copydoc TensorV2::multiply(float const &value, TensorV2 &out)
+   * @todo    Need implementation and unit tests
+   */
+  TensorV2 &multiply(float const &value, TensorV2 &out) const override {
+    return out;
+  }
+
+  /**
+   * @copydoc TensorV2::multiply(TensorV2 const &m, TensorV2 &output, const
+   * float beta = 0.0)
+   * @todo    Need implementation and unit tests
+   */
+  TensorV2 &multiply(TensorV2 const &m, TensorV2 &output,
+                     const float beta = 0.0) const override {
+    return output;
+  }
+
   /**
    * @copydoc TensorV2::print(std::ostream &out)
    */

diff --git a/nntrainer/tensor/tensor_base.h b/nntrainer/tensor/tensor_base.h
@@ -182,6 +182,23 @@ class TensorBase {
    */
   virtual void initialize(Initializer init) = 0;
 
+  /**
+   * @copydoc TensorV2::multiply_i(float const &value)
+   */
+  virtual int multiply_i(float const &value) = 0;
+
+  /**
+   * @copydoc TensorV2::multiply(float const &value, TensorV2 &out)
+   */
+  virtual TensorV2 &multiply(float const &value, TensorV2 &out) const = 0;
+
+  /**
+   * @copydoc TensorV2::multiply(TensorV2 const &m, TensorV2 &output, const
+   * float beta = 0.0)
+   */
+  virtual TensorV2 &multiply(TensorV2 const &m, TensorV2 &output,
+                             const float beta = 0.0) const = 0;
+
   /**
    * @copydoc TensorV2::print(std::ostream &out)
    */

diff --git a/nntrainer/tensor/tensor_v2.cpp b/nntrainer/tensor/tensor_v2.cpp
@@ -151,6 +151,31 @@ TensorV2 &TensorV2::apply(std::function<TensorV2 &(TensorV2, TensorV2 &)> f,
   return f(*this, output);
 }
 
+int TensorV2::multiply_i(float const &value) { return ML_ERROR_NONE; }
+
+TensorV2 TensorV2::multiply(float const &value) const {
+  TensorV2 t;
+  return multiply(value, t);
+}
+
+TensorV2 &TensorV2::multiply(float const &value, TensorV2 &out) const {
+  return out;
+}
+
+int TensorV2::multiply_i(TensorV2 const &m, const float beta) {
+  return ML_ERROR_NONE;
+}
+
+TensorV2 TensorV2::multiply(TensorV2 const &m, const float beta) const {
+  TensorV2 t("", this->getFormat());
+  return multiply(m, t, beta);
+}
+
+TensorV2 &TensorV2::multiply(TensorV2 const &m, TensorV2 &output,
+                             const float beta) const {
+  return output;
+}
+
 void TensorV2::print(std::ostream &out) const { itensor->print(out); }
 
 void TensorV2::putData() const { itensor->putData(); }

diff --git a/nntrainer/tensor/tensor_v2.h b/nntrainer/tensor/tensor_v2.h
@@ -21,6 +21,7 @@
 
 #include <cstddef>
 
+#include <nntrainer_log.h>
 #include <tensor_base.h>
 
 namespace nntrainer {
@@ -467,6 +468,55 @@ class TensorV2 {
   TensorV2 &apply(std::function<TensorV2 &(TensorV2, TensorV2 &)> f,
                   TensorV2 &output) const;
 
+  /**
+   * @brief     Multiply value element by element immediately
+   * @param[in] value multiplier
+   * @retval    #ML_ERROR_INVALID_PARAMETER Tensor dimension is not right
+   * @retval    #ML_ERROR_NONE Successful
+   */
+  int multiply_i(float const &value);
+
+  /**
+   * @brief     Multiply value element by element
+   * @param[in] value multiplier
+   * @retval    Calculated Tensor
+   */
+  TensorV2 multiply(float const &value) const;
+
+  /**
+   * @brief      multiply value element by element
+   * @param[in]  value multiplier
+   * @param[out] out out tensor to store the result
+   * @retval     Calculated Tensor
+   */
+  TensorV2 &multiply(float const &value, TensorV2 &out) const;
+
+  /**
+   * @brief     Multiply Tensor Elementwise
+   * @param[in] m Tensor to be multiplied
+   * @param[in] beta scalar to multiply output with and add
+   * @retval    #ML_ERROR_NONE successful
+   */
+  int multiply_i(TensorV2 const &m, const float beta = 0.0);
+
+  /**
+   * @brief     Multiply Tensor Element by Element ( Not the MxM )
+   * @param[in] m Tensor to be multiplied
+   * @param[in] beta scalar to multiply output with and add
+   * @retval    Calculated Tensor
+   */
+  TensorV2 multiply(TensorV2 const &m, const float beta = 0.0) const;
+
+  /**
+   * @brief      Multiply Tensor Element by Element ( Not the MxM )
+   * @param[in]  m Tensor to be multiplied
+   * @param[out] output Tensor to store the result
+   * @param[in]  beta scalar to multiply output with and add
+   * @retval     Calculated Tensor
+   */
+  TensorV2 &multiply(TensorV2 const &m, TensorV2 &output,
+                     const float beta = 0.0) const;
+
   /**
    * @brief     Print element
    * @param[in] out out stream