[Blas] copy functionality for signed int16 data type

This pull request aims to add the functionality of copying the int16 data type into fp32. Please note that this implementation does not utilize SIMD at this time. **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 17, 2025 · ee3b1d5 · ee3b1d5
1 parent ebae34b
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diff --git a/nntrainer/tensor/blas_interface.cpp b/nntrainer/tensor/blas_interface.cpp
@@ -979,6 +979,15 @@ void scopy_int8_to_float32(const unsigned int N, const int8_t *X,
   }
 }
 
+void copy_s16_fp32(const unsigned int N, const int16_t *X, float *Y) {
+#ifdef USE_NEON
+  nntrainer::neon::copy_s16_fp32(N, X, Y);
+#endif
+  for (unsigned int idx = 0; idx < N; ++idx) {
+    Y[idx] = (float)X[idx];
+  }
+}
+
 float snrm2(const int N, const float *X, const int incX) {
 #ifdef USE_BLAS
 #ifdef BLAS_NUM_THREADS

diff --git a/nntrainer/tensor/blas_interface.h b/nntrainer/tensor/blas_interface.h
@@ -320,6 +320,14 @@ void scopy_int8_to_float32(const unsigned int N, const uint8_t *X,
 void scopy_int8_to_float32(const unsigned int N, const int8_t *X,
                            const int incX, float *Y, const int intY);
 
+/**
+ * @brief     copy function : Y = X
+ * @param[in] N number of elements in X
+ * @param[in] X int16_t * for Vector X
+ * @param[in] Y float * for Vector Y
+ */
+void copy_s16_fp32(const unsigned int N, const int16_t *X, float *Y);
+
 /**
  * @brief     sdot computation : sum of all X * Y
  * @param[in] N number of elements in Y

diff --git a/nntrainer/tensor/blas_neon.cpp b/nntrainer/tensor/blas_neon.cpp
@@ -1597,6 +1597,14 @@ void copy_int8_to_fp32(const unsigned int N, const int8_t *X, float *Y) {
   }
 }
 
+void copy_s16_fp32(const unsigned int N, const int16_t *X, float *Y) {
+  /// @todo implement int16_t to fp32
+  unsigned int idx = 0;
+  for (; (N - idx) >= 1; ++idx) {
+    Y[idx] = X[idx];
+  }
+}
+
 void copy_fp16_to_fp32(const unsigned int N, const __fp16 *X, float *Y) {
   unsigned int idx = 0;
 

diff --git a/nntrainer/tensor/blas_neon.h b/nntrainer/tensor/blas_neon.h
@@ -88,6 +88,15 @@ void copy_int8_or_int4(const unsigned int N, const uint8_t *X, uint8_t *Y);
  * @param[in] Y int8_t * for Vector Y
  */
 void copy_int8(const unsigned int N, const int8_t *X, int8_t *Y);
+
+/**
+ * @brief     copy function with neon: Y = X
+ * @param[in] N number of elements in X
+ * @param[in] X int16_t * for Vector X
+ * @param[in] Y float * for Vector Y
+ */
+void copy_s16_fp32(const unsigned int N, const int16_t *X, float *Y);
+
 /**
  * @brief     sine with neon: Y = sin(alpha * X)
  * @param[in] N number of elements in X

diff --git a/nntrainer/tensor/float_tensor.cpp b/nntrainer/tensor/float_tensor.cpp
@@ -763,6 +763,9 @@ void FloatTensor::copyData(const Tensor &from) {
     throw std::invalid_argument("Error: enable-fp16 is not enabled");
 #endif
     break;
+  case ml::train::TensorDim::DataType::QINT16:
+    copy_s16_fp32(from.size(), from.getData<int16_t>(), (float *)getData());
+    break;
   case ml::train::TensorDim::DataType::QINT8:
     scopy_int8_to_float32(from.size(), from.getData<int8_t>(), 1,
                           (float *)getData(), 1);