[Test] Generate TensorV2 in unit test

This PR includes the implementation of test util functions to create a tensor filled with values to utilize in unit testing. **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 22, 2024 · 114c4cb · 114c4cb
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diff --git a/test/include/nntrainer_test_util.h b/test/include/nntrainer_test_util.h
@@ -38,6 +38,7 @@
 #include <nntrainer_log.h>
 #include <realizer.h>
 #include <tensor.h>
+#include <tensor_v2.h>
 
 /** tolerance is reduced for packaging, but CI runs at full tolerance */
 #ifdef REDUCE_TOLERANCE
@@ -155,6 +156,31 @@ randUniform(unsigned int batch, unsigned channel, unsigned height,
             nntrainer::Tformat fm = nntrainer::Tformat::NCHW,
             nntrainer::Tdatatype d_type = nntrainer::Tdatatype::FP32);
 
+/**
+ * @brief return a tensor filled with contant value with dimension
+ */
+nntrainer::TensorV2
+constantV2(float value, unsigned int d0, unsigned d1, unsigned d2, unsigned d3,
+           nntrainer::Tformat fm = nntrainer::Tformat::NCHW,
+           nntrainer::Tdatatype d_type = nntrainer::Tdatatype::FP32);
+
+/**
+ * @brief return a tensor filled with ranged value with given dimension
+ */
+nntrainer::TensorV2
+rangedV2(unsigned int batch, unsigned channel, unsigned height, unsigned width,
+         nntrainer::Tformat fm = nntrainer::Tformat::NCHW,
+         nntrainer::Tdatatype d_type = nntrainer::Tdatatype::FP32);
+
+/**
+ * @brief return a tensor filled with random value with given dimension
+ */
+nntrainer::TensorV2
+randUniformV2(unsigned int batch, unsigned channel, unsigned height,
+              unsigned width, float min = -1, float max = 1,
+              nntrainer::Tformat fm = nntrainer::Tformat::NCHW,
+              nntrainer::Tdatatype d_type = nntrainer::Tdatatype::FP32);
+
 /**
  * @brief replace string and save in file
  * @param[in] from string to be replaced

diff --git a/test/nntrainer_test_util.cpp b/test/nntrainer_test_util.cpp
@@ -213,6 +213,45 @@ nntrainer::Tensor randUniform(unsigned int batch, unsigned int channel,
   return t;
 }
 
+nntrainer::TensorV2 constantV2(float value, unsigned int d0, unsigned int d1,
+                               unsigned int d2, unsigned int d3,
+                               nntrainer::Tformat fm,
+                               nntrainer::Tdatatype d_type) {
+  nntrainer::TensorV2 t(d0, d1, d2, d3, {fm, d_type});
+  t.setValue(value);
+
+  return t;
+}
+
+nntrainer::TensorV2 rangedV2(unsigned int batch, unsigned int channel,
+                             unsigned int height, unsigned int width,
+                             nntrainer::Tformat fm,
+                             nntrainer::Tdatatype d_type) {
+  nntrainer::TensorV2 t(batch, channel, height, width, {fm, d_type});
+  if (d_type == nntrainer::Tdatatype::FP32) {
+    float i = 0;
+    t = t.apply((std::function<float(float)>)[&](float in) { return i++; });
+  } else if (d_type == nntrainer::Tdatatype::FP16) {
+#ifdef ENABLE_FP16
+    _FP16 i = 0;
+    t = t.apply((std::function<_FP16(_FP16)>)[&](_FP16 in) { return i++; });
+#else
+    throw std::invalid_argument("Error: enable-fp16 is not enabled");
+#endif
+  }
+
+  return t;
+}
+
+nntrainer::TensorV2 randUniformV2(unsigned int batch, unsigned int channel,
+                                  unsigned int height, unsigned int width,
+                                  float min, float max, nntrainer::Tformat fm,
+                                  nntrainer::Tdatatype d_type) {
+  nntrainer::TensorV2 t(batch, channel, height, width, {fm, d_type});
+  t.setRandUniform(min, max);
+  return t;
+}
+
 const std::string
 getResPath(const std::string &filename,
            const std::initializer_list<const char *> fallback_base) {