Set precision in DTensor::saveToFile properly

CHANGELOG.md

@@ -5,6 +5,16 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+<!-- ---------------------
+      v1.5.1
+     --------------------- -->
+## v1.5.1 - 29-11-2024
+
+### Fixed
+
+- Set precision in `DTensor::saveToFile` properly
+- `DTensor<T>::parseFromTextFile` throws `std::invalid_argument` if `T` is unsupported
+
 <!-- ---------------------
       v1.5.0
      --------------------- -->

include/tensor.cuh

@@ -629,8 +629,9 @@ data_t<T> vectorFromFile(std::string path_to_file) {
             vecDataFromFile[i] = std::stoull(line.c_str());
         } else if constexpr (std::is_same_v<T, size_t>) {
             sscanf(line.c_str(), "%zu", &vecDataFromFile[i]);
+        }  else {
+            throw std::invalid_argument("data type not supported");
         }
-        // todo
 
         if (++i == numElements) break;
     }
@@ -653,8 +654,7 @@ void DTensor<T>::saveToFile(std::string pathToFile) {
     file << numRows() << std::endl << numCols() << std::endl << numMats() << std::endl;
     std::vector<T> myData(numEl()); download(myData);
     if constexpr (std::is_floating_point<T>::value) {
-        int prec = std::numeric_limits<T>::max_digits10 - 1;
-        file << std::setprecision(prec);
+        file << std::setprecision(std::numeric_limits<T>::max_digits10);
     }
     for(const T& el : myData) file << el << std::endl;
 }

test/testTensor.cu

@@ -122,24 +122,35 @@ TEST_F(TensorTest, randomTensorCreation) {
 
 TEMPLATE_WITH_TYPE_T
 void parseTensorFromFile() {
-    size_t nR = 20, nC = 40, nM = 60;
-    auto r = DTensor<T>::createRandomTensor(nR, nC, nM, -1, 1);
-    std::string fName = "myTest.dtensor";
-    r.saveToFile(fName);
-    auto a = DTensor<T>::parseFromTextFile(fName);
-    EXPECT_EQ(nR, a.numRows());
-    EXPECT_EQ(nC, a.numCols());
-    EXPECT_EQ(nM, a.numMats());
-    auto diff = a - r;
-    T err = diff.maxAbs();
-    EXPECT_LT(err, 2*std::numeric_limits<T>::epsilon());
+    size_t n_runs = 10;
+    for (size_t i = 0; i < n_runs; i++) {
+        size_t nR = 20, nC = 40, nM = 6;
+        auto r = DTensor<T>::createRandomTensor(nR, nC, nM, -1, 1);
+        std::string fName = "myTest.dtensor";
+        r.saveToFile(fName);
+        auto a = DTensor<T>::parseFromTextFile(fName);
+        EXPECT_EQ(nR, a.numRows());
+        EXPECT_EQ(nC, a.numCols());
+        EXPECT_EQ(nM, a.numMats());
+        auto diff = a - r;
+        T err = diff.maxAbs();
+        EXPECT_LT(err, 2 * std::numeric_limits<T>::epsilon());
+    }
 }
 
 TEST_F(TensorTest, parseTensorFromFile) {
     parseTensorFromFile<float>();
     parseTensorFromFile<double>();
 }
 
+TEST_F(TensorTest, parseTensorUnsupportedDataType) {
+    size_t nR = 20, nC = 40, nM = 60;
+    auto r = DTensor<double>::createRandomTensor(nR, nC, nM, -1, 1);
+    std::string fName = "myTest.dtensor";
+    r.saveToFile(fName);
+    EXPECT_THROW(DTensor<char>::parseFromTextFile(fName), std::invalid_argument);
+}
+
 /* ---------------------------------------
  * Move constructor
  * --------------------------------------- */