Merge pull request #9188 from KonduitAI/qwr_fix_testFailures

fix test failures

libnd4j/include/ops/declarable/generic/nn/fusedBatchNorm.cpp

@@ -89,8 +89,8 @@ namespace sd {
             else {
                 //REQUIRE_TRUE(block.width() == 3, 0, "CUSTOM_OP fused_batch_norm: when isTraining=true then number of input arrays must be equal to 3, but got %i instead !", block.width());
                 std::vector<Nd4jLong> shape = {iD};
-                mean = NDArrayFactory::create_(scale->ordering(), shape, sd::DataType::FLOAT32, block.launchContext());
-                variance = NDArrayFactory::create_(scale->ordering(), shape, sd::DataType::FLOAT32, block.launchContext());
+                mean = NDArrayFactory::create_(scale->ordering(), shape, scale->dataType(), block.launchContext());
+                variance = NDArrayFactory::create_(scale->ordering(), shape, scale->dataType(), block.launchContext());
             }
 
 
@@ -104,7 +104,7 @@ namespace sd {
 
             const int restSize = x->lengthOf() / iD;
 
-            auto xAffected = NDArrayFactory::create(x->ordering(), {restSize, iD}, sd::DataType::FLOAT32, block.launchContext());
+            auto xAffected = NDArrayFactory::create(x->ordering(), {restSize, iD}, mean->dataType(), block.launchContext());
             xAffected.assign(xCast);
 
             const int restSizeMinusOne = (restSize > 1) ? (restSize - 1) : 1;

libnd4j/include/ops/declarable/generic/random/uniform.cpp

@@ -40,7 +40,7 @@ namespace sd {
          * TArgs[0] - min for rng
          * TArgs[1] - max for rng
          */
-        CUSTOM_OP_IMPL(randomuniform, -1, 1, true, 0, -1) {
+        CUSTOM_OP_IMPL(randomuniform, -1, 1, true, 0, -2) {
             // uniform distribution
             auto rng = block.randomGenerator();
             auto dtype = DataType::FLOAT32;

libnd4j/include/ops/declarable/generic/shape/reshape.cpp

@@ -61,6 +61,29 @@ DECLARE_TYPES(reshape) {
       ->setSameMode(true);
 }
 
+
+bool handleOptionalOrder(std::vector<int> &reshapeArgs, char &ordering){
+    if(reshapeArgs.size()>0){
+        //check if any optional negative ordering value is passed
+        auto optional = reshapeArgs[0]; 
+        if(optional < 0){
+            optional = abs(optional);
+            //check if passed option is allowed. (-1 -> dynamic shape)
+            // in that case we will return back
+            if(optional == 1 ) return true;
+            //in this case it should obey allowed orderings
+            if (optional != 'c' && optional != 'f' ) return false;
+            reshapeArgs.erase( reshapeArgs.begin());
+            //ordering was passed and ok. let's assign
+            ordering = optional;
+        } 
+
+    }
+    //skipped 
+    return true;
+}
+
+
 DECLARE_SHAPE_FN(reshape) {
 
   const auto x = INPUT_VARIABLE(0);
@@ -78,26 +101,14 @@ DECLARE_SHAPE_FN(reshape) {
    */
   if (block.width() == 1) {
     reshapeArgs = *block.getIArguments();
-    if (!reshapeArgs.empty()) {
-      char potentialOrdering = (char)-reshapeArgs[0];
-      orderNew = potentialOrdering;
-      if (potentialOrdering != 'c' && potentialOrdering != 'f') {
+    if(!handleOptionalOrder(reshapeArgs, orderNew)){
         throw std::runtime_error(
             "reshape:: Value passed in must be -99 or -102 for the ordering if "
             "an int array is present. -99 represents c ordering and -102 "
             "represents f ordering. This number is negative for the long array "
             "case to flag the difference between an ordering and a dimension "
             "being specified.");
-      }
-
-      nd4j_debug("Reshape Ordering is %c int ordering is %d\n", orderNew,
-                 -reshapeArgs[0]);
-
-      if (orderNew == 'c' || orderNew == 'f')
-        reshapeArgs.erase(
-            reshapeArgs
-                .begin()); // remove first element being order in this case
-    }
+      }; 
   } else {
     reshapeArgs = INPUT_VARIABLE(1)->getBufferAsVector<int>();
     if (block.numI() > 0) {

libnd4j/tests_cpu/layers_tests/SparseUtilsTest.cpp

@@ -227,6 +227,7 @@ TEST_F(SparseUtilsTest, RavelIndices_Test) {
     }
 
     shape[2] = 30;
+    delete[] shapeInfoBuffer;
     shapeInfoBuffer = shape::shapeBuffer(rank, sd::DataType::INT64, shape);
 
     try {