lower: fix a bug causing undefined variables when applying fuse

Fixes tensor-compiler#355.

This commit fixes a bug where the fuse transformation would not generate
necessary locator variables when applied to iteration over two dense
variables.

Additionally, this commit adds a test for when a dense iteration results
in a transposition of a tensor.

src/lower/lowerer_impl.cpp

@@ -417,6 +417,24 @@ Stmt LowererImpl::lowerForall(Forall forall)
     Expr recoveredValue = provGraph.recoverVariable(varToRecover, definedIndexVarsOrdered, underivedBounds, indexVarToExprMap, iterators);
     taco_iassert(indexVarToExprMap.count(varToRecover));
     recoverySteps.push_back(VarDecl::make(indexVarToExprMap[varToRecover], recoveredValue));
+
+    // After we've recovered this index variable, some iterators are now
+    // accessible for use when declaring locator access variables. So, generate
+    // the accessors for those locator variables as part of the recovery process.
+    // This is necessary after a fuse transformation, for example: If we fuse
+    // two index variables (i, j) into f, then after we've generated the loop for
+    // f, all locate accessors for i and j are now available for use.
+    std::vector<Iterator> itersForVar;
+    for (auto& iters : iterators.levelIterators()) {
+      // Collect all level iterators that have locate and iterate over
+      // the recovered index variable.
+      if (iters.second.getIndexVar() == varToRecover && iters.second.hasLocate()) {
+        itersForVar.push_back(iters.second);
+      }
+    }
+    // Finally, declare all of the collected iterators' position access variables.
+    recoverySteps.push_back(this->declLocatePosVars(itersForVar));
+
     // place underived guard
     std::vector<ir::Expr> iterBounds = provGraph.deriveIterBounds(varToRecover, definedIndexVarsOrdered, underivedBounds, indexVarToExprMap, iterators);
     if (forallNeedsUnderivedGuards && underivedBounds.count(varToRecover) &&
@@ -2275,7 +2293,6 @@ Stmt LowererImpl::declLocatePosVars(vector<Iterator> locators) {
         if (locateIterator.isLeaf()) {
           break;
         }
-
         locateIterator = locateIterator.getChild();
       } while (accessibleIterators.contains(locateIterator));
     }

test/tests-scheduling.cpp

@@ -72,6 +72,56 @@ TEST(scheduling, splitIndexStmt) {
   ASSERT_TRUE(equals(a(i) = b(i), i2Forall.getStmt()));
 }
 
+TEST(scheduling, fuseDenseLoops) {
+  auto dim = 4;
+  Tensor<int> A("A", {dim, dim, dim}, {Dense, Dense, Dense});
+  Tensor<int> B("B", {dim, dim, dim}, {Dense, Dense, Dense});
+  Tensor<int> expected("expected", {dim, dim, dim}, {Dense, Dense, Dense});
+  IndexVar f("f"), g("g");
+  for (int i = 0; i < dim; i++) {
+    for (int j = 0; j < dim; j++) {
+      for (int k = 0; k < dim; k++) {
+        A.insert({i, j, k}, i + j + k);
+        B.insert({i, j, k}, i + j + k);
+        expected.insert({i, j, k}, 2 * (i + j + k));
+      }
+    }
+  }
+  A.pack();
+  B.pack();
+  expected.pack();
+
+  // Helper function to evaluate the target statement and verify the results.
+  // It takes in a function that applies some scheduling transforms to the
+  // input IndexStmt, and applies to the point-wise tensor addition below.
+  // The test is structured this way as TACO does its best to avoid re-compilation
+  // whenever possible. I.e. changing the stmt that a tensor is compiled with
+  // doesn't cause compilation to occur again.
+  auto testFn = [&](IndexStmt modifier(IndexStmt)) {
+    Tensor<int> C("C", {dim, dim, dim}, {Dense, Dense, Dense});
+    C(i, j, k) = A(i, j, k) + B(i, j, k);
+    auto stmt = C.getAssignment().concretize();
+    C.compile(modifier(stmt));
+    C.evaluate();
+    ASSERT_TRUE(equals(C, expected)) << endl << C << endl << expected << endl;
+  };
+
+  // First, a sanity check with no transformations.
+  testFn([](IndexStmt stmt) { return stmt; });
+  // Next, fuse the outer two loops. This tests the original bug in #355.
+  testFn([](IndexStmt stmt) {
+    IndexVar f("f");
+    return stmt.fuse(i, j, f);
+  });
+  // Lastly, fuse all of the loops into a single loop. This ensures that
+  // locators with a chain of ancestors have all of their dependencies
+  // generated in a valid ordering.
+  testFn([](IndexStmt stmt) {
+    IndexVar f("f"), g("g");
+    return stmt.fuse(i, j, f).fuse(f, k, g);
+  });
+}
+
 TEST(scheduling, lowerDenseMatrixMul) {
   Tensor<double> A("A", {4, 4}, {Dense, Dense});
   Tensor<double> B("B", {4, 4}, {Dense, Dense});

test/tests-transpose.cpp

@@ -76,3 +76,26 @@ TEST(DISABLED_lower, transpose3) {
                            &reason));
   ASSERT_EQ(error::expr_transposition, reason);
 }
+
+// denseIterationTranspose tests a dense iteration that contain a transposition
+// of one of the tensors.
+TEST(lower, denseIterationTranspose) {
+  auto dim = 4;
+  Tensor<int> A("A", {dim, dim, dim}, {Dense, Dense, Dense});
+  Tensor<int> B("B", {dim, dim, dim}, {Dense, Dense, Dense});
+  Tensor<int> C("C", {dim, dim, dim}, {Dense, Dense, Dense});
+  Tensor<int> expected("expected", {dim, dim, dim}, {Dense, Dense, Dense});
+  for (int i = 0; i < dim; i++) {
+    for (int j = 0; j < dim; j++) {
+      for (int k = 0; k < dim; k++) {
+        A.insert({i, j, k}, i + j + k);
+        B.insert({i, j, k}, i + j + k);
+        expected.insert({i, j, k}, 2 * (i + j + k));
+      }
+    }
+  }
+  A.pack(); B.pack(); expected.pack();
+  C(i, j, k) = A(i, j, k) + B(k, j, i);
+  C.evaluate();
+  ASSERT_TRUE(equals(C, expected));
+}