IterDomain resize for pad, cat, slice

CMakeLists.txt

@@ -353,6 +353,7 @@ if(BUILD_TEST)
   list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_gpu_outer_reduction.cpp)
   list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_loop_rotation.cpp)
   list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_gpu_shift.cpp)
+  list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_resize.cpp)
   list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_gpu_tensorcore.cpp)
   list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_gpu_matmul_sass.cpp)
   list(APPEND JIT_TEST_SRCS ${NVFUSER_ROOT}/test/test_gpu_view.cpp)

csrc/codegen.cpp

@@ -2774,6 +2774,41 @@ class CudaKernelGenerator : private OptOutConstDispatch {
     indent() << "NVFUSER_UPDATE_MAGIC_ZERO\n";
   }
 
+  void handle(const CatOp* cat) final {
+    auto out = gen(cat->output(0));
+
+    // Generate code like:
+    // if (consumer_idx < producer_0_extent) {
+    //   consumer[consumer_idx] = produce_0[producer_idx0];
+    // } else if (consumer_idx < producer_1_extent) {
+    //   consumer[consumer_idx] = produce_1[producer_idx1];
+    // } else if (consumer_idx < producer_2_extent) {
+    //   consumer[consumer_idx] = produce_2[producer_idx2];
+    // } else {
+    //   consumer[consumer_idx] = produce_3[producer_idx3];
+    // }
+
+    for (const auto i : c10::irange(cat->inputs().size())) {
+      auto inp = cat->input(i)->as<kir::TensorIndex>();
+      auto inp_str = gen(inp);
+      if (i < cat->inputs().size() - 1) {
+        if (i == 0) {
+          indent() << "if (";
+        } else {
+          indent() << "} else if (";
+        }
+        code_ << gen(cat->getPred(i)) << ") {\n";
+      } else {
+        // last case doesn't need to be predicated
+        indent() << "} else {\n";
+      }
+
+      indent() << kTab << out << " = " << gen(inp) << ";\n";
+    }
+
+    indent() << "}\n";
+  }
+
  private:
   std::stringstream code_;
   const kir::Kernel* kernel_;

csrc/compute_at_map.cpp

@@ -99,8 +99,8 @@ bool IterDomainGraph::exprsMap(
   }
 
   TORCH_INTERNAL_ASSERT(
-      first->isA<Merge>() || first->isA<Split>(),
-      "Merge and split are the only expressions supported through rfactor operations in compute at map, but found:\n",
+      first->isA<Merge>() || first->isA<Split>() || first->isA<Resize>(),
+      "Merge, split and resize are the only expressions supported through rfactor operations in compute at map, but found:\n",
       first->toString());
 
   auto first_ids = ir_utils::filterByType<IterDomain>(
@@ -176,6 +176,15 @@ bool IterDomainGraph::exprsMap(
     }
   }
 
+  if (first->isA<Resize>()) {
+    auto first_resize = first->as<Resize>();
+    auto second_resize = second->as<Resize>();
+    if (!first_resize->leftExpand()->sameAs(second_resize->leftExpand()) ||
+        !first_resize->rightExpand()->sameAs(second_resize->rightExpand())) {
+      return false;
+    }
+  }
+
   return true;
 }
 
@@ -211,6 +220,7 @@ void IterDomainGraph::mapThroughExpr(Expr* first, Expr* second, bool forward) {
   for (auto out_i : c10::irange(first_ids.size())) {
     exact_nodes_.mapEntries(first_ids[out_i], second_ids[out_i]);
     permissive_nodes_.mapEntries(first_ids[out_i], second_ids[out_i]);
+    permissive_resize_nodes_.mapEntries(first_ids[out_i], second_ids[out_i]);
   }
 }
 
@@ -407,6 +417,7 @@ void IterDomainGraph::build(Fusion* fusion) {
           auto id0 = *disjoint_set->begin();
           for (auto id1 : disjoint_set->vector()) {
             permissive_nodes_.mapEntries(id0, id1);
+            permissive_resize_nodes_.mapEntries(id0, id1);
             exact_nodes_.mapEntries(id0, id1);
             sibling_sets_.mapEntries(id0, id1);
           }
@@ -430,8 +441,22 @@ void IterDomainGraph::build(Fusion* fusion) {
         // Look for matching ID transformations in producer and consumer, replay
         // producer as consumer. We use the symmetric API of BestEffortReplay so
         // that both broadcast and squeeze are handled correctly.
+        //
+        // Note on the boolean flags: swizzles are skipped in both
+        // producer and consumer but resizes are not.
         const auto permissive_disjoint_sets =
-            BestEffortReplay::replayPasC(p_tv, c_tv, -1, pairwise_map)
+            BestEffortReplay::replayPasC(
+                p_tv, c_tv, -1, pairwise_map, true, true, false)
+                .getIterDomainEquivalence();
+
+        // Permissive-Resize map allows mappings of resize inputs and
+        // outputs
+        //
+        // Note on the boolean flags: swizzles and resizes are skipped
+        // in the permissive-resize map
+        const auto permissive_resize_disjoint_sets =
+            BestEffortReplay::replayPasC(
+                p_tv, c_tv, -1, pairwise_map, true, true, true)
                 .getIterDomainEquivalence();
 
         // For exact mapings do not map any broadcast dimensions to
@@ -483,16 +508,12 @@ void IterDomainGraph::build(Fusion* fusion) {
             for (auto j : c10::irange(i + 1, vec.size())) {
               auto id2 = vec[j];
               if (p_ids.count(id1) && c_ids.count(id2)) {
-                consumers_.at(id1).pushBack(id2);
-                producers_.at(id2).pushBack(id1);
                 if (idIsAComputeAtLeafDomain(id1, p_tv, c_tv) &&
                     idIsALeafDomain(id2, c_tv)) {
                   loop_nodes_.mapEntries(id1, id2);
                 }
               }
               if (c_ids.count(id1) && p_ids.count(id2)) {
-                producers_.at(id1).pushBack(id2);
-                consumers_.at(id2).pushBack(id1);
                 if (idIsAComputeAtLeafDomain(id2, p_tv, c_tv) &&
                     idIsALeafDomain(id1, c_tv)) {
                   loop_nodes_.mapEntries(id1, id2);
@@ -501,6 +522,31 @@ void IterDomainGraph::build(Fusion* fusion) {
             }
           }
         }
+
+        // Mostly the same as the above for the permissive map but
+        // nothing to do for the loop map.
+        // The producer and consumer maps are based on the most
+        // permissive mappings, so they are set using the
+        // permissive-resize mappings.
+        for (auto& dset : permissive_resize_disjoint_sets.disjointSets()) {
+          auto& vec = dset->vector();
+          for (auto i : c10::irange(vec.size())) {
+            auto id1 = vec[i];
+            permissive_resize_nodes_.mapEntries(id1, vec[0]);
+            mapMaybeSwizzleOp(permissive_resize_nodes_, id1);
+            for (auto j : c10::irange(i + 1, vec.size())) {
+              auto id2 = vec[j];
+              if (p_ids.count(id1) && c_ids.count(id2)) {
+                consumers_.at(id1).pushBack(id2);
+                producers_.at(id2).pushBack(id1);
+              }
+              if (c_ids.count(id1) && p_ids.count(id2)) {
+                producers_.at(id1).pushBack(id2);
+                consumers_.at(id2).pushBack(id1);
+              }
+            }
+          }
+        }
       }
     }
   }
@@ -561,7 +607,7 @@ void IterDomainGraph::build(Fusion* fusion) {
     for (auto expr : exprs) {
       auto rfactor_inp_ids = ir_utils::filterByType<IterDomain>(expr->inputs());
       TORCH_INTERNAL_ASSERT(
-          expr->isA<Split>() || expr->isA<Merge>(),
+          expr->isA<Split>() || expr->isA<Merge>() || expr->isA<Resize>(),
           "Wasn't expecting the expression type of:\n",
           expr->toString(),
           "\nto be an expression defined in an rfactor transformation.");
@@ -688,6 +734,7 @@ void IterDomainGraph::initializeId(
     bool is_rfactor_id,
     bool is_leaf_id) {
   permissive_nodes_.initializeSet(id);
+  permissive_resize_nodes_.initializeSet(id);
   exact_nodes_.initializeSet(id);
   if (is_leaf_id) {
     loop_nodes_.initializeSet(id);
@@ -1127,6 +1174,17 @@ void ComputeAtMap::buildConcreteIds() {
     auto concrete_id = computeConcreteId(first_id, IdMappingMode::LOOP);
     concrete_id_cache_[disjoint_set_shared_ptr] = concrete_id;
   }
+
+  for (const auto& disjoint_set_shared_ptr :
+       id_graph_.permissiveResizeNodes().disjointSets()) {
+    TORCH_INTERNAL_ASSERT(
+        disjoint_set_shared_ptr->vector().size(),
+        "Cannot compute concrete id of empty set.");
+    auto first_id = disjoint_set_shared_ptr->vector().front();
+    auto concrete_id =
+        computeConcreteId(first_id, IdMappingMode::PERMISSIVE_RESIZE);
+    concrete_id_cache_[disjoint_set_shared_ptr] = concrete_id;
+  }
 }
 
 bool ComputeAtMap::areExactExprs(Expr* expr_1, Expr* expr_2) {
@@ -1349,6 +1407,8 @@ std::string ComputeAtMap::toString() const {
   ss << "Loop map:\n" << idGraphNodesToString(*this, IdMappingMode::LOOP);
   ss << "Permissive map:\n"
      << idGraphNodesToString(*this, IdMappingMode::PERMISSIVE);
+  ss << "Permissive-Resize map:\n"
+     << idGraphNodesToString(*this, IdMappingMode::PERMISSIVE_RESIZE);
   ss << "Consumer maps:\n";
   for (auto key : getSortedKeys(id_graph_.consumers(), Statement::lessThan)) {
     auto consumers = id_graph_.consumers().at(key);
@@ -1408,6 +1468,8 @@ const DisjointSets<IterDomain*>& ComputeAtMap::getIdSets(
       return id_graph_.loopNodes();
     case IdMappingMode::PERMISSIVE:
       return id_graph_.permissiveNodes();
+    case IdMappingMode::PERMISSIVE_RESIZE:
+      return id_graph_.permissiveResizeNodes();
   }
   TORCH_INTERNAL_ASSERT(false, "Error with mapping mode provided.");
 }

csrc/compute_at_map.h

@@ -53,6 +53,10 @@ namespace nvfuser {
 //   Map all iteration domains
 //   Always contain root mappings (otherwise they could have been forwarded in
 //   broadcast)
+// IdMappingMode::PERMISSIVE_RESIZE
+//   Include everything in PERMISSIVE. Map also domains that are
+//   inputs and outputs of resize ops. Used for, e.g., propagating
+//   parallel types across those domains.
 // IdMappingMode::EXACT
 //   Don't map any broadcast axes to non-broadcast axes
 //   Do not forward through any broadcast IDs
@@ -79,6 +83,9 @@ class TORCH_CUDA_CU_API IterDomainGraph {
   const DisjointSets<IterDomain*>& loopNodes() const {
     return loop_nodes_;
   }
+  const DisjointSets<IterDomain*>& permissiveResizeNodes() const {
+    return permissive_resize_nodes_;
+  }
 
   // Consumers and producers is not symmetric like the other sets
   const std::unordered_map<IterDomain*, VectorOfUniqueEntries<IterDomain*>>&
@@ -132,8 +139,11 @@ class TORCH_CUDA_CU_API IterDomainGraph {
   DisjointSets<IterDomain*> exact_nodes_;
   DisjointSets<IterDomain*> almost_exact_nodes_;
   DisjointSets<IterDomain*> loop_nodes_;
+  DisjointSets<IterDomain*> permissive_resize_nodes_;
 
-  // Consumers and producers is not symmetric like the other sets
+  // Consumers and producers is not symmetric like the other sets.
+  // Mapping is based on the most permissive map, i.e., the
+  // permissive-resize map.
   std::unordered_map<IterDomain*, VectorOfUniqueEntries<IterDomain*>>
       consumers_;
   std::unordered_map<IterDomain*, VectorOfUniqueEntries<IterDomain*>>

csrc/contiguity.cpp

@@ -331,6 +331,48 @@ void OrderedIdInformation::handle(Swizzle2D* swizzle) {
   }
 }
 
+void OrderedIdInformation::handle(Resize* resize) {
+  // Find inputs in the active_ids_ vector
+  const auto in_it =
+      std::find(active_ids_.begin(), active_ids_.end(), resize->in());
+
+  if (in_it == active_ids_.end()) {
+    return;
+  }
+
+  auto in_pos = std::distance(active_ids_.begin(), in_it);
+
+  // Find inputs in the ordered transforms map
+  const auto in_ordered_it = consistently_ordered_ids_.find(resize->in());
+
+  bool in_ordered = in_ordered_it != consistently_ordered_ids_.end();
+
+  // Get root ids of the two inputs
+  const auto in_root_ids_it = id_to_root_ids_.find(resize->in());
+
+  TORCH_INTERNAL_ASSERT(
+      in_root_ids_it != id_to_root_ids_.end(),
+      "Error replaying transforms in contiguous ID checker.");
+
+  const auto& in_root_ids = in_root_ids_it->second;
+
+  // Update map for outputs
+  // Remove inputs from the active_ids_ and insert the output ID
+  active_ids_[in_pos] = resize->out();
+
+  // Not completely certain, but propagating these properties should e
+  // fine
+  if (in_ordered) {
+    consistently_ordered_ids_.emplace(resize->out());
+  }
+
+  if (exclusivelyConsumesRoots(resize->in())) {
+    exclusively_consumes_roots_.emplace(resize->out());
+  }
+
+  id_to_root_ids_[resize->out()] = in_root_ids;
+}
+
 NonDivisibleSplitDependencies::NonDivisibleSplitDependencies(
     // TODO: Revisit reduction rfactor axes and propagation. Should probably use
     // ca_map to propogate non divisibility dependencies across exact map. Still
@@ -500,6 +542,19 @@ void ContigIDs::build(const std::vector<IterDomain*>& ids) {
         {root_domain_.begin(), root_domain_.end()},
         {ids.begin(), ids.end()});
     for (auto expr : exprs) {
+      if (auto resize = dynamic_cast<Resize*>(expr)) {
+        resize_deps_.insert(resize->out());
+      } else {
+        if (std::any_of(
+                expr->inputs().begin(), expr->inputs().end(), [&](Val* inp) {
+                  return inp->isA<IterDomain>() &&
+                      resize_deps_.count(inp->as<IterDomain>());
+                })) {
+          for (auto out : ir_utils::filterByType<IterDomain>(expr->outputs())) {
+            resize_deps_.insert(out);
+          }
+        }
+      }
       handle(expr);
     }
   }
@@ -576,6 +631,12 @@ void ContigIDs::handle(Merge* merge) {
     return;
   }
 
+  // Don't allow contig indexing after resize as we need traverse back
+  // at least to direct outputs of resize ops
+  if (resize_deps_.count(merge->out())) {
+    return;
+  }
+
   // All broadcasting
   if (last_root == nullptr) {
     return;

csrc/contiguity.h

@@ -62,6 +62,8 @@ class OrderedIdInformation : public OptInDispatch {
 
   void handle(Swizzle2D* swizzle) override;
 
+  void handle(Resize* resize) override;
+
   // Track which root ids were used to generate each iter domain
   std::unordered_map<IterDomain*, VectorOfUniqueEntries<IterDomain*>>
       id_to_root_ids_;
@@ -255,6 +257,8 @@ class ContigIDs : public OptInDispatch {
   // cases, depending on specific swizzle type and axes.
   void handle(Swizzle2D* swizzle) override {}
 
+  void handle(Resize* resize) override {}
+
   IterDomain* getCAIndexConcreteId(IterDomain* id) const;
 
   //! True if an ID is indexable.
@@ -307,6 +311,9 @@ class ContigIDs : public OptInDispatch {
   std::unique_ptr<const OrderedIdInformation> consistent_transform_info_;
 
   NonDivisibleSplitDependencies non_divisible_id_info_;
+
+  //! IDs that depend on resize output IDs
+  std::unordered_set<IterDomain*> resize_deps_;
 };
 
 } // namespace nvfuser