[RELAY][FUSION] Enhance fusion rule that starts from elemwise and broadcast (apache#2932)

* [relay][bugfix] fuse injective to elemwise and broadcast

* enhance fusion for prarllel injectiveOD

* check if tensor in schedule

* fix codegen

* fix lint

* update

* lint

Author: zhiics

include/tvm/schedule.h

@@ -551,6 +551,22 @@ class ScheduleNode : public Node {
   /*! \brief Invalidate temp cache. */
   void InvalidateCache();
 
+  /*!
+   * \brief Check if the schedule contains an Operation.
+   * \param op The candidate Operation.
+   * \return true if the schedule has the Operation. Otherwise, false.
+   */
+  EXPORT bool Contain(const Operation& op) const;
+
+  /*!
+   * \brief Check if the schedule contains a Tensor.
+   * \param tensor The candidate tensor.
+   * \return true if the schedule has the tensor. Otherwise, false.
+   */
+  EXPORT bool Contain(const Tensor& tensor) const {
+    return Contain(tensor->op);
+  }
+
   /*!
    * \brief Create a schedule for array of ops(and their dependencies).
    * \param ops The ops to be scheduled.

src/relay/backend/compile_engine.cc

@@ -127,7 +127,9 @@ class ScheduleGetter :
       schedule =
           fschedule[master_op_](master_attrs_, tensor_outs, target_);
       for (const auto& scalar : scalars_) {
-        schedule[scalar].compute_inline();
+        if (schedule->Contain(scalar)) {
+          schedule[scalar].compute_inline();
+        }
       }
     }
     return std::make_pair(schedule, cfunc);

src/relay/pass/fuse_ops.cc

@@ -715,10 +715,13 @@ class GraphPartitioner {
           // The final terminal node can already be fused to a OutEWiseFusable group.
           auto fcond = [](OpPatternKind kind, bool is_sink) {
             if (!is_sink) {
-              return kind <= kBroadcast;
+              // Elemwise, broadcast, and injective ops on the parallel branches
+              // are allowed be fused to the elemwise/broadcast master.
+              return kind <= kInjective;
             } else {
               return (kind <= kBroadcast ||
                       kind == kCommReduce ||
+                      kind == kInjective ||
                       kind == kOutEWiseFusable);
             }
           };

src/schedule/schedule_lang.cc

@@ -712,6 +712,10 @@ void ScheduleNode::InitCache() {
   CHECK_EQ(op2stage_cache_.size(), stages.size());
 }
 
+bool ScheduleNode::Contain(const Operation& op) const {
+  return stage_map.find(op) != stage_map.end();
+}
+
 Schedule ScheduleNode::make(Array<Operation> ops) {
   auto n = make_node<ScheduleNode>();
   Schedule sch(n);

tests/python/relay/test_pass_fuse_ops.py

@@ -23,13 +23,15 @@ def before():
         x = relay.var("x", shape=(10, 20))
         y = relay.add(x, relay.const(1, "float32"))
         z = relay.exp(y)
-        return relay.Function([x], z)
+        w = relay.squeeze(z)
+        return relay.Function([x], w)
 
     def expected():
         x = relay.var("p", shape=(10, 20))
         y = relay.add(x, relay.const(1, "float32"))
         z = relay.exp(y)
-        f1 = relay.Function([x], z)
+        w = relay.squeeze(z)
+        f1 = relay.Function([x], w)
         x = relay.var("x", shape=(10, 20))
         y = relay.Call(f1, [x])
         return relay.Function([x], y)
@@ -503,6 +505,38 @@ def expected(dshape):
     assert relay.ir_pass.alpha_equal(zz, after)
 
 
+def test_fuse_parallel_injective():
+    """Test fusing parallel injective ops to an elemwise op."""
+    def before():
+        x = relay.var("x", shape=(10, 20))
+        y = relay.add(x, relay.const(1, "float32"))
+        z = relay.squeeze(y)
+        u = relay.transpose(y, axes=[0, 1])
+        w = relay.left_shift(z, u)
+        return relay.Function([x], w)
+
+    def expected():
+        x = relay.var("p", shape=(10, 20))
+        y = relay.add(x, relay.const(1, "float32"))
+        z = relay.squeeze(y)
+        u = relay.transpose(y, axes=[0, 1])
+        w = relay.left_shift(z, u)
+        f1 = relay.Function([x], w)
+        x = relay.var("x", shape=(10, 20))
+        y = relay.Call(f1, [x])
+        return relay.Function([x], y)
+
+    z = before()
+    z = relay.ir_pass.infer_type(z)
+    zz = relay.ir_pass.fuse_ops(z, opt_level=0)
+    assert not relay.ir_pass.free_vars(zz)
+    zz = relay.ir_pass.fuse_ops(z, opt_level=2)
+    zz = relay.ir_pass.infer_type(zz)
+    assert not relay.ir_pass.free_vars(zz)
+    after = relay.ir_pass.infer_type(expected())
+    assert relay.ir_pass.alpha_equal(zz, after)
+
+
 if __name__ == "__main__":
     test_fuse_simple()
     test_conv2d_fuse()
@@ -515,3 +549,4 @@ def expected(dshape):
     test_tuple_intermediate()
     test_tuple_consecutive()
     test_inception_like()
+    test_fuse_parallel_injective()