Revert "Move ReluQuantFusion to Level2 for CPU EP only (#21329)"

This reverts commit 22d4d82.
microsoft · Oct 29, 2024 · afe2e76 · afe2e76
1 parent 7f1dd50
commit afe2e76
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Showing 3 changed files with 2 additions and 55 deletions.
diff --git a/onnxruntime/core/optimizer/graph_transformer_utils.cc b/onnxruntime/core/optimizer/graph_transformer_utils.cc
@@ -134,12 +134,12 @@ InlinedVector<std::unique_ptr<RewriteRule>> GenerateRewriteRules(
       rules.push_back(std::make_unique<ConvBNFusion>());
       rules.push_back(std::make_unique<PadFusion>());
       rules.push_back(std::make_unique<MatmulBNFusion>());
+      rules.push_back(std::make_unique<ReluQuantFusion>());
       rules.push_back(std::make_unique<LabelEncoderFusion>());
       break;
 
     case TransformerLevel::Level2:
       rules.push_back(std::make_unique<ClipQuantFusion>());
-      rules.push_back(std::make_unique<ReluQuantFusion>());
       rules.push_back(std::make_unique<GemmTransposeFusion>());
       break;
 

diff --git a/onnxruntime/core/optimizer/qdq_transformer/relu_quantizelinear.cc b/onnxruntime/core/optimizer/qdq_transformer/relu_quantizelinear.cc
@@ -13,15 +13,13 @@ namespace onnxruntime {
 
 bool ReluQuantFusion::SatisfyCondition(const Graph& graph, const Node& node, const logging::Logger& /*logger*/) const {
   if (!graph_utils::IsSupportedOptypeVersionAndDomain(node, "Relu", {6, 13, 14}) ||
-      !graph_utils::IsSupportedProvider(node, {kCpuExecutionProvider}) ||
       !optimizer_utils::CheckOutputEdges(graph, node, 1)) {
     return false;
   }
 
   // if Relu is followed by QuantizeLinear, it can be fused into QuantizeLinear potentially
   const auto& next_node = *node.OutputNodesBegin();
-  if (!graph_utils::IsSupportedProvider(next_node, {kCpuExecutionProvider}) ||
-      !QDQ::MatchQNode(next_node)) {
+  if (!QDQ::MatchQNode(next_node)) {
     return false;
   }
 

diff --git a/onnxruntime/test/optimizer/qdq_transformer_test.cc b/onnxruntime/test/optimizer/qdq_transformer_test.cc
@@ -3101,57 +3101,6 @@ TEST(QDQTransformerTests, Clip) {
   }
 }
 
-// Test that the ReluQuantFusion transformer only runs for optimization level >= 2.
-TEST(QDQTransformerTests, ReluQuantFusion_Level2Only) {
-  auto test_case = [&](TransformerLevel opt_level, int8_t zp) {
-    auto build_test_case = [&](ModelTestBuilder& builder) {
-      auto* input_arg = builder.MakeInput<int8_t>({1, 2, 2, 2},
-                                                  {-4, -3, -2, 0, 1, 2, 3, 4});
-      auto* output_arg = builder.MakeOutput();
-
-      // add DQ
-      auto* dq_output = builder.MakeIntermediate();
-      builder.AddDequantizeLinearNode<int8_t>(input_arg, 1.0f, zp, dq_output);
-
-      // add Relu
-      auto* relu_output = builder.MakeIntermediate();
-      builder.AddNode("Relu", {dq_output}, {relu_output});
-
-      // add Q + DQ
-      auto* q_output = builder.MakeIntermediate();
-      builder.AddQuantizeLinearNode<int8_t>(relu_output, 1.0f, zp, q_output);
-      builder.AddDequantizeLinearNode<int8_t>(q_output, 1.0f, zp, output_arg);
-    };
-
-    auto check_relu_graph = [&](InferenceSessionWrapper& session) {
-      auto op_to_count = CountOpsInGraph(session.GetGraph());
-      const QDQOpKeys qdq_keys = GetQDQOpKeys(false);
-      // Only fuse relu into Q if level >= 2 and zero_point == -128 for int8.
-      // Level1 graph:   input -> DQ -> Relu -> Q -> DQ -> output
-      // Level2+ graph: input -> DQ -> output (QuantReluFusion + QDQFinalCleanupTransformer transformers)
-      const bool fuse_relu = (zp == -128) &&
-                             (opt_level == TransformerLevel::Level2 || opt_level == TransformerLevel::Level3);
-      EXPECT_EQ(op_to_count[qdq_keys.quantize_linear], fuse_relu ? 0 : 1);
-      EXPECT_EQ(op_to_count["Relu"], fuse_relu ? 0 : 1);
-      EXPECT_EQ(op_to_count[qdq_keys.dequantize_linear], fuse_relu ? 1 : 2);
-    };
-
-    constexpr float epsilon = std::numeric_limits<float>::epsilon();
-
-    TransformerTester(build_test_case, check_relu_graph,
-                      TransformerLevel::Default,
-                      opt_level,
-                      18,
-                      epsilon,
-                      epsilon);
-  };
-
-  test_case(TransformerLevel::Level1, -128);  // Will not fuse Relu into QuantizeLinear due to level1 opt.
-  test_case(TransformerLevel::Level2, -128);  // Will fuse Relu into QuantizeLinear.
-  test_case(TransformerLevel::Level3, -128);  // Will fuse Relu into QuantizeLinear.
-  test_case(TransformerLevel::Level3, 0);     // Will not fuse Relu into QuantizeLinear due to zero-point != -128
-}
-
 TEST(QDQTransformerTests, Concat) {
   auto test_case = [&](const std::vector<std::vector<int64_t>>& input_shapes,
                        int64_t axis,