Merge pull request #32486 from Intel-tensorflow:rgomathi/mkl_quantize…

…_minfirst PiperOrigin-RevId: 280006380 Change-Id: Iaa6feaff763eafe31bdf559b3cf4b1866dc1669b
tensorflow · Nov 12, 2019 · d6bbe8c · d6bbe8c
2 parents 65016d4 + 1b8b71e
commit d6bbe8c
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Showing 5 changed files with 455 additions and 42 deletions.
diff --git a/tensorflow/core/graph/mkl_layout_pass.cc b/tensorflow/core/graph/mkl_layout_pass.cc
@@ -1576,10 +1576,13 @@ rinfo_.push_back({csinfo_.tanh_grad,
     int axis = -1;
     string mode_string;
     string round_mode_string;
+    DataType type;
     TryGetNodeAttr(n->def(), "narrow_range", &narrow_range);
     TryGetNodeAttr(n->def(), "axis", &axis);
     TF_CHECK_OK(GetNodeAttr(n->def(), "mode", &mode_string));
     TF_CHECK_OK(GetNodeAttr(n->def(), "round_mode", &round_mode_string));
+    TF_CHECK_OK(GetNodeAttr(n->def(), "T", &type));
+
     if (narrow_range) {
       VLOG(1) << "QuantizeOpRewrite: narrow range is enabled for quantization."
               << "This case is not optimized by Intel MKL, "
@@ -1593,8 +1596,9 @@ rinfo_.push_back({csinfo_.tanh_grad,
               << "thus using Eigen op for Quantize op ";
       return false;
     }
-    if (mode_string != "SCALED" || round_mode_string != "HALF_TO_EVEN") {
-      VLOG(1) << "QuantizeOpRewrite: Mode is not SCALED and/or"
+    if (!((mode_string == "SCALED" && round_mode_string == "HALF_TO_EVEN") ||
+          (mode_string == "MIN_FIRST"))) {
+      VLOG(1) << "QuantizeOpRewrite: Mode is not SCALED or MIN_FIRST and/or"
               << "rounding mode is not HALF_TO_EVEN. "
               << "This case is not optimized by Intel MKL, thus using Eigen op"
               << "for Quantize op ";
@@ -1608,6 +1612,14 @@ rinfo_.push_back({csinfo_.tanh_grad,
 
       return false;
     }
+    if (mode_string == "MIN_FIRST") {
+      if (type != DT_QUINT8) {
+        VLOG(1) << "QuantizeOpRewrite: For MIN_FIRST mode the data type is "
+                << "not DT_UINT8. This case is not optimized by Intel MKL, "
+                << "thus using Eigen op for Quantize op ";
+        return false;
+      }
+    }
     return true;
   }
   static bool MaxpoolGradRewrite(const Node* n) {
@@ -1849,6 +1861,7 @@ rinfo_.push_back({csinfo_.tanh_grad,
   // NOTE: names are alphabetically sorted.
   static void CopyAttrsAll(const Node* orig_node, NodeBuilder* nb,
                            bool change_format = false);
+
   static void CopyAttrsConv(const Node* orig_node, NodeBuilder* nb,
                             bool change_format = false);
   static void CopyAttrsConv2DDepthwiseCheckConstFilter(

diff --git a/tensorflow/core/graph/mkl_layout_pass_test.cc b/tensorflow/core/graph/mkl_layout_pass_test.cc
@@ -1470,7 +1470,7 @@ TEST_F(MklLayoutPassTest, NodeRewrite_QuantizeV2Op_Negative_ConstInp) {
             "A->D;B->D:1;C->D:2;D->E");
 }
 
-TEST_F(MklLayoutPassTest, NodeRewrite_QuantizeV2Op_Negative_MinFirst) {
+TEST_F(MklLayoutPassTest, NodeRewrite_QuantizeV2Op_MinFirst) {
   InitGraph(
       "node { name: 'A' op: 'Input' } "
       "node { name: 'B' op: 'Const' "
@@ -1491,8 +1491,11 @@ TEST_F(MklLayoutPassTest, NodeRewrite_QuantizeV2Op_Negative_MinFirst) {
       "node { name: 'E' op: 'Zeta' attr { key: 'T' value { type: DT_QUINT8 } }"
       " input: ['D'] }");
   EXPECT_EQ(DoMklLayoutOptimizationPass(),
-            "A(Input);B(Const);C(Const);D(QuantizeV2);E(Zeta)|"
-            "A->D;B->D:1;C->D:2;D->E");
+            "A(Input);B(Const);C(Const);D(_MklQuantizeV2);DMT/_0(Const);DMT/"
+            "_1(Const);DMT/_2(Const);E(Zeta)|"
+            "A->D;A:control->DMT/_0:control;A:control->DMT/"
+            "_1:control;A:control->DMT/_2:control;B->D:1;C->D:2;D->E;DMT/"
+            "_0->D:3;DMT/_1->D:4;DMT/_2->D:5");
 }
 
 TEST_F(MklLayoutPassTest, NodeRewrite_QuantizeV2Op_Negative_NarrowRange_True) {