Merge pull request #5154 from tensor-tang/merge

refine check macro

paddle/gserver/layers/MKLDNNBatchNormLayer.cpp

@@ -216,17 +216,13 @@ void MKLDNNBatchNormLayer::resetFwdPD(
   }
   auto fwdDesc = bn_fwd::desc(pk, in->getMemoryDesc(), EPS, flags_);
   pd.reset(new bn_fwd::primitive_desc(fwdDesc, engine_));
-  // TODO(TJ): use check macro
-  CHECK(out);
-  CHECK(out->getPrimitiveDesc() == pd->dst_primitive_desc());
+  CHECK_PRIMITIVE_DESC_EQ(out, pd->dst_primitive_desc());
   if (wgt) {
-    CHECK(wgt->getPrimitiveDesc() == pd->weights_primitive_desc());
+    CHECK_PRIMITIVE_DESC_EQ(wgt, pd->weights_primitive_desc());
   }
   if (passType_ != PASS_TEST || useGlobalStats_) {
-    CHECK(mean_);
-    CHECK(mean_->getPrimitiveDesc() == pd->mean_primitive_desc());
-    CHECK(var_);
-    CHECK(var_->getPrimitiveDesc() == pd->variance_primitive_desc());
+    CHECK_PRIMITIVE_DESC_EQ(mean_, pd->mean_primitive_desc());
+    CHECK_PRIMITIVE_DESC_EQ(var_, pd->variance_primitive_desc());
   }
 }
 
@@ -283,19 +279,14 @@ void MKLDNNBatchNormLayer::resetBwdPD(
   if (in == nullptr) {
     return;
   }
-  CHECK(out);
-  CHECK(out->getPrimitiveDesc() == in->getPrimitiveDesc());
+  CHECK_PRIMITIVE_DESC_EQ(out, in->getPrimitiveDesc());
   auto md = in->getMemoryDesc();
   auto bwdDesc = bn_bwd::desc(prop_kind::backward, md, md, EPS, flags_);
   pd.reset(new bn_bwd::primitive_desc(bwdDesc, engine_, *fwdPD_));
-  // TODO(TJ): use check macro
-  CHECK(wgt);
-  CHECK(wgt->getPrimitiveDesc() == pd->diff_weights_primitive_desc());
   CHECK(pd->weights_primitive_desc() == fwdPD_->weights_primitive_desc());
-  CHECK(mean_);
-  CHECK(mean_->getPrimitiveDesc() == pd->mean_primitive_desc());
-  CHECK(var_);
-  CHECK(var_->getPrimitiveDesc() == pd->variance_primitive_desc());
+  CHECK_PRIMITIVE_DESC_EQ(wgt, pd->diff_weights_primitive_desc());
+  CHECK_PRIMITIVE_DESC_EQ(mean_, pd->mean_primitive_desc());
+  CHECK_PRIMITIVE_DESC_EQ(var_, pd->variance_primitive_desc());
 }
 
 void MKLDNNBatchNormLayer::resetBwdPipeline(

paddle/gserver/layers/MKLDNNConvLayer.cpp

@@ -262,12 +262,15 @@ void MKLDNNConvLayer::resetBwdWgtPD(
                                             padR,
                                             padKind);
   pd.reset(new conv_bwdWgt::primitive_desc(bwdWgtDesc, engine_, *fwdPD_));
-  CHECK(pd->src_primitive_desc() == inVal_->getPrimitiveDesc())
-      << "primitive desc of in value should equal";
-  CHECK(pd->diff_dst_primitive_desc() == outVal_->getPrimitiveDesc())
-      << "primitive desc of out grad should equal the out value";
-  CHECK(pd->diff_weights_primitive_desc() == wgtVal_->getPrimitiveDesc())
-      << "primitive desc of weight grad should equal the weight value";
+  CHECK_PRIMITIVE_DESC_EQ(inVal_, pd->src_primitive_desc());
+  CHECK_PRIMITIVE_DESC_EQ(
+      outVal_,
+      pd->diff_dst_primitive_desc(),
+      "primitive desc of out value and grad should be equal");
+  CHECK_PRIMITIVE_DESC_EQ(
+      wgtVal_,
+      pd->diff_weights_primitive_desc(),
+      "primitive desc of weight value and grad should be equal");
 }
 
 void MKLDNNConvLayer::resetBwdDataPD(
@@ -292,10 +295,14 @@ void MKLDNNConvLayer::resetBwdDataPD(
                                         padR,
                                         padding_kind::zero);
   pd.reset(new conv_bwdData::primitive_desc(bwdDataDesc, engine_, *fwdPD_));
-  CHECK(pd->diff_src_primitive_desc() == inVal_->getPrimitiveDesc())
-      << "primitive desc of in grad should equal the in value";
-  CHECK(pd->diff_dst_primitive_desc() == outVal_->getPrimitiveDesc())
-      << "primitive desc of out grad should equal";
+  CHECK_PRIMITIVE_DESC_EQ(
+      inVal_,
+      pd->diff_src_primitive_desc(),
+      "primitive desc of in value and grad should be equal");
+  CHECK_PRIMITIVE_DESC_EQ(
+      outVal_,
+      pd->diff_dst_primitive_desc(),
+      "primitive desc of out value and grad should be equal");
 }
 
 void MKLDNNConvLayer::resetBwdBuffers(
@@ -310,17 +317,20 @@ void MKLDNNConvLayer::resetBwdBuffers(
 
   resetWithMatrix(
       wgt, weight_->getWGrad(), wgtPD->diff_weights_primitive_desc());
-  CHECK(wgtVal_ != nullptr &&
-        wgt->getPrimitiveDesc() == wgtVal_->getPrimitiveDesc())
-      << "primitive desc of weight grad and value should be equal";
+  CHECK_PRIMITIVE_DESC_EQ(
+      wgtVal_,
+      wgt->getPrimitiveDesc(),
+      "primitive desc of weight grad and value should be equal");
 
   bias = nullptr;
   if (biases_ && biases_->getWGrad()) {
     resetWithMatrix(
         bias, biases_->getWGrad(), wgtPD->diff_bias_primitive_desc());
-    CHECK(bias && biasVal_ &&
-          bias->getPrimitiveDesc() == biasVal_->getPrimitiveDesc())
-        << "primitive desc of bias grad should equal the bias value";
+    CHECK(bias);
+    CHECK_PRIMITIVE_DESC_EQ(
+        biasVal_,
+        bias->getPrimitiveDesc(),
+        "primitive desc of bias grad and value should be equal");
   }
 
   if (dataPD == nullptr) {

paddle/gserver/layers/MKLDNNLayer.cpp

@@ -235,8 +235,7 @@ void MKLDNNLayer::resetInGrad(MKLDNNMatrixPtr& in,
   in = MKLDNNMatrix::create(intPD, inMat);
   Argument& arg = input->getOutput(this->getName());
   arg.grad = std::dynamic_pointer_cast<Matrix>(in);
-  CHECK(inVal_);
-  CHECK(inVal_->getPrimitiveDesc() == intPD) << "the primitive desc must equal";
+  CHECK_PRIMITIVE_DESC_EQ(inVal_, intPD);
   if (inputIsOnlyMKLDNN()) {
     return;
   }
@@ -250,8 +249,7 @@ void MKLDNNLayer::resetInGrad(MKLDNNMatrixPtr& in,
   CHECK(extInVal_ != nullptr && isPaddleFormat(extInVal_->getFormat()))
       << "should have external input value and the format must be nchw(nc)";
   extInGrad_ = MKLDNNMatrix::create(extInVal_->getPrimitiveDesc(), inMat);
-  CHECK(inVal_ != nullptr && inVal_->getPrimitiveDesc() == intPD)
-      << "should have internal input value and primitive desc must equal";
+  CHECK_PRIMITIVE_DESC_EQ(inVal_, intPD);
   in = MKLDNNMatrix::create(intPD);
   cvtInGrad_ = MKLDNNMatrix::createReorder(in, extInGrad_);
   CHECK(cvtInGrad_);
@@ -277,8 +275,7 @@ void MKLDNNLayer::resetOutGrad(MKLDNNMatrixPtr& out,
   CHECK(extOutVal_ != nullptr && isPaddleFormat(extOutVal_->getFormat()))
       << "should have external output value and the format must be nchw(nc)";
   extOutGrad_ = MKLDNNMatrix::create(extOutVal_->getPrimitiveDesc(), outMat);
-  CHECK(outVal_ != nullptr && outVal_->getPrimitiveDesc() == intPD)
-      << "should have internal output value and primitive desc must equal";
+  CHECK_PRIMITIVE_DESC_EQ(outVal_, intPD);
   out = MKLDNNMatrix::create(intPD);
   cvtOutGrad_ = MKLDNNMatrix::createReorder(extOutGrad_, out);
   CHECK(cvtOutGrad_);

paddle/math/MKLDNNMatrix.h

@@ -24,6 +24,12 @@ namespace paddle {
 class MKLDNNMatrix;
 typedef std::shared_ptr<MKLDNNMatrix> MKLDNNMatrixPtr;
 
+#define CHECK_PRIMITIVE_DESC_EQ(MAT, PD, ...)                        \
+  CHECK(MAT) << " can not be empty.";                                \
+  CHECK(MAT->getPrimitiveDesc() == PD)                               \
+      << #MAT "->getPrimitiveDesc() and " #PD " should be equal.\n " \
+      << "" __VA_ARGS__;
+
 /**
  * @brief MKLDNN Matrix.
  *