paddle/fluid/ modify MKLDNN [fluid_ops] - part (#74536)

Author: co63oc

paddle/fluid/framework/executor.cc

@@ -607,7 +607,7 @@ void Executor::EnableONEDNN(const ProgramDesc& program) {
   }
 #else
   LOG(WARNING)
-      << "'MKLDNN' is not supported, Please re-compile with WITH_ONEDNN option";
+      << "'ONEDNN' is not supported, Please re-compile with WITH_ONEDNN option";
 #endif
 }
 }  // namespace paddle::framework

paddle/fluid/framework/ir/conv_bn_fuse_pass.h

@@ -23,7 +23,7 @@ namespace framework {
 namespace ir {
 
 /*
- * Fuse the Conv and BatchNorm to a ConvBNMKLDNNOp.
+ * Fuse the Conv and BatchNorm to a ConvBNONEDNNOp.
  */
 
 class ConvBNFusePass : public FusePassBase {

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -3281,7 +3281,7 @@ PDNode *patterns::Bloat16Ops::operator()() {
   return op;
 }
 
-PDNode *patterns::MKLDNNInPlace::operator()() {
+PDNode *patterns::ONEDNNInPlace::operator()() {
   const std::unordered_set<std::string> &supported_op_types = {
       "abs", "gelu", "leaky_relu", "relu", "softmax", "sqrt", "swish", "tanh"};
 

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -1771,8 +1771,8 @@ struct Bloat16Ops : public PatternBase {
 
 // Pattern used for enforcing inplace computation for in-place computation
 // supporting DNNL ops. softmax, batch_norm and layer_norm
-struct MKLDNNInPlace : public PatternBase {
-  MKLDNNInPlace(PDPattern* pattern, const std::string& name_scope)
+struct ONEDNNInPlace : public PatternBase {
+  ONEDNNInPlace(PDPattern* pattern, const std::string& name_scope)
       : PatternBase(pattern, name_scope, "mkldnn_inplace") {}
   PDNode* operator()();
 

paddle/fluid/framework/ir/onednn/matmul_elementwise_add_onednn_fuse_pass.cc

@@ -23,7 +23,7 @@ namespace paddle::framework::ir {
 
 using string::PrettyLogDetail;
 
-void MatmulElementwiseAddMKLDNNFusePass::ApplyImpl(Graph* graph) const {
+void MatmulElementwiseAddONEDNNFusePass::ApplyImpl(Graph* graph) const {
   auto matmul_types = {"fused_matmul", "matmul", "matmul_v2"};
   auto matmul_as_x = {true, false};
 
@@ -33,7 +33,7 @@ void MatmulElementwiseAddMKLDNNFusePass::ApplyImpl(Graph* graph) const {
     }
 }
 
-void MatmulElementwiseAddMKLDNNFusePass::FuseMatmulElementwiseAdd(
+void MatmulElementwiseAddONEDNNFusePass::FuseMatmulElementwiseAdd(
     Graph* graph, const std::string& matmul_type, bool matmul_as_x) const {
   const std::string fusion_mode = matmul_as_x ? "x" : "y";
   const auto name_scope = matmul_type + "_elementwise_add_as_" + fusion_mode;
@@ -87,7 +87,7 @@ void MatmulElementwiseAddMKLDNNFusePass::FuseMatmulElementwiseAdd(
   }
 }
 
-MatmulElementwiseAddMKLDNNFusePass::MatmulElementwiseAddMKLDNNFusePass() {
+MatmulElementwiseAddONEDNNFusePass::MatmulElementwiseAddONEDNNFusePass() {
   AddOpCompat(OpCompat("matmul"))
       .AddInput("X")
       .IsTensor()
@@ -164,7 +164,7 @@ MatmulElementwiseAddMKLDNNFusePass::MatmulElementwiseAddMKLDNNFusePass() {
 }  // namespace paddle::framework::ir
 
 REGISTER_PASS(matmul_elementwise_add_onednn_fuse_pass,
-              paddle::framework::ir::MatmulElementwiseAddMKLDNNFusePass);
+              paddle::framework::ir::MatmulElementwiseAddONEDNNFusePass);
 REGISTER_PASS_CAPABILITY(matmul_elementwise_add_onednn_fuse_pass)
     .AddCombination(
         paddle::framework::compatible::OpVersionComparatorCombination()

paddle/fluid/framework/ir/onednn/matmul_elementwise_add_onednn_fuse_pass.h

@@ -21,10 +21,10 @@ namespace paddle {
 namespace framework {
 namespace ir {
 
-class MatmulElementwiseAddMKLDNNFusePass : public FusePassBase {
+class MatmulElementwiseAddONEDNNFusePass : public FusePassBase {
  public:
-  MatmulElementwiseAddMKLDNNFusePass();
-  virtual ~MatmulElementwiseAddMKLDNNFusePass() {}
+  MatmulElementwiseAddONEDNNFusePass();
+  virtual ~MatmulElementwiseAddONEDNNFusePass() {}
 
  protected:
   void ApplyImpl(Graph* graph) const;

paddle/fluid/framework/op_kernel_type.h

@@ -107,7 +107,7 @@ inline bool NeedTransformLayout(const DataLayout& l, const DataLayout& r) {
   bool ret =
       (l != DataLayout::kAnyLayout && r != DataLayout::kAnyLayout && l != r);
 #ifdef PADDLE_WITH_DNNL
-  // Layout transform needed for either non-MKLDNN to OneDNN or vice versa
+  // Layout transform needed for either non-ONEDNN to OneDNN or vice versa
   ret |= (l != DataLayout::ONEDNN && r == DataLayout::ONEDNN);
   ret |= (l == DataLayout::ONEDNN && r != DataLayout::ONEDNN);
 #endif

paddle/fluid/pir/transforms/onednn/cpu_bfloat16_type_placement_pass.cc

@@ -135,7 +135,7 @@ class CpuBfloat16TypePattern : public pir::RewritePattern {
         } else {
           PADDLE_THROW(common::errors::Unimplemented(
               "result type is not DenseTensorType or VectorType, please close "
-              "MKLDNNBf16"));
+              "ONEDNNBf16"));
         }
       }
     }

paddle/fluid/pir/transforms/onednn/depthwise_conv_onednn_pass.cc

@@ -80,9 +80,9 @@ class DepthwiseConvPattern : public paddle::drr::DrrPatternBase {
   }
 };
 
-class DepthwiseConvMKLDNNPass : public pir::PatternRewritePass {
+class DepthwiseConvONEDNNPass : public pir::PatternRewritePass {
  public:
-  DepthwiseConvMKLDNNPass()
+  DepthwiseConvONEDNNPass()
       : pir::PatternRewritePass("depthwise_conv_onednn_pass", 2) {}
 
   pir::RewritePatternSet InitializePatterns(pir::IrContext *context) override {
@@ -97,11 +97,11 @@ class DepthwiseConvMKLDNNPass : public pir::PatternRewritePass {
 
 namespace pir {
 
-std::unique_ptr<Pass> CreateDepthwiseConvMKLDNNPass() {
+std::unique_ptr<Pass> CreateDepthwiseConvONEDNNPass() {
   // pd_op.depthwise_conv  -> pd_op.conv2d
-  return std::make_unique<DepthwiseConvMKLDNNPass>();
+  return std::make_unique<DepthwiseConvONEDNNPass>();
 }
 
 }  // namespace pir
 
-REGISTER_IR_PASS(depthwise_conv_onednn_pass, DepthwiseConvMKLDNNPass);
+REGISTER_IR_PASS(depthwise_conv_onednn_pass, DepthwiseConvONEDNNPass);

paddle/fluid/pir/transforms/onednn/depthwise_conv_onednn_pass.h

@@ -21,6 +21,6 @@ namespace pir {
 
 class Pass;
 
-IR_API std::unique_ptr<Pass> CreateDepthwiseConvMKLDNNPass();
+IR_API std::unique_ptr<Pass> CreateDepthwiseConvONEDNNPass();
 
 }  // namespace pir