Merge pull request #3548 from tensor-tang/remove-flag

Remove flag use_mkldnn_wgt

paddle/gserver/layers/MKLDNNFcLayer.cpp

@@ -57,11 +57,14 @@ bool MKLDNNFcLayer::init(const LayerMap& layerMap,
 }
 
 void MKLDNNFcLayer::convertWeightsFromPaddle() {
-  if (FLAGS_use_mkldnn_wgt) {
+  if (hasInitedWgt_) {
     return;
   }
 
-  if (hasInitedWgt_) {
+  // TODO(TJ): dst format should get from wgtVal_
+  int dstFmt = PARAM_FORMAT_MKLDNN_OI;
+  int srcFmt = weight_->getParameterPtr()->getHeaderFormat();
+  if (srcFmt == dstFmt) {
     return;
   }
 
@@ -78,6 +81,7 @@ void MKLDNNFcLayer::convertWeightsFromPaddle() {
   MatrixPtr paddleWgtT;
   paddleWgt->transpose(paddleWgtT, true);
   weight_->getW()->copyFrom(*paddleWgtT);
+  weight_->getParameterPtr()->setHeaderFormat(dstFmt);
   hasInitedWgt_ = true;
 }
 

paddle/gserver/tests/MKLDNNTester.cpp

@@ -330,9 +330,7 @@ void MKLDNNTester::run(const TestConfig& dnn,
   log_ = log;
   lvl_ = level;
 
-  // Firstly test FLAGS_use_mkldnn_wgt = false
-  FLAGS_use_mkldnn_wgt = false;
-  // reset and run once
+  // Firstly test mkldnn init from PARAM_FORMAT_ORIGINAL weight
   reset(dnn, ref, batchSize);
   randomWgtDatas();
   clearWgtDiffs();
@@ -342,17 +340,32 @@ void MKLDNNTester::run(const TestConfig& dnn,
     runOnce();
   }
 
-  // Then test FLAGS_use_mkldnn_wgt = true
-  FLAGS_use_mkldnn_wgt = true;
-  // after run once the mkldnn weight has been stored in dnnlayer
+  if (parameters_[DNN].empty()) {
+    // has no paramters
+    return;
+  }
+
+  // After run some iterations, the mkldnn weight has been stored in dnnLayer
+  // and we can also get the mkldnn weight parameter header format.
+  // Weight parameter should always be index 0 (and bias index 1).
+  // TODO(TJ): should also consider mean and var format when batchnorm ready
+  int dnnWgtFmt = parameters_[DNN][0]->getHeaderFormat();
+  int refWgtFmt = parameters_[REF][0]->getHeaderFormat();
+  if (dnnWgtFmt == refWgtFmt) {
+    // weight format are equal, so no need check more
+    return;
+  }
+
   // then save the weights and restart again
   vector<VectorPtr> dnnWgts, refWgts;
   CHECK_EQ(parameters_[DNN].size(), parameters_[REF].size());
   saveWgt(parameters_[DNN], dnnWgts);
   saveWgt(parameters_[REF], refWgts);
 
-  // restart again with flag true
+  // restart again with dnn weight format
   reset(dnn, ref, batchSize);
+  // TODO(TJ): should also considerate mean and var format when batchnorm ready
+  parameters_[DNN][0]->setHeaderFormat(dnnWgtFmt);
 
   // restore wgt
   restoreWgt(dnnWgts, parameters_[DNN]);

paddle/gserver/tests/MKLDNNTester.h

@@ -108,7 +108,7 @@ private:
    * if many(>failRate) wrong(abs(dnn-ref)/abs(ref)>thres) points return the
    * max(diff/ref)
    * else return sum(abs(a-b)) / sum(abs(b))
-   * The return value should smaller than eps when passing.
+   * The return value should be smaller than eps when passing.
    */
   double getDelta(const real* d1,
                   const real* d2,

paddle/parameter/Parameter.cpp

@@ -48,7 +48,8 @@ Parameter::Parameter(const ParameterConfig& config, bool useGpu, bool doInit)
       deviceId_(-1),
       sharedCount_(0),
       updateCounter_(0),
-      updated_(false) {
+      updated_(false),
+      headerFormat_(PARAM_FORMAT_ORIGINAL) {
   setID(-1); /* capture uninitialized id */
   if (useGpu_ && FLAGS_parallel_nn) {
     /* gpu environment is specified by device property */
@@ -285,7 +286,7 @@ bool Parameter::save(const std::string& filename) const {
 bool Parameter::save(std::ostream& s) const {
   CpuVector vec(*bufs_[PARAMETER_VALUE].get());
   Header header;
-  header.version = kFormatVersion;
+  header.format = headerFormat_;
   header.valueSize = sizeof(real);
   header.size = getSize();
 
@@ -344,8 +345,9 @@ bool Parameter::load(std::istream& s) {
   Header header;
   CHECK(s.read(reinterpret_cast<char*>(&header), sizeof(header)))
       << "Fail to read parameter " << getName();
-  CHECK_EQ(header.version, kFormatVersion) << "Incorrect format version: "
-                                           << header.version;
+  CHECK(isHeaderFormatSupported(header.format)) << "Incorrect format version: "
+                                                << header.format;
+  headerFormat_ = header.format;
   CHECK_EQ(header.size, getSize())
       << "The size (" << header.size << ") in the file does not match the size "
       << "(" << getSize() << ") of the parameter: " << getName();

paddle/parameter/Parameter.h

@@ -34,6 +34,20 @@ limitations under the License. */
 
 namespace paddle {
 
+typedef enum {
+  /// The paddle original basic format
+  PARAM_FORMAT_ORIGINAL = 0,
+
+  /// See mkldnn_memory_format_t in
+  /// https://github.com/01org/mkl-dnn/blob/master/include/mkldnn_types.h
+  /// for a detailed description.
+  /// 2D weights tensor in the format (output channels, input channels).
+  PARAM_FORMAT_MKLDNN_OI,
+
+  /// The total format items numbers
+  PARAM_FORMAT_ITEMS,
+} PARAM_FORMAT;
+
 class SparsePrefetchRowCpuMatrix;
 
 class Parameter;
@@ -242,14 +256,30 @@ public:
   /// Initialize the value to 0
   void zeroMem();
 
-  static const int kFormatVersion = 0;
   /// file header structure
   struct Header {
-    int32_t version;     // = 0, file format version
+    int32_t format;      // = PARAM_FORMAT
     uint32_t valueSize;  // = sizeof(real)
     uint64_t size;       // = getSize()
   };
 
+  /**
+   * @brief Is the header format supported.
+   */
+  static bool isHeaderFormatSupported(int32_t fmt) {
+    return fmt < PARAM_FORMAT_ITEMS;
+  }
+
+  /**
+   * @brief Get the format in header.
+   */
+  int getHeaderFormat() { return headerFormat_; }
+
+  /**
+   * @brief Set the format in header.
+   */
+  void setHeaderFormat(int32_t fmt) { headerFormat_ = fmt; }
+
   /**
    * @brief  Parameter Update Hook.
    *
@@ -321,6 +351,9 @@ protected:
   bool updated_;
   SparseFormat format_;
 
+  /// The header format for saving or loading param
+  int32_t headerFormat_;
+
   std::vector<std::shared_ptr<IParameterUpdaterHook>> updaterHooks_;
 
 public:

paddle/pserver/ParameterServer2.cpp

@@ -1032,8 +1032,8 @@ void ParameterServer2::loadValueVector(const LoadValueRequest& request,
   Parameter::Header header;
   CHECK(fs.read(reinterpret_cast<char*>(&header), sizeof(header)))
       << "Fail to read parameters in pserver";
-  CHECK_EQ(header.version, Parameter::kFormatVersion)
-      << "Incorrect format version: " << header.version;
+  CHECK(Parameter::isHeaderFormatSupported(header.format))
+      << "Incorrect format version: " << header.format;
   CHECK_EQ(header.size, (size_t)size_)
       << "The size (" << header.size << ") in the file does not match the size "
       << "(" << size_ << ") of the pserver: " << serverId_;
@@ -1063,7 +1063,8 @@ void ParameterServer2::saveValueVector(const SaveValueRequest& request,
   CpuVector& vec = vectors_[PARAMETER_APPLY] ? *vectors_[PARAMETER_APPLY]
                                              : *vectors_[PARAMETER_VALUE];
   Parameter::Header header;
-  header.version = Parameter::kFormatVersion;
+  // TODO(TJ): save param headerFormat_
+  header.format = PARAM_FORMAT_ORIGINAL;
   header.valueSize = sizeof(real);
   header.size = size_;
 

paddle/trainer/TrainerConfigHelper.cpp

@@ -29,7 +29,6 @@ DECLARE_bool(with_gpu);
 DECLARE_bool(parallel_nn);
 DECLARE_string(config_args);
 DECLARE_bool(use_mkldnn);
-DECLARE_bool(use_mkldnn_wgt);
 
 const char *kConfigParserModuleName = "paddle.trainer.config_parser";
 const char *kConfigParserFuncName = "parse_config_and_serialize";
@@ -47,7 +46,6 @@ TrainerConfigHelper::TrainerConfigHelper(const std::string &configFilePath)
              << ",with_cost=" << FLAGS_with_cost << ",use_gpu=" << FLAGS_use_gpu
              << ",parallel_nn=" << FLAGS_parallel_nn
              << ",use_mkldnn=" << FLAGS_use_mkldnn
-             << ",use_mkldnn_wgt=" << FLAGS_use_mkldnn_wgt
              << ",cudnn_version=" << hl_get_cudnn_lib_version();
   if (!FLAGS_config_args.empty()) {
     configArgs << "," << FLAGS_config_args;

paddle/utils/Flags.cpp

@@ -27,7 +27,6 @@ DEFINE_bool(use_mkldnn, false, "Default still keep use CPU training");
 DEFINE_bool(use_mkldnn, false, "Only support CPU training");
 #endif
 
-DEFINE_bool(use_mkldnn_wgt, false, "Init weight from CPU weight");
 DEFINE_bool(parallel_nn,
             false,
             "Whether to use multi-threads to calculate one neural network."

paddle/utils/Flags.h

@@ -41,4 +41,3 @@ DECLARE_string(predict_file);
 DECLARE_bool(prev_batch_state);
 DECLARE_string(init_model_path);
 DECLARE_bool(use_mkldnn);
-DECLARE_bool(use_mkldnn_wgt);