add delta score, scale show (#33492)

paddle/fluid/framework/fleet/heter_ps/feature_value.h

@@ -52,25 +52,6 @@ struct FeaturePushValue {
   float lr_g;
   float mf_g[MF_DIM];
 };
-// class DownpourFixedFeatureValue {
-//    public:
-//        DownpourFixedFeatureValue() {}
-//        ~DownpourFixedFeatureValue() {}
-//        float* data() {
-//            return _data.data();
-//        }
-//        size_t size() {
-//            return _data.size();
-//        }
-//        void resize(size_t size) {
-//            _data.resize(size);
-//        }
-//        void shrink_to_fit() {
-//            _data.shrink_to_fit();
-//        }
-//    private:
-//        std::vector<float> _data;
-//    };
 
 }  // end namespace framework
 }  // end namespace paddle

paddle/fluid/framework/fleet/heter_ps/optimizer.cuh.h

@@ -23,30 +23,6 @@ limitations under the License. */
 namespace paddle {
 namespace framework {
 
-__device__ double cuda_double_random(unsigned long long seed) {
-  // copy from MurmurHash3
-  seed ^= seed >> 33;
-  seed *= 0xff51afd7ed558ccd;
-  seed ^= seed >> 33;
-  seed *= 0xc4ceb9fe1a85ec53;
-  seed ^= seed >> 33;
-  return ((double)seed / 18446744073709551615.0);
-}
-
-__device__ float cuda_normal_random(unsigned long long idx) {
-  static double pi = 3.1415926897932384;
-  unsigned long long x = clock64() + idx;
-  double x1, x2, res;
-  while (1) {
-    x1 = cuda_double_random(x);
-    x2 = cuda_double_random(x + 33);
-    res = sqrt(-2.0 * log(x1)) * cos(2.0 * pi * x2);
-    if (-10 < res && res < 10) break;
-    x += 207;
-  }
-  return res;
-}
-
 template <typename ValType, typename GradType>
 class Optimizer {
  public:
@@ -95,11 +71,12 @@ class Optimizer {
   }
   __device__ void update_value(ValType& val, const GradType& grad) {
     val.slot = grad.slot;
-    ;
     val.show += grad.show;
     val.clk += grad.clk;
+    val.delta_score += optimizer_config::nonclk_coeff * (grad.show - grad.clk) +
+                       optimizer_config::clk_coeff * grad.clk;
 
-    update_lr(val.lr, val.lr_g2sum, grad.lr_g, 1.0);
+    update_lr(val.lr, val.lr_g2sum, grad.lr_g, grad.show);
 
     if (val.mf_size == 0) {
       if (optimizer_config::mf_create_thresholds <=
@@ -116,7 +93,7 @@ class Optimizer {
         }
       }
     } else {
-      update_mf(MF_DIM, &val.mf[1], val.mf[0], grad.mf_g, 1.0);
+      update_mf(MF_DIM, &val.mf[1], val.mf[0], grad.mf_g, grad.show);
     }
   }
 };

paddle/fluid/framework/fleet/heter_ps/optimizer_conf.h

@@ -16,15 +16,16 @@ limitations under the License. */
 
 namespace optimizer_config {
 
-__constant__ float mf_create_thresholds = 0;
 __constant__ float nonclk_coeff = 0.1;
 __constant__ float clk_coeff = 1;
+
 __constant__ float min_bound = -10;
 __constant__ float max_bound = 10;
 __constant__ float learning_rate = 0.05;
 __constant__ float initial_g2sum = 3.0;
-__constant__ float initial_range = 1e-4;
+__constant__ float initial_range = 0;
 
+__constant__ float mf_create_thresholds = 10;
 __constant__ float mf_learning_rate = 0.05;
 __constant__ float mf_initial_g2sum = 3.0;
 __constant__ float mf_initial_range = 1e-4;

paddle/fluid/framework/io/fs.cc

@@ -240,16 +240,16 @@ void set_download_command(const std::string& x) {
 
 std::shared_ptr<FILE> hdfs_open_read(std::string path, int* err_no,
                                      const std::string& converter) {
+  if (download_cmd() != "") {  // use customized download command
+    path = string::format_string("%s \"%s\"", download_cmd().c_str(),
+                                 path.c_str());
+  } else {
     if (fs_end_with_internal(path, ".gz")) {
       path = string::format_string("%s -text \"%s\"", hdfs_command().c_str(),
                                    path.c_str());
     } else {
-    const std::string file_path = path;
       path = string::format_string("%s -cat \"%s\"", hdfs_command().c_str(),
-                                 file_path.c_str());
-    if (download_cmd() != "") {  // use customized download command
-      path = string::format_string("%s \"%s\"", download_cmd().c_str(),
-                                   file_path.c_str());
+                                   path.c_str());
     }
   }
 

python/paddle/fluid/incubate/fleet/parameter_server/pslib/optimizer_factory.py

@@ -24,6 +24,7 @@ from collections import OrderedDict
 import copy
 from .node import DownpourWorker, DownpourServer
 from . import ps_pb2 as pslib
+import os
 
 OpRole = core.op_proto_and_checker_maker.OpRole
 # this dict is for store info about pull/push sparse ops.
@@ -765,7 +766,8 @@ class DistributedAdam(DistributedOptimizerImplBase):
             "user_define_dump_filename", "")
         opt_info["dump_fields_path"] = strategy.get("dump_fields_path", "")
         opt_info["dump_param"] = strategy.get("dump_param", [])
-        opt_info["worker_places"] = strategy.get("worker_places", [])
+        gpus_env = os.getenv("FLAGS_selected_gpus")
+        opt_info["worker_places"] = [int(s) for s in gpus_env.split(",")]
         opt_info["use_ps_gpu"] = strategy.get("use_ps_gpu", False)
         if server._server.downpour_server_param.downpour_table_param[
                 0].accessor.accessor_class in [

python/paddle/fluid/incubate/fleet/utils/fleet_util.py

@@ -32,7 +32,7 @@ OpRole = core.op_proto_and_checker_maker.OpRole
 __all__ = ["FleetUtil"]
 
 _logger = get_logger(
-    __name__, logging.INFO, fmt='%(asctime)s-%(levelname)s: %(message)s')
+    __name__, logging.INFO, fmt='%(asctime)s %(levelname)s: %(message)s')
 
 fleet = None
 

python/paddle/fluid/log_helper.py

@@ -45,7 +45,7 @@ def get_logger(name, level, fmt=None):
     handler = logging.StreamHandler()
 
     if fmt:
-        formatter = logging.Formatter(fmt=fmt)
+        formatter = logging.Formatter(fmt=fmt, datefmt='%a %b %d %H:%M:%S')
         handler.setFormatter(formatter)
 
     logger.addHandler(handler)