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Merge commit '75bf97b57539e5572e7ae8eba72bac6562c63c07'

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Conflicts:
	subtree/rabit/rabit-learn/io/line_split-inl.h
	subtree/rabit/yarn/build.sh
This commit is contained in:
tqchen
2015-03-21 00:48:34 -07:00
parent 5648bec8a3 75bf97b575
commit 9ccbeaa8f0
34 changed files with 856 additions and 201 deletions
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10
subtree/rabit/rabit-learn/linear/Makefile
View File

@@ -1,4 +1,10 @@
# specify tensor path
ifneq ("$(wildcard ../config.mk)","")
config = ../config.mk
else
config = ../make/config.mk
endif
include $(config)
BIN = linear.rabit
MOCKBIN= linear.mock
MPIBIN =
@@ -6,10 +12,10 @@ MPIBIN =
OBJ = linear.o
# common build script for programs
include ../make/config.mk
include ../make/common.mk
CFLAGS+=-fopenmp
linear.o: linear.cc ../../src/*.h linear.h ../solver/*.h
# dependenies here
linear.rabit: linear.o lib
linear.mock: linear.o lib

11
subtree/rabit/rabit-learn/linear/linear.cc
View File

@@ -206,21 +206,22 @@ int main(int argc, char *argv[]) {
rabit::Finalize();
return 0;
}
rabit::linear::LinearObjFunction linear;
rabit::linear::LinearObjFunction *linear = new rabit::linear::LinearObjFunction();
if (!strcmp(argv[1], "stdin")) {
linear.LoadData(argv[1]);
linear->LoadData(argv[1]);
rabit::Init(argc, argv);
} else {
rabit::Init(argc, argv);
linear.LoadData(argv[1]);
linear->LoadData(argv[1]);
}
for (int i = 2; i < argc; ++i) {
char name[256], val[256];
if (sscanf(argv[i], "%[^=]=%s", name, val) == 2) {
linear.SetParam(name, val);
linear->SetParam(name, val);
}
}
linear.Run();
linear->Run();
delete linear;
rabit::Finalize();
return 0;
}

5
subtree/rabit/rabit-learn/linear/linear.h
View File

@@ -26,10 +26,11 @@ struct LinearModel {
int reserved[16];
// constructor
ModelParam(void) {
memset(this, 0, sizeof(ModelParam));
base_score = 0.5f;
num_feature = 0;
loss_type = 1;
std::memset(reserved, 0, sizeof(reserved));
num_feature = 0;
}
// initialize base score
inline void InitBaseScore(void) {
@@ -119,7 +120,7 @@ struct LinearModel {
}
fi.Read(weight, sizeof(float) * (param.num_feature + 1));
}
inline void Save(rabit::IStream &fo, const float *wptr = NULL) const {
inline void Save(rabit::IStream &fo, const float *wptr = NULL) {
fo.Write(&param, sizeof(param));
if (wptr == NULL) wptr = weight;
fo.Write(wptr, sizeof(float) * (param.num_feature + 1));

5
subtree/rabit/rabit-learn/linear/run-yarn.sh
View File

@@ -6,12 +6,13 @@ then
fi
# put the local training file to HDFS
hadoop fs -rm -r -f $2/data
hadoop fs -rm -r -f $2/mushroom.linear.model
hadoop fs -mkdir $2/data
hadoop fs -put ../data/agaricus.txt.train $2/data
# submit to hadoop
../../tracker/rabit_yarn.py -n $1 --vcores 1 linear.rabit hdfs://$2/data/agaricus.txt.train model_out=hdfs://$2/mushroom.linear.model "${*:3}"
../../tracker/rabit_yarn.py -n $1 --vcores 1 ./linear.rabit hdfs://$2/data/agaricus.txt.train model_out=hdfs://$2/mushroom.linear.model "${*:3}"
# get the final model file
hadoop fs -get $2/mushroom.linear.model ./linear.model