提交 bbeb826f 编写于 作者: L Luo Tao

remove ProtoDataProvider in test_PyDataProvider.cpp

上级 b7df7f9e
./trainer/tests/pydata_provider_wrapper_dir/test_pydata_provider_wrapper.proto_data
...@@ -20,28 +20,6 @@ import random ...@@ -20,28 +20,6 @@ import random
import json import json
import string import string
@provider(slots=[
SparseNonValueSlot(10), DenseSlot(2), SparseValueSlot(10), StringSlot(1),
IndexSlot(3)
])
def processNonSequenceData(obj, filename):
with open(filename, "rb") as f:
for line in f:
slots_str = line.split(';')
index = int(slots_str[0])
non_values = map(int, slots_str[1].split()[1:])
dense = map(float, slots_str[2].split()[1:])
strs = slots_str[4].strip().split(' ', 1)[1]
def __values_mapper__(s):
s = s.split(":")
return int(s[0]), float(s[1])
values = map(__values_mapper__, slots_str[3].split()[1:])
yield [non_values, dense, values, strs, index]
SPARSE_ID_LIMIT = 1000 SPARSE_ID_LIMIT = 1000
SPARSE_ID_COUNT = 100 SPARSE_ID_COUNT = 100
SEQUENCE_LIMIT = 50 SEQUENCE_LIMIT = 50
...@@ -146,8 +124,6 @@ def processSubSeqAndGenerateData(obj, name): ...@@ -146,8 +124,6 @@ def processSubSeqAndGenerateData(obj, name):
if __name__ == "__main__": if __name__ == "__main__":
pvd = processNonSequenceData("test.txt")
print pvd.getNextBatch(100)
pvd = processSeqAndGenerateData("_") pvd = processSeqAndGenerateData("_")
print pvd.getNextBatch(100) print pvd.getNextBatch(100)
pvd = processSubSeqAndGenerateData("_") pvd = processSubSeqAndGenerateData("_")
......
...@@ -25,45 +25,9 @@ limitations under the License. */ ...@@ -25,45 +25,9 @@ limitations under the License. */
#include <unordered_set> #include <unordered_set>
#include "picojson.h" #include "picojson.h"
void checkEqual(const paddle::Argument& expect, const paddle::Argument& actual);
void checkValue(std::vector<paddle::Argument>& arguments, picojson::array& arr); void checkValue(std::vector<paddle::Argument>& arguments, picojson::array& arr);
const std::string kDir = "./trainer/tests/pydata_provider_wrapper_dir/"; const std::string kDir = "./trainer/tests/pydata_provider_wrapper_dir/";
TEST(PyDataProviderWrapper, NoSequenceData) {
paddle::DataConfig conf;
conf.set_type("py");
conf.set_load_data_module(std::string("testPyDataWrapper"));
conf.set_load_data_object(std::string("processNonSequenceData"));
conf.set_async_load_data(false);
conf.clear_files();
conf.set_files(kDir + "test_pydata_provider_wrapper.list");
paddle::DataProviderPtr provider(paddle::DataProvider::create(conf, false));
provider->setSkipShuffle();
provider->reset();
paddle::DataBatch batchFromPy;
provider->getNextBatch(100, &batchFromPy);
paddle::DataConfig conf2;
conf2.set_type("proto");
conf2.set_async_load_data(false);
conf2.clear_files();
conf2.set_files(kDir + "test_pydata_provider_wrapper.protolist");
provider.reset(paddle::DataProvider::create(conf2, false));
provider->setSkipShuffle();
provider->reset();
paddle::DataBatch batchFromProto;
provider->getNextBatch(100, &batchFromProto);
std::vector<paddle::Argument>& pyArguments = batchFromPy.getStreams();
std::vector<paddle::Argument>& protoArguments = batchFromProto.getStreams();
EXPECT_EQ(pyArguments.size(), protoArguments.size());
for (size_t i = 0; i < pyArguments.size(); ++i) {
checkEqual(protoArguments[i], pyArguments[i]);
}
}
TEST(PyDataProviderWrapper, SequenceData) { TEST(PyDataProviderWrapper, SequenceData) {
paddle::DataConfig conf; paddle::DataConfig conf;
conf.set_type("py"); conf.set_type("py");
...@@ -148,66 +112,6 @@ int main(int argc, char** argv) { ...@@ -148,66 +112,6 @@ int main(int argc, char** argv) {
return RUN_ALL_TESTS(); return RUN_ALL_TESTS();
} }
void checkEqual(const paddle::Argument& expect,
const paddle::Argument& actual) {
if (expect.value) {
EXPECT_TRUE(actual.value != nullptr);
paddle::Matrix* e = expect.value.get();
paddle::Matrix* a = actual.value.get();
EXPECT_EQ(e->getWidth(), a->getWidth());
EXPECT_EQ(e->getHeight(), a->getHeight());
if (dynamic_cast<paddle::CpuSparseMatrix*>(e)) {
paddle::CpuSparseMatrix* se = dynamic_cast<paddle::CpuSparseMatrix*>(e);
paddle::CpuSparseMatrix* sa = dynamic_cast<paddle::CpuSparseMatrix*>(a);
EXPECT_EQ(se->getFormat(), sa->getFormat());
EXPECT_EQ(se->getElementCnt(), sa->getElementCnt());
size_t rowSize = se->getFormat() == paddle::SPARSE_CSC
? se->getElementCnt()
: se->getHeight() + 1;
size_t colSize = se->getFormat() == paddle::SPARSE_CSC
? se->getWidth() + 1
: se->getElementCnt();
for (size_t i = 0; i < rowSize; ++i) {
EXPECT_EQ(se->getRows()[i], sa->getRows()[i]);
}
for (size_t i = 0; i < colSize; ++i) {
EXPECT_EQ(se->getCols()[i], sa->getCols()[i]);
}
if (se->getValueType() == paddle::FLOAT_VALUE) {
EXPECT_EQ(paddle::FLOAT_VALUE, sa->getValueType());
for (size_t i = 0; i < se->getElementCnt(); ++i) {
EXPECT_EQ(se->getValue()[i], sa->getValue()[i]);
}
}
} else if (dynamic_cast<paddle::CpuMatrix*>(e)) {
EXPECT_EQ(e->getElementCnt(), a->getElementCnt());
for (size_t i = 0; i < e->getElementCnt(); ++i) {
EXPECT_EQ(e->getData()[i], a->getData()[i]);
}
}
}
if (expect.ids) {
EXPECT_TRUE(actual.ids != nullptr);
paddle::VectorT<int>* e = expect.ids.get();
paddle::VectorT<int>* a = actual.ids.get();
EXPECT_EQ(e->getSize(), a->getSize());
for (size_t i = 0; i < e->getSize(); ++i) {
EXPECT_EQ(e->getData()[i], a->getData()[i]);
}
}
if (expect.strs) {
EXPECT_TRUE(actual.strs != nullptr);
std::vector<std::string>* e = expect.strs.get();
std::vector<std::string>* a = actual.strs.get();
EXPECT_EQ(e->size(), a->size());
for (size_t i = 0; i < e->size(); ++i) {
EXPECT_EQ((*e)[i], (*a)[i]);
}
}
}
void checkValue(std::vector<paddle::Argument>& arguments, void checkValue(std::vector<paddle::Argument>& arguments,
picojson::array& arr) { picojson::array& arr) {
// CHECK SLOT 0, Sparse Value. // CHECK SLOT 0, Sparse Value.
......
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