提交 400bf520 编写于 作者: G guru4elephant

refine VLOG

上级 53ff72e1
......@@ -99,8 +99,8 @@ static void g_change_server_port() {
if (read_proto_conf(FLAGS_inferservice_path.c_str(),
FLAGS_inferservice_file.c_str(),
&conf) != 0) {
VLOG(WARNING) << "failed to load configure[" << FLAGS_inferservice_path
<< "," << FLAGS_inferservice_file << "].";
VLOG(2) << "failed to load configure[" << FLAGS_inferservice_path
<< "," << FLAGS_inferservice_file << "].";
return;
}
uint32_t port = conf.port();
......
......@@ -35,11 +35,11 @@ int StubImpl<T, C, R, I, O>::initialize(const VariantInfo& var,
}
_gchannel = init_channel(var, filter);
LOG(INFO) << "Create stub with tag: " << *tag << ", " << *tag_value
<< ", ep: " << ep;
VLOG(2) << "Create stub with tag: " << *tag << ", " << *tag_value
<< ", ep: " << ep;
} else {
_gchannel = init_channel(var, NULL);
LOG(INFO) << "Create stub without tag, ep " << ep;
VLOG(2) << "Create stub without tag, ep " << ep;
}
if (!_gchannel) {
......@@ -143,7 +143,7 @@ int StubImpl<T, C, R, I, O>::thrd_initialize() {
return -1;
}
LOG(WARNING) << "Succ thread initialize stub impl!";
VLOG(2) << "Succ thread initialize stub impl!";
return 0;
}
......@@ -370,7 +370,7 @@ google::protobuf::RpcChannel* StubImpl<T, C, R, I, O>::init_channel(
// brpc parallel channel
_pchannel = init_pchannel(_channel, _max_channel, _package_size, chn_options);
if (_pchannel) {
LOG(INFO) << "Succ create parallel channel, count: " << _max_channel;
VLOG(2) << "Succ create parallel channel, count: " << _max_channel;
return _pchannel;
}
......@@ -384,21 +384,21 @@ brpc::ParallelChannel* StubImpl<T, C, R, I, O>::init_pchannel(
uint32_t package_size,
const brpc::ChannelOptions& options) {
if (channel_count <= 1) { // noneed use parallel channel
LOG(INFO) << "channel count <= 1, noneed use pchannel.";
VLOG(2) << "channel count <= 1, noneed use pchannel.";
return NULL;
}
_pchannel = butil::get_object<brpc::ParallelChannel>();
if (!_pchannel) {
LOG(FATAL) << "Failed get pchannel from object pool";
VLOG(2) << "Failed get pchannel from object pool";
return NULL;
}
brpc::ParallelChannelOptions pchan_options;
pchan_options.timeout_ms = options.timeout_ms;
if (_pchannel->Init(&pchan_options) != 0) {
LOG(FATAL) << "Failed init parallel channel with tmo_us: "
<< pchan_options.timeout_ms;
VLOG(2) << "Failed init parallel channel with tmo_us: "
<< pchan_options.timeout_ms;
return NULL;
}
......
......@@ -52,9 +52,9 @@ int WeightedRandomRender::initialize(const google::protobuf::Message& conf) {
return -1;
}
LOG(INFO) << "Succ read weights list: " << weights
<< ", count: " << _variant_weight_list.size()
<< ", normalized: " << _normalized_sum;
VLOG(2) << "Succ read weights list: " << weights
<< ", count: " << _variant_weight_list.size()
<< ", normalized: " << _normalized_sum;
} catch (std::bad_cast& e) {
LOG(ERROR) << "Failed init WeightedRandomRender"
<< "from configure, err:" << e.what();
......@@ -87,9 +87,9 @@ Variant* WeightedRandomRender::route(const VariantList& variants) {
for (uint32_t ci = 0; ci < cand_size; ++ci) {
cur_total += _variant_weight_list[ci];
if (sample < cur_total) {
LOG(INFO) << "Sample " << sample << " on " << ci
<< ", _normalized: " << _normalized_sum
<< ", weight: " << _variant_weight_list[ci];
VLOG(2) << "Sample " << sample << " on " << ci
<< ", _normalized: " << _normalized_sum
<< ", weight: " << _variant_weight_list[ci];
return variants[ci];
}
}
......
......@@ -80,8 +80,8 @@ int EndpointConfigManager::load(const std::string& sdk_desc_str) {
LOG(ERROR) << "Failed load configure" << e.what();
return -1;
}
LOG(INFO) << "Success reload endpoint config file, id: "
<< _current_endpointmap_id;
VLOG(2) << "Success reload endpoint config file, id: "
<< _current_endpointmap_id;
return 0;
}
......@@ -128,8 +128,8 @@ int EndpointConfigManager::load() {
LOG(ERROR) << "Failed load configure" << e.what();
return -1;
}
LOG(INFO) << "Success reload endpoint config file, id: "
<< _current_endpointmap_id;
VLOG(2) << "Success reload endpoint config file, id: "
<< _current_endpointmap_id;
return 0;
}
......@@ -181,8 +181,8 @@ int EndpointConfigManager::init_one_endpoint(const configure::Predictor& conf,
return -1;
}
LOG(INFO) << "Succ load one endpoint, name: " << ep.endpoint_name
<< ", count of variants: " << ep.vars.size() << ".";
VLOG(2) << "Succ load one endpoint, name: " << ep.endpoint_name
<< ", count of variants: " << ep.vars.size() << ".";
} catch (std::exception& e) {
LOG(ERROR) << "Exception acccurs when load endpoint conf"
<< ", message: " << e.what();
......@@ -258,7 +258,7 @@ int EndpointConfigManager::merge_variant(const VariantInfo& default_var,
int EndpointConfigManager::parse_tag_values(SplitParameters& split) {
split.tag_values.clear();
if (!split.split_tag.init || !split.tag_cands_str.init) {
LOG(WARNING) << "split info not set, skip...";
VLOG(2) << "split info not set, skip...";
return 0;
}
......
......@@ -35,8 +35,8 @@ int Endpoint::initialize(const EndpointInfo& ep_info) {
return -1;
}
_variant_list.push_back(var);
LOG(INFO) << "Succ create variant: " << vi
<< ", endpoint:" << _endpoint_name;
VLOG(2) << "Succ create variant: " << vi
<< ", endpoint:" << _endpoint_name;
}
return 0;
......@@ -51,7 +51,7 @@ int Endpoint::thrd_initialize() {
return -1;
}
}
LOG(WARNING) << "Succ thrd initialize all vars: " << var_size;
VLOG(2) << "Succ thrd initialize all vars: " << var_size;
return 0;
}
......
......@@ -25,7 +25,7 @@ int PredictorApi::register_all() {
return -1;
}
LOG(WARNING) << "Succ register all components!";
VLOG(2) << "Succ register all components!";
return 0;
}
......@@ -66,8 +66,8 @@ int PredictorApi::create(const std::string & api_desc_str) {
return -1;
}
LOG(INFO) << "Succ create endpoint instance with name: "
<< ep_info.endpoint_name;
VLOG(2) << "Succ create endpoint instance with name: "
<< ep_info.endpoint_name;
}
return 0;
......@@ -101,7 +101,7 @@ int PredictorApi::create(const char* path, const char* file) {
return -1;
}
LOG(INFO) << "endpoint name: " << ep_info.endpoint_name;
VLOG(2) << "endpoint name: " << ep_info.endpoint_name;
std::pair<std::map<std::string, Endpoint*>::iterator, bool> r =
_endpoints.insert(std::make_pair(ep_info.endpoint_name, ep));
......@@ -110,8 +110,8 @@ int PredictorApi::create(const char* path, const char* file) {
return -1;
}
LOG(INFO) << "Succ create endpoint instance with name: "
<< ep_info.endpoint_name;
VLOG(2) << "Succ create endpoint instance with name: "
<< ep_info.endpoint_name;
}
return 0;
......@@ -126,7 +126,7 @@ int PredictorApi::thrd_initialize() {
return -1;
}
LOG(WARNING) << "Succ thrd initialize endpoint:" << it->first;
VLOG(2) << "Succ thrd initialize endpoint:" << it->first;
}
return 0;
}
......@@ -152,7 +152,7 @@ int PredictorApi::thrd_finalize() {
return -1;
}
LOG(INFO) << "Succ thrd finalize endpoint:" << it->first;
VLOG(2) << "Succ thrd finalize endpoint:" << it->first;
}
return 0;
}
......
......@@ -53,7 +53,7 @@ int Variant::initialize(const EndpointInfo& ep_info,
}
if (_stub_map.size() > 0) {
LOG(INFO) << "Initialize variants from VariantInfo"
VLOG(2) << "Initialize variants from VariantInfo"
<< ", stubs count: " << _stub_map.size();
return 0;
}
......@@ -66,7 +66,7 @@ int Variant::initialize(const EndpointInfo& ep_info,
}
_default_stub = stub;
LOG(INFO) << "Succ create default debug";
VLOG(2) << "Succ create default debug";
return 0;
}
......@@ -82,10 +82,10 @@ int Variant::thrd_initialize() {
LOG(ERROR) << "Failed thrd initialize stub: " << iter->first;
return -1;
}
LOG(INFO) << "Succ thrd initialize stub:" << iter->first;
VLOG(2) << "Succ thrd initialize stub:" << iter->first;
}
LOG(WARNING) << "Succ thrd initialize all stubs";
VLOG(2) << "Succ thrd initialize all stubs";
return 0;
}
......
......@@ -32,5 +32,5 @@ for pass_id in range(30):
fetch_list=[avg_loss])
serving_io.save_model(
"serving_server_model", "serving_client_conf",
{"x": x}, {"y": y_predict}, fluid.default_main_program())
"uci_housing_model", "uci_housing_client",
{"x": x}, {"price": y_predict}, fluid.default_main_program())
......@@ -46,18 +46,17 @@ if __name__ == "__main__":
dataset.set_use_var([data, label])
pipe_command = "python imdb_reader.py"
dataset.set_pipe_command(pipe_command)
dataset.set_batch_size(4)
dataset.set_batch_size(128)
dataset.set_filelist(filelist)
dataset.set_thread(10)
from nets import cnn_net
avg_cost, acc, prediction = cnn_net(data, label, dict_dim)
from nets import bow_net
avg_cost, acc, prediction = bow_net(data, label, dict_dim)
optimizer = fluid.optimizer.SGD(learning_rate=0.01)
optimizer.minimize(avg_cost)
exe = fluid.Executor(fluid.CPUPlace())
exe.run(fluid.default_startup_program())
epochs = 6
save_dirname = "cnn_model"
import paddle_serving_client.io as serving_io
......@@ -67,9 +66,5 @@ if __name__ == "__main__":
logger.info("TRAIN --> pass: {}".format(i))
if i == 5:
serving_io.save_model("serving_server_model", "serving_client_conf",
{"words": data,
"label": label}, {
"cost": avg_cost,
"acc": acc,
"prediction": prediction
}, fluid.default_main_program())
{"words": data}, {"prediction": prediction},
fluid.default_main_program())
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