未验证 提交 ae199073 编写于 作者: D daminglu 提交者: GitHub

Test word2vec (#10779)

上级 11b6473c
......@@ -236,8 +236,7 @@ void TestInference(const std::string& dirname,
// Disable the profiler and print the timing information
paddle::platform::DisableProfiler(
paddle::platform::EventSortingKey::kDefault,
"run_inference_profiler");
paddle::platform::EventSortingKey::kDefault, "run_inference_profiler");
paddle::platform::ResetProfiler();
}
......
......@@ -90,7 +90,7 @@ def train_program(is_sparse):
return avg_cost
def train(use_cuda, train_program, save_path):
def train(use_cuda, train_program, save_dirname):
train_reader = paddle.batch(
paddle.dataset.imikolov.train(word_dict, N), BATCH_SIZE)
test_reader = paddle.batch(
......@@ -99,27 +99,36 @@ def train(use_cuda, train_program, save_path):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
def event_handler(event):
if isinstance(event, fluid.EndEpochEvent):
outs = trainer.test(reader=test_reader)
if isinstance(event, fluid.EndStepEvent):
outs = trainer.test(
reader=test_reader,
feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw'])
avg_cost = outs[0]
print("loss= ", avg_cost)
if avg_cost < 5.0:
trainer.save_params(save_path)
return
if avg_cost < 10.0:
trainer.save_params(save_dirname)
trainer.stop()
if math.isnan(avg_cost):
sys.exit("got NaN loss, training failed.")
trainer = fluid.Trainer(
train_program, fluid.optimizer.SGD(learning_rate=0.001), place=place)
train_func=train_program,
optimizer=fluid.optimizer.SGD(learning_rate=0.001),
place=place)
trainer.train(
reader=train_reader, num_epochs=1, event_handler=event_handler)
reader=train_reader,
num_epochs=1,
event_handler=event_handler,
feed_order=['firstw', 'secondw', 'thirdw', 'forthw', 'nextw'])
def infer(use_cuda, inference_program, save_path):
def infer(use_cuda, inference_program, save_dirname=None):
place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
inferencer = fluid.Inferencer(
infer_func=inference_program, param_path=save_path, place=place)
infer_func=inference_program, param_path=save_dirname, place=place)
lod = [0, 1]
first_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
......@@ -127,12 +136,14 @@ def infer(use_cuda, inference_program, save_path):
third_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
fourth_word = create_random_lodtensor(lod, place, low=0, high=dict_size - 1)
result = inferencer.infer({
result = inferencer.infer(
{
'firstw': first_word,
'secondw': second_word,
'thirdw': third_word,
'forthw': fourth_word
})
},
return_numpy=False)
print(np.array(result[0]))
......@@ -140,9 +151,17 @@ def main(use_cuda, is_sparse):
if use_cuda and not fluid.core.is_compiled_with_cuda():
return
save_path = "word2vec.params"
train(use_cuda, partial(train_program, is_sparse), save_path)
infer(use_cuda, partial(inference_program, is_sparse), save_path)
save_path = "word2vec.inference.model"
train(
use_cuda=use_cuda,
train_program=partial(train_program, is_sparse),
save_dirname=save_path)
infer(
use_cuda=use_cuda,
inference_program=partial(inference_program, is_sparse),
save_dirname=save_path)
if __name__ == '__main__':
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册