From b67ce353fae31a352bfe0642925139f87aa2d858 Mon Sep 17 00:00:00 2001 From: "Yang Yang(Tony)" Date: Wed, 16 May 2018 14:02:29 -0700 Subject: [PATCH] speed up test label semantic roles (#10718) --- .../tests/book/test_label_semantic_roles.py | 27 +++++-------------- 1 file changed, 6 insertions(+), 21 deletions(-) diff --git a/python/paddle/fluid/tests/book/test_label_semantic_roles.py b/python/paddle/fluid/tests/book/test_label_semantic_roles.py index 09793760e55..f1ee5dfd99e 100644 --- a/python/paddle/fluid/tests/book/test_label_semantic_roles.py +++ b/python/paddle/fluid/tests/book/test_label_semantic_roles.py @@ -182,12 +182,6 @@ def train(use_cuda, save_dirname=None, is_local=True): crf_decode = fluid.layers.crf_decoding( input=feature_out, param_attr=fluid.ParamAttr(name='crfw')) - chunk_evaluator = fluid.evaluator.ChunkEvaluator( - input=crf_decode, - label=target, - chunk_scheme="IOB", - num_chunk_types=int(math.ceil((label_dict_len - 1) / 2.0))) - train_data = paddle.batch( paddle.reader.shuffle( paddle.dataset.conll05.test(), buf_size=8192), @@ -203,7 +197,6 @@ def train(use_cuda, save_dirname=None, is_local=True): def train_loop(main_program): exe.run(fluid.default_startup_program()) - embedding_param = fluid.global_scope().find_var( embedding_name).get_tensor() embedding_param.set( @@ -213,27 +206,19 @@ def train(use_cuda, save_dirname=None, is_local=True): start_time = time.time() batch_id = 0 for pass_id in xrange(PASS_NUM): - chunk_evaluator.reset(exe) for data in train_data(): - cost, precision, recall, f1_score = exe.run( - main_program, - feed=feeder.feed(data), - fetch_list=[avg_cost] + chunk_evaluator.metrics) - pass_precision, pass_recall, pass_f1_score = chunk_evaluator.eval( - exe) + cost = exe.run(main_program, + feed=feeder.feed(data), + fetch_list=[avg_cost]) + cost = cost[0] if batch_id % 10 == 0: - print("avg_cost:" + str(cost) + " precision:" + str( - precision) + " recall:" + str(recall) + " f1_score:" + - str(f1_score) + " pass_precision:" + str( - pass_precision) + " pass_recall:" + str( - pass_recall) + " pass_f1_score:" + str( - pass_f1_score)) + print("avg_cost:" + str(cost)) if batch_id != 0: print("second per batch: " + str((time.time( ) - start_time) / batch_id)) # Set the threshold low to speed up the CI test - if float(pass_precision) > 0.01: + if float(cost) < 60.0: if save_dirname is not None: # TODO(liuyiqun): Change the target to crf_decode fluid.io.save_inference_model(save_dirname, [ -- GitLab