From f12291a38c8cb0ec71758ed65adb8d0a39ae8cb4 Mon Sep 17 00:00:00 2001 From: yoonlee666 Date: Fri, 18 Sep 2020 17:06:35 +0800 Subject: [PATCH] bugfix bert perf test --- tests/perf_test/bert/test_bert_train.py | 18 ++++++------------ 1 file changed, 6 insertions(+), 12 deletions(-) diff --git a/tests/perf_test/bert/test_bert_train.py b/tests/perf_test/bert/test_bert_train.py index 705318c283..6df1109613 100644 --- a/tests/perf_test/bert/test_bert_train.py +++ b/tests/perf_test/bert/test_bert_train.py @@ -54,13 +54,12 @@ def load_test_data(batch_size=1): return ret -def get_config(version='base', batch_size=1): +def get_config(version='base'): """ get_config definition """ if version == 'base': return BertConfig( - batch_size=batch_size, seq_length=128, vocab_size=21128, hidden_size=768, @@ -74,13 +73,10 @@ def get_config(version='base', batch_size=1): type_vocab_size=2, initializer_range=0.02, use_relative_positions=True, - input_mask_from_dataset=True, - token_type_ids_from_dataset=True, dtype=mstype.float32, compute_type=mstype.float32) if version == 'large': return BertConfig( - batch_size=batch_size, seq_length=128, vocab_size=21128, hidden_size=1024, @@ -94,11 +90,9 @@ def get_config(version='base', batch_size=1): type_vocab_size=2, initializer_range=0.02, use_relative_positions=True, - input_mask_from_dataset=True, - token_type_ids_from_dataset=True, dtype=mstype.float32, compute_type=mstype.float32) - return BertConfig(batch_size=batch_size) + return BertConfig() class BertLearningRate(lr_schedules.LearningRateSchedule): @@ -143,7 +137,7 @@ def test_bert_train(): batch_size = int(os.getenv('BATCH_SIZE', '1')) inputs = load_test_data(batch_size) - config = get_config(version=version, batch_size=batch_size) + config = get_config(version=version) netwithloss = BertNetworkWithLoss(config, True) lr = BertLearningRate(10) optimizer = AdamWeightDecay(netwithloss.trainable_params(), lr) @@ -168,7 +162,7 @@ def test_bert_withlossscale_train(): scaling_sens = Tensor(np.ones([1]).astype(np.float32)) inputs = load_test_data(batch_size) + (scaling_sens,) - config = get_config(version=version, batch_size=batch_size) + config = get_config(version=version) netwithloss = BertNetworkWithLoss(config, True) lr = BertLearningRate(10) optimizer = AdamWeightDecay(netwithloss.trainable_params(), lr) @@ -195,7 +189,7 @@ def bert_withlossscale_manager_train(): batch_size = int(os.getenv('BATCH_SIZE', '1')) inputs = load_test_data(batch_size) - config = get_config(version=version, batch_size=batch_size) + config = get_config(version=version) netwithloss = BertNetworkWithLoss(config, True) lr = BertLearningRate(10) optimizer = AdamWeightDecay(netwithloss.trainable_params(), lr) @@ -223,7 +217,7 @@ def bert_withlossscale_manager_train_feed(): scaling_sens = Tensor(np.ones([1]).astype(np.float32)) inputs = load_test_data(batch_size) + (scaling_sens,) - config = get_config(version=version, batch_size=batch_size) + config = get_config(version=version) netwithloss = BertNetworkWithLoss(config, True) lr = BertLearningRate(10) optimizer = AdamWeightDecay(netwithloss.trainable_params(), lr)