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!3486 Fix the performance test case of bert 

Merge pull request !3486 from chenhaozhe/fix_bert_performance_test_case
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mindspore-ci-bot 2020-07-25 17:54:02 +08:00 committed by Gitee
parent 7fbed0ce94 ef7ea3b92d
commit 7be664fa85
1 changed files with 3 additions and 7 deletions
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10
tests/st/networks/models/bert/test_bert_tdt_lossscale.py
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@ -101,12 +101,8 @@ def me_de_train_dataset(sink_mode=False):
type_cast_op = C.TypeCast(mstype.int32) type_cast_op = C.TypeCast(mstype.int32)
new_repeat_count = repeat_count new_repeat_count = repeat_count
if sink_mode: if sink_mode:
repeat_count = 30
sink_size = 100 sink_size = 100
ori_dataaet_size = ds.get_dataset_size() new_repeat_count = 3
new_size = sink_size * batch_size
ds.set_dataset_size(new_size)
new_repeat_count = int(repeat_count * ori_dataaet_size // ds.get_dataset_size())
ds = ds.map(input_columns="masked_lm_ids", operations=type_cast_op) ds = ds.map(input_columns="masked_lm_ids", operations=type_cast_op)
ds = ds.map(input_columns="masked_lm_positions", operations=type_cast_op) ds = ds.map(input_columns="masked_lm_positions", operations=type_cast_op)
ds = ds.map(input_columns="next_sentence_labels", operations=type_cast_op) ds = ds.map(input_columns="next_sentence_labels", operations=type_cast_op)
@ -264,7 +260,7 @@ def test_bert_performance():
config = get_config(version=version, batch_size=batch_size) config = get_config(version=version, batch_size=batch_size)
netwithloss = BertNetworkWithLoss(config, True) netwithloss = BertNetworkWithLoss(config, True)
lr = BertLearningRate(decay_steps=ds.get_dataset_size()*new_repeat_count, lr = BertLearningRate(decay_steps=sink_size * new_repeat_count,
learning_rate=5e-5, end_learning_rate=1e-9, learning_rate=5e-5, end_learning_rate=1e-9,
power=10.0, warmup_steps=0) power=10.0, warmup_steps=0)
decay_filter = lambda x: 'layernorm' not in x.name.lower() and 'bias' not in x.name.lower() decay_filter = lambda x: 'layernorm' not in x.name.lower() and 'bias' not in x.name.lower()
@ -302,7 +298,7 @@ def test_bert_performance():
else: else:
logger.info("***************** BERT param name is 3 {}".format(name)) logger.info("***************** BERT param name is 3 {}".format(name))
param.default_input = weight_variable(value.asnumpy().shape) param.default_input = weight_variable(value.asnumpy().shape)
time_monitor_callback = TimeMonitor(ds.get_dataset_size()) time_monitor_callback = TimeMonitor(sink_size)
model.train(new_repeat_count, ds, callbacks=[time_monitor_callback, callback], model.train(new_repeat_count, ds, callbacks=[time_monitor_callback, callback],
dataset_sink_mode=True, sink_size=sink_size) dataset_sink_mode=True, sink_size=sink_size)