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提交 9c3cd3c7 编写于 作者: X Xinghai Sun

Update some parameters and comments.

上级 0babc5c4
......@@ -26,6 +26,8 @@ parser.add_argument(
"--rnn_layer_size", default=256, type=int, help="RNN layer cell number.")
parser.add_argument(
"--use_gpu", default=True, type=bool, help="Use gpu or not.")
parser.add_argument(
"--use_sortagrad", default=False, type=bool, help="Use sortagrad or not.")
parser.add_argument(
"--trainer_count", default=8, type=int, help="Trainer number.")
args = parser.parse_args()
......@@ -56,12 +58,9 @@ def train():
# create parameters and optimizer
parameters = paddle.parameters.create(cost)
optimizer = paddle.optimizer.Adam(
learning_rate=5e-5,
gradient_clipping_threshold=5,
regularization=paddle.optimizer.L2Regularization(rate=8e-4))
learning_rate=5e-4, gradient_clipping_threshold=400)
trainer = paddle.trainer.SGD(
cost=cost, parameters=parameters, update_equation=optimizer)
# create data readers
feeding = {
"audio_spectrogram": 0,
......@@ -70,13 +69,13 @@ def train():
train_batch_reader_with_sortagrad = audio_data_utils.padding_batch_reader(
paddle.batch(
audio_data_utils.reader_creator(
manifest_path="./libri.manifest.dev", sort_by_duration=True),
manifest_path="./libri.manifest.train", sort_by_duration=True),
batch_size=args.batch_size // args.trainer),
padding=[-1, 1000])
train_batch_reader_without_sortagrad = audio_data_utils.padding_batch_reader(
paddle.batch(
audio_data_utils.reader_creator(
manifest_path="./libri.manifest.dev",
manifest_path="./libri.manifest.train",
sort_by_duration=False,
shuffle=True),
batch_size=args.batch_size // args.trainer),
......@@ -84,7 +83,7 @@ def train():
test_batch_reader = audio_data_utils.padding_batch_reader(
paddle.batch(
audio_data_utils.reader_creator(
manifest_path="./libri.manifest.test", sort_by_duration=False),
manifest_path="./libri.manifest.dev", sort_by_duration=False),
batch_size=args.batch_size // args.trainer),
padding=[-1, 1000])
......@@ -92,27 +91,31 @@ def train():
def event_handler(event):
if isinstance(event, paddle.event.EndIteration):
if event.batch_id % 10 == 0:
print "Pass: %d, Batch: %d, TrainCost: %f, %s" % (
event.pass_id, event.batch_id, event.cost, event.metrics)
print "/nPass: %d, Batch: %d, TrainCost: %f" % (
event.pass_id, event.batch_id, event.cost)
else:
sys.stdout.write('.')
sys.stdout.flush()
if isinstance(event, paddle.event.EndPass):
result = trainer.test(reader=test_batch_reader, feeding=feeding)
print "Pass: %d, TestMetric: %s" % (event.pass_id, result.metrics)
print "Pass: %d, TestCost: %s" % (event.pass_id, result.cost)
with gzip.open("params.tar.gz", 'w') as f:
parameters.to_tar(f)
# run train
trainer.train(
reader=train_batch_reader_with_sortagrad,
event_handler=event_handler,
num_passes=1,
feeding=feeding)
# first pass with sortagrad
if args.use_sortagrad:
trainer.train(
reader=train_batch_reader_with_sortagrad,
event_handler=event_handler,
num_passes=1,
feeding=feeding)
args.num_passes -= 1
# other passes without sortagrad
trainer.train(
reader=train_batch_reader_without_sortagrad,
event_handler=event_handler,
num_passes=self.num_passes - 1,
num_passes=args.num_passes,
feeding=feeding)
......
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